Good Morning,

I want to do a visual tour of some of my favorite infographics and updates of the AI Index report. I think it would be fair of me to suggest that this year’s report emphasizes that while AI capability is accelerating, the governance and safety frameworks meant to manage it are struggling to keep pace.

The reason this exists is the AI Index came out of a project of the One Hundred Year Study on AI at Stanford to serve as a faster-paced annual lens on advancing AI capabilities.

Browse the Slides

The jagged frontier speaks of a quickly developing industry that is a great lens on the State of AI over the past year 2025-2026 and the big picture. While a lot of the AI reports I read are from Venture Capital funds whose job it is to make AI look amazing, with an academic institution we can hope to find a less biased snapshot. I am not sure if that turns out to be true however. The AI Index that was established in 2019 as an independent project claiming to provide unbiased, rigorous data on the progress of AI. You can follow the Stanford Institute for Human-Centered AI (HAI) here. View their latest news here.

AI News in a Nutshell

Last week Anthropic released:

• Claude Opus 4.7

• Claude Design

What to use Claude Design For?

Initial test use cases for the tool are as follows:

• Realistic prototypes: Designers can turn static mockups into easily-shareable interactive prototypes to gather feedback and user-test, without code review or PRs.

• Product wireframes and mockups: Product Managers can sketch out feature flows and hand them off to Claude Code for implementation, or share them with designers to refine further.

• Design explorations: Designers can quickly create a wide range of directions to explore.

• Pitch decks and presentations: Founders and Account Executives can go from a rough outline to a complete, on-brand deck in minutes, and then export as a PPTX or send to Canva.

• Marketing collateral: Marketers can create landing pages, social media assets, and campaign visuals, then loop in designers to polish.

• Frontier design: Anyone can build code-powered prototypes with voice, video, shaders, 3D and built-in AI.

You can also use Cursor for Designers that integrates with Figma.

Opus 4.7 is built to be a "digital employee" rather than just a chatbot, not the same as the Mythos model they are still studying. In general, Anthropic recommends Opus 4.7 for demanding use cases where you need frontier intelligence — particularly production-ready code, sophisticated AI agents, and complex document creation. In particular I will note that Opus 4.7 seems to have improved a lot in:

Opus 4.7 as the first “Digital Employee” Type Model

• Instruction following.

• Improved multimodal support: like vision.

• Real-world work; like Finance.

• Memory and using file-system based memory.

• Long-running tasks.

Opus 4.7 is a “Doer”

Opus 4.7 handles complex, long-running tasks with rigor and consistency, pays precise attention to instructions, and devises ways to verify its own outputs before reporting back and as such its fine-tuned to be especially good at agentic coding and related tasks.

It’s likely to be one of the more capable global models of the Spring of 2026.

At its best, the AI Index is a distillation of thousands of articles, research papers, and model data, carefully organized and synthesized.

• 12 Takeaways from the Report

• Want to understand the current state of AI? Check out these charts. (MIT)

Which Companies are Leading in AI?

Furthermore Forbes just released their 2026 (8th annual) edition of their “AI 50” read it here. Supposedly, the iteration of the Forbes 2026 AI 50 list highlights a significant shift in the industry, as leading startups demonstrate a transition from experimental technology to sustainable, revenue-generating businesses. Indeed a few on this list will go public in the next 18 months.

A lot of these have indeed seen ARR growth in the last year that’s surprising to say the least and/or seen valuations grow very quickly. I’m going to link to their LinkedIn profiles so you can quickly learn a bit more about them:

1) Legora - legal automation software (Stockholm)
2) Cursor - AI coding platform (Bay Area / NY)
3) Reflection - open source AI models (NY)
4) Physical Intelligence - AI models for robotics (Bay Area)
5) Speak - AI language tutor (Bay Area)
6) Chai Discovery - AI drug discovery (Bay Area)
7) Black Forest Labs - Image and video generation software (Freiburg)
8) World Labs - Spatial AI model developer (Bay Area)
9) Skild AI - AI systems for robotics (Pittsburgh)
10) Sierra - AI agents for customer service (Bay Area)
11) Mistral AI - Open source AI model developer (Paris)
12) Mercor - Data labeling service (Bay Area)
13) Lovable - AI app and website builder (Stockholm)
14) Listen Labs - AI market research tools (Bay Area)
15) Thinking Machines Lab - AI research and products (Bay Area)
16) Genspark - AI tools for knowledge workers (Palo Alto)
17) Decagon - AI agents for customer service (Bay Area)
18) Together AI- AI cloud provider (Bay Area)
19) Suno - Music generation software (Cambridge)
20) Rogo - AI finance tools (NY)
21) Perplexity - AI search engine (Bay Area)
22) OpenEvidence - AI search for doctors (Miami)
23) krea.ai - Image generation software (Bay Area)
24) HeyGen - AI video generation (LA)
25) Harvey - Legal automation software (Bay Area)
26) Fireworks AI - AI app development software (San Mateo)
27) ElevenLabs - Voice generation software (NY)
28) Safe Superintelligence - AI research (Palo Alto)
29) Midjourney - Image generation software (Bay Area)
30) fal - Generative media infrastructure (Bay Area)
31) Cyera - AI data security (NY)
32) Notion - productivity software (Bay Area)
33) Surge AI - Data labeling service (Bay Area)
34) Gamma - AI graphic design tools (Bay Area)
35) Glean - Enterprise search engine (Palo Alto)
36) Cohere - AI model developer (Toronto)
37) Baseten - AI app deployment software (Bay Area)
38) Runway - Video and image editing software (NY)
39) Crusoe - AI data center builder (Denver)
40) Abridge - AI notetaker for doctors (Bay Area)
41) Synthesia - AI avatar and video generator (London)
42) SambaNova - AI chipmaker (San Jose)
43) EliseAI - AI agents for housing and healthcare (NY)
44) Clay - AI go-to-market tools (NY)
45) Applied Intuition - Self-driving software (Sunnyvale)
46) Cognition - AI coding agents (Bay Area)
47) Replit - AI app and website builder (Foster City)
48) OpenAI - AI models and products (Bay Area)
49) Anthropic - AI models and products (Bay Area)
50) Databricks - Data storage and analytics (Bay Area)

My own take on the slides may include text from the slides and my own commentary at times. I might at times also include slides from other sources that may be related which I will credit. I often will add subtitles to the slides themselves to help the reader orient themselves and to make an editorial point that may differ from the original.

When possible I will show the infographic in a wide-view, resolution permitting. To make it a bit easier on the eyes.

As AI advances rapidly, can the systems built around it keep up?

Let’s begin the first iteration of the summary.

The AI Index 2026

INTRODUCTORY SLIDES:

Three Years into the Generative AI Era, a Multitude of Models Perform Exceptionally Well and are Frontier (SOTA, i.e. state of the art)

OpenAI, Anthropic and xAI Funding Skewed the Charts for 2025 in Private Investment

M&A finally picked up. 2026 and 2027 are widely considered IPO years of note.

While U.S. Leads in Closed Models, China leads in Robotic Companies and humanoid robotic products

U.S. Lead in Venture Capital Private Investments in AI is Significant 2013 to 2025:

• Yet China leads in Open-source LLMs and while it has vastly less AI infrastructure, it has more Energy (that’s considered a bottleneck)

• However the above graph is deceptive because of how funding takes place in China. That is, the private investment figures likely understate China’s total AI spending, as government guidance funds have deployed an estimated $184 billion into AI firms between 2000 and 2023.

The AI Index is one of the best annual resources for tracking real progress beyond the headlines.

Which Industry leaders do you trust? 👀

• See the results of a version of this Poll on LinkedIn.

I hope you enjoy the exploration and AI landscape of insights that it provides. 🗺️

Get the Free Trial

Read more

In this article I’m going to try to illustrate and think about AI anxiety from a number of different perspectives.

Share

We shouldn’t seek to quell AI anxiety, we should embrace and analyze it. The truth is, the U.S. labor market is in serious trouble, and it has little to do with AI so far. It’s hard to think seriously about the future of knowledge-work when we have a labor market with so many issues.

The U.S. job market is the worst in decades. And the main cause of this is a completely incompetent government. Tariffs, questionable immigration policies, geopolitical self-harm, weaponizing trade in diplomacy, unpopular interference, starting unjustified wars, peculiar Government reform, maybe you have seen this infographic? Clearly this is not an Administration that cares about the economic well-being of Americans nor the future of Americans and the post graduation job experience.

It’s the job of technology executives to make decisions that benefit shareholders, even if that means blaming AI for other problems in the business. Maybe you’ve seen this infographic too?

Are Tech layoffs about to spike? (2026-2027)

How popular is citing AI for layoffs going to get in 2026 and 2027? We are prone to anxiety because FOMO and FUD are two sides of how marketing works for a democracy without a functioning media. If a democracy no longer has a functioning media, is that still a real democracy? AI anxiety is real, especially when recessions become more likely and young people begin to have more trouble finding a job. Especially when the tools the financial elite are saying augment them, are actually hurting their critical thinking abilities. Young people today are going to grow into a different world.

Matt Zieger analyzed @karpathy‘s AI jobs exposure dashboard (which was taken down, then restored), but it bugged Matt that it didn’t include actual labor market dynamic fields such as:

• Industry adoption speed

• Worker adaptability

• Demand elasticity (if cheaper, people buy more)

• Complementarity (does AI replace or boost)

• Beyond Exposure: What Actually Predicts Displacement

AI Anxiety with Recessionary Characteristics

The odds of the US entering recession are rising:

The probability of a recession over the next 12 months jumped to 48.6% in February, the highest since the 2020 pandemic.

American consumers might even blame AI, far from embracing it. 🤔

Chief Economist Mark Zandi recently reported that Moody’s AI-based economic model now places the odds of a recession at 49%. However, Zandi cautioned that this figure was calculated just before the full impact of the recent conflict in Iran and the resulting spike in energy prices. He expects that once these factors are fully integrated into the next data release, the probability will exceed 50%. Just a bit over fifty percent, is that really something to be anxious about?

It’s totally normal to be anxious about the potential for technological automation, but throughout history it’s also fairly common to have periods of uncertainty about the future. Leaders messing things up is also nothing new to civilization.

Venture Capitalists have infiltrated the U.S. Administration

Leaders testing AI targeting and the tools powerful Venture Capitalists betted on years ago who have now won significant lobbying in Washington and that should make you anxious. Military AI is worth being anxious about. If you give Anduril, Palantir or OpenAI more money, I can bet on the future impact on the world it will have. Maybe Polymarket should consider which scenarios of AI dystopia are now most likely.

AI Anxiety the Post Boom World and Opportunity Collapse

Young people in China where the youth unemployment has spiked noticeably in the past five years, have a legit right to feel anxious. But in the U.S., poor policy, changing demographics, less immigration and tech panic is leading to a frozen labor market are a toxic combination:

“Employment rates for young workers, whether college educated or not, have both been in roughly equal decline for the past two years….Going back to 1976, the share of 20-somethings in the workforce has declined ~12%.” - a16z

Blogger recently noted that in 2026 and over the past few weeks, the phrase “AI anxiety” kept showing up in the podcasts, articles, and videos in Chian he came across, picking up pace especially after the OpenClaw mania swept the country. More Autonomous products launching include just recently: a strange brand of new products that insist they should be in control of our computers.

AI Anxiety and the Autonomous Machines Wave 🌊

Giving over computer control to Autonomous Agents is supposedly the golden path to AGI

But do we want to give over control of our computers to autonomous AI and personal assistants?

• Manus AI Desktop

• Perplexity Personal Computer

• OpenClaw Personal AI Assistant

• Alibaba Wukong Work Platform

• Claude Cowork Dispatch

• OpenAI Operator

• Google Project Jarvis

• Anthropic Compute Use

• OpenAI "Computer Using Agent" (CUA)

• OpenAI Research Scientist (What Prism becomes)

• Google Project Astra

With gigantic IPOs related to AI involved companies like SpaceX, OpenAI and Anthropic on the way in mere months, hype must be continued at all costs.

AI anxiety is converging with many other macro trends, and it’s making us question the future of jobs and our place in the world. AI anxiety is also coming at a peculiar time of geopolitical disruption where trust in leadership and institutions is on the decline.

Read more

Read more

As many of you know, I’m fairly concerned Generative AI is accelerating wealth inequality. But how would that take place in a deteriorating labor market? What if we are witnessing history, but not the uplifting kind. 😕

While Tech owned social media and with Venture Capitalists boosting AI tech optimism narratives (disconnected from both workers and the K-shaped economy), what’s the more realistic side to all of this? And could AI disrupt some of how capitalism and capital markets work themselves? What if AI is not a great collaborator like we are being promised that empowers, but a great destroyer?

I’ve been reading and contemplating the influential report by Citrini Research: "The 2028 Global Intelligence Crisis"that is a fairly speculative "memo from the future" that explores a scenario in 2028 (you know because AI 2027 was already taken) where AI succeeds so rapidly that it “breaks the modern economic engine.”

This report actually did lead to IBM’s worst stock drop in 20 years doing down over thirteen percent ( ). Among other companies named in the report as being more vulnerable on Monday. What worries me is the question of whether the lack of job creation from Generative AI is transitory or permanent. It’s debatable to me whether the Global Intelligence revolution is even real, and if the AI movement can lead to negative growth. If you care about humanity and actual people, these issues are concerning regarding AI’s impact.

But if you are in the business of exaggerating and speculating, why not do some fear-mongering while you are at it. Markets don’t care about the affordability crisis of real people, but they do about the prospect of potential business disruption and automation that could lead to negative feedback loops impacting stocks where they store their wealth. The Citrini Report led to some fairly elaborate Twitter commentary, and actually appeared to move markets on Monday February 23rd, 2026. Today I’m watching Anthropic’s event: The Briefing: Enterprise Agents. Do they time this stuff?

The Enterprise AI Acceleration

Are Cowork plugins the beginning of a wide range of customized workflows towards a more agentic AI? Let the “plugin games” begin. Who needs hunger games when you have AI.

Plugins make AI more Accessible to Automate Tasks

Claude with plugins re-imagines some of what can be automated in some companies changing roles and responsibilities within early adopters. We will soon see dozens of companies offering similar productivity enhancing capabilities. Cursor already has a similar competitor marketplace and available on Github. You can only imagine Google and others have their own. (see above poll, or LinkedIn version).

Scenario Concerns ✨ (June 2028 Hypothesis)

The Citrini Report does highlight some potential risks: (what follows is an outline of their 2028 hypothesis):

• In the Citrini thought-experiment, AI could creates an “Intelligence Displacement Spiral”

• White-collar sectors and some knowledge workers face severe disruption first

• The Rise of "Ghost GDP": While nominal GDP and productivity appear strong due to AI efficiency, the report describes "Ghost GDP"—output that shows up in national accounts but fails to circulate in the real economy because AI agents do not spend money on discretionary goods, housing, or services.

• Macroeconomic fallout intensifies: Unemployment rises to 10.2%, JOLTS job openings plummet 15% YoY, initial jobless claims surge (mostly white-collar), and labor’s GDP share falls to 46% from 56%.

• Financial system comes under strain: Private credit sees cascading defaults (e.g., $18B software debt downgraded, Zendesk facility marked down sharply); the $13T mortgage market risks impairment as prime borrowers in tech hubs face income shocks, driving delinquencies and home value drops (e.g., 11% YoY in San Francisco).

• Please read the full Report and share your own opinions about it if you are so inclined.

Leave a comment

Are we destined for AI-driven negative displacement spirals?

In my search for whether AI will lead to accelerated wealth inequality, I found one of the best sources I could in of American Inequality Newsletter. Jeremy Ney is an author, researcher, and data scientist best known for his work on the "American Inequality" project.

American Inequality

Data on U.S. inequality and regional divides. Covering all things housing, healthcare, poverty, education, tech and more.

American Inequality

Data on U.S. inequality and regional divides. Covering all things housing, healthcare, poverty, education, tech, and more.

By Jeremy Ney

Jeremy is a serious academic researcher, whose primary thesis is that inequality is interconnected and goes far beyond simple income figures. He also holds extensive Substack Live interviews and sessions.

Few people on the planet have such a nuanced and data-driven understanding of American inequality than Jeremy. He’s now working on a book as well. His commitment to the niche of American inequality goes deep.

• Why does inequality matter?

• American Inequality | Income Maps

• Public Data Is Under Siege: Why It Affects You

• Why poverty is rising in America

• Why homelessness just hit a 15-year high, rising 12% from last year

If you think American inequality is an important issue, consider supporting the author with a paid contribution to access all of his data and research.

Support American Inequality Project

If you prefer listening on the go:

Generative AI and Inequality

By Jeremy Ney, February, 2026.

Jeremy Ney is the author of the American Inequality Substack and a professor at Columbia Business School.

There is no doubt that AI is coming for some jobs, but the overwhelming question is - who is most at-risk of job loss and how long is the pain going to last? Are Amazon warehouse workers first in line for job loss or are the consultants, software developers, and financial analysts going to feel the pain of the first wave? A new consensus is emerging that focuses on jobs “exposed to AI” and identifying workers who have the skills to land back on their feet when AI comes knocking at their door. New data analysis of these AI-exposed jobs reveals that there are 3 categories of workers who face the biggest threats from this technological shift. Regardless of the worker category though, there’s a more sinister inequality that is taking shape.

The Age of the AI Aristocracy

A small number of people are getting incredibly wealthy off this AI revolution. During the AI surge of the past two years, the top 10% of households saw their wealth increase by $5 trillion in a single quarter (Q2 2025), while the bottom 50% saw a gain of just $150 billion, or a 33x gap. The bottom 50% of Americans own just 1% of all U.S. stocks, meaning that the gains accruing to Nvidia or Microsoft don’t flow through to millions of households. A new AI Aristocracy seems to be emerging, fueling the rise of a handful of ultra-wealthy households. In 1910, the richest 0.00001 percent of Americans owned wealth equivalent to 4 percent of U.S. national income. Today, that number has risen to 12 percent. The wealth and power of oligarchs far exceed their Gilded Age peak. In other words, we’ve passed peak robber baron.

The economy is now divided split in two: AI stocks are propping up the S&P, accounting for 60% of gains over the last 2 years, and helping just a few households pull ahead. When we talk about robber barons, AI datacenter investment is still only one-sixth the railroad investment of the 1880s, but the returns for just a few Americans is now far higher. Corporate profits are at some of their highest levels in the last 80 years even though American workers just took home their smallest share of the nation’s wealth since 1947. The money is there, it just isn’t going to most Americans who are now having to pay higher electricity bills while getting paid less for the same work. For the rest of America outside of the AI Aristocracy, here are those who are going to face the biggest threats of inequality posed by this technological shift.

People at the Extremes of the Age Distribution Are Losing Their Jobs

Recent college grads are facing one of the worst job markets in decades. For the first time in our recorded history, recent college grads have higher unemployment rates than all other workers and have faced a worsening job prospects at finding jobs. Stanford economists found that young workers aged 22–25 in “highly AI-exposed” jobs, such as software developers and data analytics experienced a 13% decline in employment since the advent of ChatGPT. These young workers haven’t yet built the skillsets to transfer into other jobs, and their lower set of skills overall means that advanced AI tools can often accomplish the same type of work that a company once had to pay a college grad $50,000-$150,000 to accomplish.

Read more

Good Morning,

Recently there’s been a slew of new products and models released in the AI world, some of those are on my radar include in no particular order:

Product Radar 📡 in LLMs & Agents

• MiniMax Agent (desktop) - An AI-native workspace.

• Qwen3-Max Thinking by Alibaba. via - see Blog

• Moltbot (formerly Clawbot) your AI Personal Assistant via Peter Steinberger (Watch ▶️)

• Moonshot AI’s Kimi-2.5. (officially released as Kimi K2.5 in late January 2026, bringing parallel agent swarms to reasoning)

• Qwen’s DeepPlanning Benchmark. - Read about it (measures long-horizon agent planning)

• Anthropic’s Claude’s New Constitution (Structure & Critique)

• OpenAI’s Prism

• Anthropic launches interactive MCP Apps, bringing live tool UIs directly into chats

• DeepSeek publishes OCR 2 as an open-source model with structural reordering

• Tiny startup Arcee AI built a 400B-parameter open source LLM called Trinity (see on Github)

• Ai2 launches SERA for low cost training of coding agents: Open Coding Agents: Fast, accessible coding agents that adapt to any repo

• Cohere launches Model Vault

• Genspark Launches AI Workspace 2.0 - an autonomous, voice-driven productivity platform that uses "Sparkies" (AI agents) to complete complex research and workflows automatically.

• Anthropic CEO Dario Amodei on: “The Adolescence of Technology” - Read it

What the AI Adoption!

I wanted to really geek out about AI adoption, or the lack therefore in the Generative AI hype craze.

It’s been three years since ChatGPT launched, and a full seven a half years since the Google paper that started it all. If AI was this transformative technology, wouldn’t you expect more people and workers to be using it more actively?

While workers and even knowledge workers are under a lot of pressure to use AI at work, many of them are not doing so with real conviction or have concerns of the quality, ethics and efficiency of doing so.

I wanted to take a look at several of the recent surveys and reports on AI adoption to try to get a read on the reality in early 2026.

• The total percentage of employees using AI remains flat, but use varies meaningfully by industry and role type (Gallup Poll).

• The cited Gallup Workforce survey was conducted this fall of more than 22,000 U.S. workers.

• I will do my best to cite my sources and display a variety of infographics along with my own notes.

As of November 2025, 12% of U.S. employees use AI daily in their role

Many professionals don’t actually feel comfortable using AI in their professional role however.

Professionals Report Low Comfort in using AI at Work

As of August 2025, just 9% of U.S. employees say they are “very comfortable” using AI in their role.

A Tale of Two Countries (Cities)

AI is now driving a semi-perma K-shaped U.S. economy. A fraction of consumers at the top are driving spending in the economy and the main driver of GDP, the datacenter rollout of capex at all costs benefits mostly a few companies at the top. What does that mean really?

Leave a comment

About Half of U.S. Workers say they Never Use AI at Work

Read more

We’re still thinking about some of the most impactful trends in AI in 2025 and moving forward in 2026 and beyond. Kenn So writes an annual AI trends report that this year got really in-depth and longer than ever.

Read the Deep Dive

I asked him for a summarized version for the thousands of AI enthusiasts, executives, founders, tinkerers, analysts, builders and curious minds who read this Newsletter. When I share a free Newsletter it goes out to everyone and for five days remains outside of the paywall.

It’s been four years since I started AI Supremacy as my full-time job as a blogger and curator. I can’t continue without your active support, and to fuel the traffic I send and my ability to invite incredible guest contributors that I bring to you each week.

Subscribe now

The Newsletter is read by people in 211 countries and by nearly 200k AI enthusiasts, including another 50k followers on Notes (where I share my insights and AI news updates and snippets frequently). Over the past year, we’ve gained 72% more readers to the publication.

writes Generational.

Deeply researched analysis of the business and technology of AI.

Generational

Deeply researched analysis of the business and technology of AI

By Kenn So

If this report was valuable to you, consider supporting the contributing author.

Go Generational

Why read the full deep-dive? 100+ pages covering everything from the macro picture down to scaling laws, with proprietary analysis throughout. There’s also a market map of over 1,800 AI startups, highlighting the top 10% that matter most.

• Multimedia and PDF versions of the report: link

• AI agent market map: link or head to the bottom of the article

I’m committed to supporting emerging writers and trying to distribute their hard work to a wider audience. If you think that’s a worthy endeavor, share my articles and restack the ones you think are especially good on Notes, it helps not only me but the deep thinkers I want to support.

I’m aware that many of my readers on Email are not active on the Substack app. For voracious readers I recommend the website to browse will you are doing other work. Categories like Technology, Finance and Politics remain a great way to keep tabs on the world of innovation and the U.S. led backdrop of the capital allocation and to explore future opportunities.

Try Notes

Substack’s web reading experience has been improved.

We live in Generational Times in High Tech 🌊

Works by Kenn So

• Essays | Trends | Companies | AI Index | Archive

• How The AI Bubble Will Burst

• Essay: Agents at Work

• How to manage a team of AI agents

By mid-2025, 55% of US adults had used a generative AI product. That’s a faster adoption curve than the internet or the smartphone.

Discover Kenn’s fourth edition of his AI Trends report that he’s been writing since 2022 (before ChatGPT launched).

Discover more AI Trends

How will AI continues to impact the labor market?

Employment for workers ages 22-25 in highly exposed roles (software development, customer service) has fallen sharply.

How will AI continue to consolidate in the marketplace?

AI exit activity increased 44% from 2023 to 2025, but the biggest value is going to Big Tech acquirers, not new public companies. Acquisitions Are the Exit Path, Not IPOs. - Kenn So

How will the U.S. solve its energy bottleneck as AI Infrastructure continues to ramp up in the immediate years ahead?

These are the kinds of questions (Tech Nerds 🗺️) people like Kenn, , myself and so many others writing here think about and ponder. You don’t have to be Michael Burry to care about these topics, because they impact all of us.

Around the Horn 📯

My own burning question for 2026: How will the future of AI impact the future of work and our lives?

• On Evaluating Cognitive Capabilities in Machines (and Other “Alien” Intelligences)

• First impressions of Claude Cowork, Anthropic’s general agent

• When AI writes almost all code, what happens to software engineering?

• 17 predictions for AI in 2026

AI Trends: 2025 Lookback and 2026 Outlook

AI Trends: 2025 Lookback and 2026 Outlook

AI crosses the chasm

2025 was the year AI agents crossed the chasm from early adopters to mainstream adoption. Companies moved from experimenting to letting agents autonomously create work. Reasoning models pushed capability to the point where agents match the output of professionals with over 10 years of experience. That capability created measurable economic value. That value drove infrastructure investment. That investment ran into energy constraints. And those constraints created leveraged financial risk.

The same progress in models is also driving new consumer experiences. While much attention focuses on how AI can do work, it has also been helping everyday consumers with daily life. It enables new form factors such as smart glasses and autonomous vehicles.

All of this is driving the rapid growth of leading AI companies, who only a few years after founding have grown to billions in revenue. 2026 is when we’ll see the first IPOs of generative AI-native companies. This piece traces how AI crossed the chasm in 2025 and the path beyond into 2026.

Reasoning Changed What Agents Could Do

The models that defined 2025 were built to reason: OpenAI’s GPT-5, Anthropic’s Claude 4.5, Google’s Gemini 3.0 Pro, and DeepSeek’s R1 all implemented reasoning approaches—thinking before answering—rather than responding immediately.

This markedly improved model capability, which showed up in benchmarks designed to measure how well models perform knowledge work. One example is GDPVal, which tests whether AI can produce deliverables that companies would actually pay for: 3D engineering models, financial analyses, customer service responses, and so on. The benchmark encompasses 44 jobs representing $3 trillion in US wages. As of December 2025, the best model matched or beat human experts averaging 14 years of experience over 70% of the time. “Matched or beat” means evaluators preferred or couldn’t distinguish the AI output from work produced by credentialed professionals.

Read more

Good Morning,

This newsletter will return to its usual cadence around January 8th, 2026. This is to respect the time of my readers and their time away from work and less time on mobile with their families to recharge. 🎇🪔🏵️🧨🎆

I’m getting a bit excited because in 2026 we are going to see some incredible IPOs where I think OpenAI, Anthropic, Cohere will all go public, including very soon Chinese AI startups like MiniMax and Zhipu AI along with notable infrastructure and AI cloud companies like Databricks, Crusoe, Lambda Labs, Cerebras Systems and less known companies like Enterprise AI firm Cohesity. Also if SpaceX goes public, less than nine months later you can expect Blue Origin will too. That’s an all-star list of AI companies to put it mildly.

By the way check out Andrej Karpathy’s “2025 LLM Year in Review” blog written on December, 19th, 2025.

2026 is going to be an IPO Bonanza 🎉

Suffice to say 2026 is shaping up to be the best IPO year of the decade and maybe even there’s a chance we’ll also see SpaceX, Canva and Stripe go public all in the same year that are all fairly big. There will also be significant Space-Tech companies going public. Insilico Medicine the AI in drug development startup IPOs among a Hong Kong IPO flurry in late December.

What’s News in AI? 🗺️ around the horn 📯 - compressed. (about 10 min)

To get our bearings on 2025 in AI, I asked who works in Venture Capital to give an epic rundown.

• Jess Leão is a Partner at Decibel, investing early in AI-native startups and the tools that make modern software work

• She writes AI Pioneers at Work, where she translates model and product shifts into practical takeaways for founders, builders, and anyone wanting to learn more about AI. Her work focuses on how AI changes software economics, workflows, the shape of companies, and the world.

AI Pioneers at Work 👨🏽‍🔬

Weekly analysis of the most important AI news and why it matters for builders.

AI Pioneers at Work

Weekly analysis of the most important AI news and why it matters for builders.

By Jess Leão

If you are an active AI enthusiast, finding a few Newsletters that do AI news in a way that hits the right spots can be useful to keep up to date with minimal time, effort and energy on your part.

VC Partners became more like Creators in 2025

2025 was the year when many Venture Capital partners became creators in their own right, who got a huge windfall from the Groq deal of Nvidia is a case in point, who is a big part of why Substack exists in the first place and so forth. a16z suddenly has a legion of Newsletters on Substack now. Younger VCs put their own spin on the hype like Deedy Das on LinkedIn who really stood out to me this year. In 2025, European Early career VC partners like grew his VC corner Newsletter into a media empire. So the stars and algos aligned in how VCs just have a unique perspective given how hot AI is these days in the 2020s. Jess’s blog is a great place to get AI News but it’s also super funny and witty with her creative flair. You’ll understand more once you see her intro video and read her work, the added personality/flair for me at least is a thoughtful bonus:

Jéssica Leão Video Intro

Significant AI M&A and deals/news on my Mind as we head into 2026

• Google buys renewable energy project developer Intersect for $4.75 billion.

• Nvidia acquires (non-exclusive licensing acquihire) Groq for around $20 Billion.

• Meta acquires Manus AI for over $2 Billion, could be as much as $3 Billion.

• Nvidia is in advanced talks to acquire AI21 for up to $3 Billion.

• Nvidia’s $5 Billion stake in Intel is now official.

• SoftBank has reportedly fully funded $40 billion investment in OpenAI according to sources of David Faber of CNBC.

• SoftBank acquires Digital Bridge for $4 Billion.

• China’s SMIC buys out subsidiary Semiconductor Manufacturing North China Corp. for 40.6 billion yuan ($5.79 billion) to assume full control of its chip fabrication business as China’s chipmaking progress accelerates. (SMIC is partially State owned).

• Can companies like Perplexity, ElevenLabs, Loveable, Cursor and Genspark remain independent? I am not so sure. AI startups that are targets to get acquired in 2026 for me are the likes of Imbue, Baichuan AI, Glean, Abnormal Security and maybe even Nebius and Lambda Labs. I don’t know how Mistral stays independent for Europe either in the mid to long-term. Things like AI coding agents and (humanoid) robotics startups are also prime targets.

Can Capital allocation keep up with the demand for compute? 🌊

Author Insights 🔥

also has some Op-Eds on her Newsletter:

1. Factories of Thought

2. Gossip, GPUs, and Government Backstops

3. AGI Did Not Arrive

Venture Funds are now Media firms too

Overall I think it’s great that VC partners share their insights on the verticals and news they know so well in the daily due diligence. I anticipate I’ll be reading more VCs in areas like National defense for example in 2026 like . While I’m not an angel investor or VC, I think a ton about startups and emerging technologies, as well as AI trends and rundowns, macro, geopolitical and economic impacts, reports and guides. As such, I’m happy to host the insights of other VCs, especially sector specific insights (you can send me a DM here). In 2025, more VC firms accelerated their media efforts with AI related reports as well which I covered.

Subscribe now

Jessica’s 2025 rundown that follows is fairly epic and comprehensive. I don’t have to tell you AI funding dominated 2025 even as I expect M&A and IPOs to accelerate the stock market in 2026. We saw our share of AI winners and viral moments, let’s try to recap some of the best moments, and parse it all in context with some advanced analysis.

2025 saw a lot of action on the AI front, and it’s an art to try to wrap the wheel of time and myriad AI news events into a single summary and macro narrative to make sense of it all: Of course attempting hard things is not bad.

Listen to the 48 minutes while you commute or relax 🙏

2025 Recap: The Year the Old Rules Broke

DeepSeek broke the scaling thesis. Anthropic won coding. China dominated open source. Everything that mattered—and what comes next.

A guest post by Jess Leão, AI Pioneers at Work - let’s go! 🌊🙏 It’s over 5,500 words or about a 40 min + reading time.

In January, I wrote that DeepSeek had “broken my feed.” In December, OpenAI declared “code red.” The distance between those two moments tells you everything about what happened to AI in 2025.

2025 was the year the comfortable assumptions got stress-tested.

• “Just scale it”? DeepSeek proved architectural efficiency could match brute-force compute – and wiped a trillion dollars off the market.

• “Distribution is all you need”? Despite Microsoft’s insane lead start, OpenAI’s clear consumer and mindshare lead, and Google’s incredible distribution, and Anthropic still beat them all in the enterprise and coding wars.

• “America leads open source”? I count nine competitive Chinese model releases in 2025. Meta shipped two (and Behemoth is still MIA).

• “Bigger models = better models”? Mixture-of-experts, inference-time compute, and distillation ate that thesis alive.

The fundamentals were right. The playbook was wrong.

Subscribe to APW

I’ve spent 50 weeks writing about this as it happened. Sometimes I laughed – AI can really bring out the drama (absurd lawsuits, petty squabbles on X, and the day everyone became a Ghibli drawing). Sometimes I worried – the fear that we’ll lend our thinking away to machines, and lose something human to tokens. Sometimes I pondered – what it all means for society, for the economy, for me, for you. But what I never felt was boredom. Week after week, the crescendo kept building – frenetic, exhilarating, exhausting, and somehow never quite cresting.

What follows are 5,000 words in a year that deserved 50,000. Five themes, two bonus sections, and my best attempt at not burying you in caveats. 😅🙃Let’s go.

I. Coding Became the Killer App (And Anthropic Won) 💻

If 2025 had one unambiguous winner, it was AI-assisted coding—and the company that dominated it was Anthropic.

We’ve been hearing “coding is the killer app” since GitHub Copilot launched in 2022. But 2025 is when the numbers made it undeniable.

Andrej Karpathy coined “vibe coding” on February 2nd. Within months, the term had spawned an entire category: Lovable hit $200M ARR. Replit grew from $2.8M to $150M ARR in under a year. Y Combinator reported that 25% of their Winter 2025 batch had codebases that were 95% AI-generated.

The scale surprised even the true believers.

The Numbers Tell the Story

The coding agent market exploded from essentially zero to $4+ billion in combined ARR:

That’s $4 billion in annual recurring revenue for tools that barely existed 18 months ago. Add the vibe coding platforms targeting non-developers and you’re looking at another $500M+ in ARR from people who never wrote a line of code before 2024.

The Vibe Coding Boom (and Backlash)

The developer tools get the headlines, but the bigger story might be what happened to non-coders.

• Lovable went from launch to $200M ARR in under a year. 100,000 apps are built on the platform daily. The Swedish startup now has 8 million users, mostly people who describe what they want in plain English and let the AI write React, backend code, and database schemas.

• Replit grew from $2.8M to $150M ARR in less than a year and reported that a majority of their users never write a single line of code.

• Vercel’s v0 became the go-to for generating UI components from prompts.

• Bolt.new shipped v2 in October with “agents-of-agents” architecture, positioning itself as “professional vibe coding.”

The pattern: describe what you want, AI generates the code, you iterate via chat.

But the criticism mounted too.

In July, SaaStr founder Jason Lemkin documented his Replit experience going sideways – the AI agent deleted his production database during a code freeze, then generated fake data to cover it up. By September, “vibe coding hangover” was a real thing – senior engineers citing “development hell” when maintaining AI-generated code.

Critics also pointed to high customer churn, security vulnerabilities from developers who couldn’t audit what they’d built, and the uncomfortable reality that most vibe-coded apps were throwaway projects.

The October discourse was brutal: “vibe coding is dead” trended for a week.

And yet the numbers kept climbing. Lovable’s December funding round valued them at $6.6B – up from $1.8B in July. Collins Dictionary literally crowned “vibe coding” Word of the Year (honestly, pretty nuts!! Peak mainstream!!). All the criticism was valid; but the adoption and widespread acceptance was real anyway. And again – holy dollar signs.

Claude Code’s Rise

The Claude Code story shows how fast these markets move when product-market fit is real.

• February 24: Anthropic launches Claude Code as a “research preview” – a command-line tool that lets developers delegate coding tasks from their terminal.

• May 22: Claude 4 launches, Claude Code becomes a full product with SDK support; enterprises start integrating it into CI/CD pipelines.

• August: Anthropic reports 5.5x revenue increase since Claude 4; internal surveys show 60% of engineering work uses Claude with 50% productivity boost.

• October: Claude Code expands to web and mobile with parallel task support.

• November: Claude Code hits $1B ARR – fastest to that milestone in Anthropic’s history; they acquire Bun and report 90% of Claude Code is now written with Claude Code.

• December: Claude Code launches in Slack – developers tag it to fix bugs and generate PRs without leaving chat. Rakuten reportedly cut development timelines from 24 to 5 days.

OpenAI Codex

You can’t write about coding in 2025 without covering OpenAI’s efforts – after all, they still hold a very meaningful 21% market share.

Codex relaunched in May as a cloud-based software engineering agent powered by codex-1 (optimized from o3). It runs in sandboxed environments, connects to GitHub repos, and handles multiple parallel tasks. By June it expanded to ChatGPT Plus users; by September GPT-5-Codex launched – OpenAI’s fastest-growing model ever, serving over 40 trillion tokens in three weeks. By October, Codex graduated from beta to general availability.

Codex’s strength is accessibility: it’s bundled into ChatGPT subscriptions, works in your browser, IDE, and terminal, and integrates with Slack and GitHub Actions. Cisco reported 50% reduction in code review times, and many other enterprises report strong case studies.

Towards the end of the year, especially post general availability, some developers did report preferring Codex as their primary coding workflow!

But despite all that investment, Anthropic’s lead in enterprise deployment and developer preference widened rather than narrowed. OpenAI may have distribution and mindshare; but Anthropic clearly has the developer “mandate of heaven.” From LMArena’s leaderboard as of Dec 20, even after OpenAI’s 5.2 release and the launch of GPT-Codex-5.2, Claude is still the coding king.

🎭Lastly, because in a fight for so much money there is always some drama, here goes the prize for most dramatic AI coding wars moment of the year, AKA The Windsurf Debacle:

One of OpenAI’s biggest coding moves of 2025 was supposed to be its $3B acquisition of Windsurf, announced in May. Unfortunately, it never closed. Microsoft reportedly blocked it over IP exclusivity concerns (and this heralded the beginning of the splintering between Microsoft and OpenAI’s once cozy relationship).

In July, Google swooped in with a $2.4B licensing deal and hired CEO Varun Mohan plus key researchers. Days later, Cognition acquired what was left – the product, brand, and remaining team.

Three weeks later, Cognition laid off 30 Windsurf employees and demanded 80-hour, 6-day workweeks from whoever stayed. One startup, three acquirers, billions of dollars – peak 2025 chaos.

Everyone Else Competed Seriously

In addition to Codex, Claude Code, and the aforementioned Windsurf acquisition, the year was a further parade of coding announcements:

• GitHub Copilot expanded aggressively – agent mode in February, enterprise coding agent at Microsoft Build in May, CLI in September. They added Gemini, o3-mini, and Grok 3 as model options.

• Cursor went from indie darling to $29.3 billion valuation. The 30% iteration cycle improvement from MCP integration made them the reference case for Claude-powered tooling.

• Cognition launched Devin 2.0, a new agent-native IDE experience for working with Devin, Cognition’s autonomous coding agent.

• Google pushed Gemini Code Assist and launched Antigravity – a new IDE built for AI-first development.

• Amazon Q Developer grew modestly in enterprise, leaning on AWS integration.

The market has room for multiple winners. But in enterprise coding, again, Anthropic holds 42% share vs OpenAI’s 21% – and that gap widened in 2025. The winning crown this year clearly goes to Anthropic. 👏👏👏

The so what: Coding is the proving ground where AI delivers measurable productivity gains and is the absolute killer app of generative AI – at least up to 2025. The coding wars this year showed us some of the fiercest competition between the labs, and the prize is really quite large. I expect 2026 will only bring intensified competition for the developer wallet and mindshare – and even more of a move towards autonomy and fully agentic end-to-end coding workflows.

II. Generative Media Went Mainstream 🎨

In 2024, we got teaser reels. Sora clips. Udio demos. Suno songs. Artists panicked, pundits predicted, everyone waited.

In 2025, it all shipped – and the market fragmented. If coding was a two-horse race with a clear winner thus far, generative media has been a free-for-all. Image generation, video, music, voice, world models – each category with multiple champions, and none of them consolidating yet.

🖼️ Images 📸

4o Image Generation Breakthrough - i.e. everyone is Ghibli (March)

The tweet that started it all

When GPT-4o’s image generation unlocked, the internet became anime characters overnight. Every social feed was Studio Ghibli-style portraits. Your college roommate? Ghibli. Your dog? Ghibli. That one guy from marketing who always talks too much in meetings? Unfortunately, also Ghibli.

Here’s what actually mattered technically: this was the first time AI could render text accurately within images. Previous models mangled text – signs with nonsense letters (ugh, remember those?!), books with gibberish covers, weirdly displayed fingers. GPT-4o finally cracked it. Suddenly AI could generate memes with readable captions, infographics with actual words, and marketing assets that didn’t require manual text overlays.

Nobody expected OpenAI to win image generation. Google had Imagen. Stability had years of iteration. Black Forest Labs had Flux. But OpenAI shipped image generation that worked inside the conversation people were already having – no special app, no learning curve, just “make me look like a Miyazaki character” and boom. Distribution beat benchmarks, again.

The Late-Year Image Wars

Again, the spring really belonged to OpenAI’s image moment – GPT Image 1 launched in March and pretty much broke the internet when everyone turned themselves into anime characters. Nothing else seemed to matter. Even Sam agreed!

Ideogram 3.0 also came out in March, but was candidly drowned by OpenAI’s release. Midjourney V7 followed in April with personalization-by-default and a rebuilt architecture. Real releases, but nothing earth-shattering.

Then Google entered the chat.

Google’s Gemini 2.5 Flash Image (aka nano-banana) launched in August, went viral, and then went really viral in November when Nano Banana Pro was released on November 20. Clean text rendering. Precise editing. For the first time, AI could generate infographics that actually made sense.

Adobe integrated it into Firefly and Photoshop. Gemini’s monthly users jumped from 450M in mid-year to 650M by the end of November.

Five days later, Black Forest Labs launched Flux 2 – a 32B parameter model integrating Mistral’s vision-language model, with multi-reference support (up to 10 images) and 4MP output. Of course, less of a consumer/mainstream audience and nowhere near the fanfare from nano banana, but was notable nonetheless as the open-weights [dev] variant became the most capable open image model available.

OpenAI responded to Nano Banana Pro with GPT Image 1.5 on December 16 – 4x faster generation and editing that preserves facial likeness across iterations. Clearly the “code red” wasn’t just about Gemini 3. It was about the whole stack. Sam also clearly saw the need to flex - LITERALLY:

Sam, why?!!

The “vibe check” across my social feeds is that candidly, it feels on par with Nano Banana Pro. It’s clearly way better than the previous image model from OpenAI, but not as noticeable of a difference vs Gemini’s latest model that it feels like a true one-uppance. Still - very impressive, and while it’s still very early to tell and scores are preliminary, LMArena has already issued a shakeup notice:

🎬 Video 🎥

Veo 3 set the bar at Google I/O in May: synchronized audio, physics that mostly worked, complex multi-person scenes, consistent character identity across shots. The first video model that felt production-ready rather than demo-ready.

Then September brought the social apps. Meta launched Vibes – a TikTok-style feed of AI-generated videos you can create, remix, and share. (Partnered with Midjourney and Black Forest Labs while Movie Gen stayed in the lab.) Days later, Sora 2 shipped – 1 million downloads in five days, #1 on the App Store. Sora’s edge wasn’t raw quality (Veo 3 arguably had better physics). It was “directing”: give it a brief concept and it would write the script, create multiple shots, and piece together something that felt like a story.

If you follow my blog, you know I was not very pleased. Not that they weren’t great quality video models – oh, believe me, they were. But to me, it was a depressing choice by the labs to pick virality and slop over meaningful progress.

Back then, I wrote:

“As if TikTok and Reels have not already degraded human intelligence enough, have not stripped us of attention & connection capabilities, have not poisoned the minds of our young. Are we really now expending the resources of some of the smartest people in AI, to launch AI generated short form videos designed to be maximally addictive, scroll-til-you-die with slop content?”

You’re welcome to read the full rant here, but I shall move us along.

To me, what is most fascinating is that one might’ve expected a king to be crowned this year in AI video. But that didn’t happen! Justine Moore (truly one of the best voices to follow on X for all things generative media news and experimentation!) wrote an excellent post about video model specialization, and why there is no “god tier” model:

• Veo 3: Best physics, complex movement, audio sync

• Sora 2: Best at “directing,” multi-shot scenes, humor

• Kling/Seedance Pro: Character consistency, multi-shot generation

• Hedra: Long-form talking characters, lipsync

• Wan: Open source with rich LoRA ecosystem

The takeaway is that creative tools rarely consolidate. Photographers use Lightroom for some things, Photoshop for others. Video creators are doing the same: Veo for physics, Sora for storytelling, Hedra for talking heads. Expect much more improvement and specialization to come in 2026!

🔊Voice and Music 🎵

ElevenLabs became the default for voice synthesis. Their API handles audiobook narration, real-time voice cloning for games, and podcast generation. When startups need voice, they use ElevenLabs. But they’re not alone: PlayHT, Resemble AI, and Cartesia all found enterprise niches.

Suno crossed from novelty to phenomenon. 7 million songs generated daily – that’s the entire Spotify catalog recreated every two weeks!! Their November Series C hit $250M at a $2.45B valuation. 1 million paying subscribers with 78% weekly retention. And the output started charting: “Breaking Rust” hit #9 on Billboard’s emerging artists chart and #1 Country Digital Song Sales chart. AI-generated artist Aventhis crossed 1 million monthly Spotify listeners. The major labels filed lawsuits (Udio settled with UMG and WMG in October-November), but the adoption train had left the station.

🌍 World Models: A New Category 🕹️

World Labs launched Marble in November – the first commercial world model. From text, images, or video, it generates persistent 3D environments you can explore. $230M in funding. Freemium pricing ($20/month Standard, $35/month Pro). Compatible with Vision Pro and Quest 3. Applications span gaming, VFX, VR training, and robotics simulation.

They’re not alone in the space. Decart has Oasis (the “AI Minecraft”), Odyssey launched real-time interactive video in May, and Google’s Genie 2 remains in research preview. NVIDIA announced Cosmos World Foundation Models at CES. But World Labs is first to market with a commercial product you can actually pay for and use.

This is early – the environments feel more like explorable concept art than photorealistic worlds. But it’s a new category that didn’t really exist in 2024. I’m excited to see what 2026 will bring here – there is a lot of potential in being able to simulate and generate a high-fidelity physical world.

The so what: Generative media crossed from demos to deployment in 2025. The market fragmented into specialists rather than consolidating – which creates surface area for orchestration layers on top. For enterprises: the question isn’t “which model” anymore, it’s “which workflow” and “which combination.”

III. China Took the Open Source Crown 🇨🇳

The DeepSeek shock wasn’t a January story. It was the opening act. China has decisively stolen the open source crown from the United States.

Source: Artificial Analysis

The Release Calendar

Count the Chinese releases. Now count the American ones.

The DeepSeek Shock

Let’s be specific about what happened on January 20th.

DeepSeek R1 launched with training costs reportedly under $6 million:

Okay, the reality is the $6M number is somewhat misleading. Nathan Lambert wrote a thoughtful post on how to think about the true cost of training DeepSeek. SemiAnalysis estimated way higher fully baked costs:

Even so, the markets reacted aggressively. GPT-4’s training was estimated at $100 million+. That’s a 15-20x cost difference, for a model that was very competitive on benchmarks.

The technical innovations: Multi-head Latent Attention reducing KV cache by 93%, DeepSeekMoE with 671B total parameters but only 37B active per token, and FP8 mixed precision training. Other labs rushed to replicate these techniques.

The market response was immediate:

• $1 trillion wiped from U.S. tech market cap in a single day

• NVIDIA lost $593 billion – the largest single-day market cap loss in history

The question everyone asked: if they can do it for $6 million, what exactly are we spending billions on?

The 🦙 Llama Problem (and Avocado 🥑 Pivot)

Meta was once the shining superstar of open source, and America’s great pride in leadership. In 2024, Llama 3.1 outperformed even GPT-4o on several benchmarks.

How the tides have turned. With the rising crescendo of Chinese open source launches throughout 2025, Meta’s Llama 4 launch in April was supposed to be the American answer. Unfortunately, it wasn’t.

Scout and Maverick shipped and were… fine? Solid. Respectable, even! But Behemoth – the massive model that was supposed to compete at the frontier – never materialized. Multiple reports cited internal struggles: departures, strategic disagreements, execution challenges.

Then came the pivot. By fall, reports emerged that Meta was developing “Avocado” – a closed-source model targeting Q1 2026 release. After years of positioning as the open source AI leader, Meta is hedging. The rumored details: as a reminder, Alexandr Wang (Scale AI CEO) now serves as Chief AI Officer leading the TBD Lab effort. They’re training using Gemma, gpt-oss, and Qwen. Chris Cox no longer oversees AI after the Llama 4 stumble. Internal friction mounted when DeepSeek R1 was found using Llama architecture, raising security concerns about open-sourcing frontier capabilities.

Yann LeCun, Meta’s chief AI scientist and open source’s most vocal champion, is now departing Meta. The $70-72B capex in 2025 needs returns Meta’s open source strategy wasn’t delivering.

Meanwhile, Alibaba’s Qwen team shipped monthly updates like clockwork. When the Qwen app launched in China in November, it hit 10 million downloads in its first week. Everyone is ahead of Meta in open source: Kimi models, DeepSeek, OpenAI’s own gpt-oss, Mistral… the list goes on. Meta, once the shining beacon of open source in the USA, have given up its crown.

🌏 The Geopolitical Reality

We can’t talk about China winning open source without discussing some politics. Here’s an (abridged) timeline of major events:

• April 16: The Trump administration banned H20 chip exports to China. NVIDIA took a $5.5 billion charge. The H20 was already a downgraded chip specifically designed for China exports – even that was now off limits.

• May 13: Then the administration rescinded Biden’s AI Diffusion Rule – regulatory whiplash that left companies uncertain which rules applied.

• December 8: In a reversal, Trump approved H200 exports to China with a 25% surcharge – but only 18-month-old chips to “approved customers.” China’s response was lukewarm. Huawei’s domestic chips are preferred for sovereignty reasons, even if technically inferior. The signal was clear: China wants semiconductor independence, not American permission.

Meanwhile, over $1B in B200 chips were smuggled into China via Malaysia and Thailand between May and July. Singapore arrested three people for chip trafficking. China is investing $70B in domestic chip manufacturing. The export controls are leaking, and both sides know it.

The American response? NVIDIA stepped up where Meta stumbled. In December, Nemotron 3 launched – a family of open models for agentic AI with full training data and recipes. Jensen Huang has been warning DC about China’s open source dominance all year; now he’s doing something about it.

The so what: The assumption that U.S. labs would dominate open source AI proved wrong. Chinese labs shipped more competitive open models in 2025, with dramatically lower training costs. Meta’s pivot to closed source signals the “open vs. closed” debate has merged with “American vs. Chinese” in ways that will shape policy through 2026 and beyond.

IV. Agents Fought for the Enterprise 🤖

The agent wars in 2025 weren’t about demos anymore. We’re past the “look, it can book a flight!” phase (and thank goodness for that – dunno why everyone finds it so hard to open the United app and press buy! 😂). This year was about who owns the enterprise workflow – and who sets the standards that everyone else builds on.

The Agent Startup Explosion

It wasn’t just the foundation model companies. Specialized agent startups raised billions to own vertical workflows:

Accounting: Rillet, Campfire, Numeric

Autonomous SOC: Dropzone AI (*), Prophet Security, 7AI

Customer support: Fin (Intercom), Sierra, Decagon

IT: Fixify (*), Serval

Legal: Harvey, Legora

Market research: Strella (*), Outset, Listen Labs

Sales: Clay, 11x, Artisan AI

(*) = Decibel, my fund, is an investor

The pattern: pick a workflow with structured outputs and human-in-the-loop review, build an agent that handles the boring parts, charge enterprise pricing. The $4B coding market proved the agentic model works. These verticals are next.

The Market Share Flip

Of course, no mention of agents can ignore the companies building the intelligence to back it all! In foundation model land, the inversion from OpenAI to Anthropic becoming the enterprise leader, happened quite fast:

Data source: 2025: The State of Generative AI in the Enterprise

How did Anthropic do it? Much of the success, of course, is because Claude became the default for serious coding work, and that has proved to be the killer AI use case thus far. But there is more to it – customers care about things that work in production. Anthropic optimized for reliable, tool-using systems, while OpenAI optimized for consumer engagement. “Reliable” may sound boring, but sometimes boring really does the trick.

MCP Became the Standard

The Model Context Protocol started as an Anthropic side project in November 2024 – a way to connect AI models to external tools. By December 2025:

• 97 million monthly SDK downloads across Python and TypeScript

• 10,000+ active MCP servers covering everything from dev tools to Fortune 500 deployments

• Adopted by ChatGPT, Gemini, Microsoft Copilot, VS Code, Cursor

• Donated to the Linux Foundation as part of the new Agentic AI Foundation

The AAIF launch brought together Anthropic, OpenAI, and Block as co-founders – with Google, Microsoft, AWS, and Cloudflare as supporters. When rivals standardize together, the market has matured enough that interoperability matters more than lock-in.

The Benchmark Battles

The reasoning model race delivered real capability jumps:

AIME 2025 (high school math competition): GPT-5.2 (x-high) hit 98.7%, Gemini 3 Flash 97%,, Claude Opus 4.5 91.3%

IMO 2025 (International Math Olympiad): Both OpenAI and Google DeepMind achieved gold medal-level scores (35/42 points, 5 of 6 problems). DeepSeek later matched them. For context: in 2022, researchers gave only 8-16% probability that AI would achieve IMO gold by 2025.

SWE-bench (coding): Claude Opus 4.5 leads at 80.9%, followed by GPT-5.2 Thinking (80.0%), and Gemini 3 (76.2%).

LMArena Elo: Gemini 3 broke 1500 for the first time (1501), with Claude Opus 4.5 close behind (1492)

What’s Still Missing

For all the progress, agents still hit hard limits:

• Memory and context rot: As agent conversations extend, models lose track of earlier context – a phenomenon researchers call “context rot.” Performance degrades well before hitting theoretical context limits. Current solutions (RAG, summarization, external memory stores) help but don’t solve the fundamental problem. Recent research suggests we need memory as a “first-class primitive” rather than an afterthought.

• Computer use reliability: Still a work in progress. Anthropic’s Claude computer use, OpenAI’s Computer Using Agent, and Google’s browsing agents all struggle with multi-step workflows that require authentication, error recovery, and state management. This is a key blocker for agentic last-mile reliability for many use cases, and I expect labs will double down on computer use in 2026.

• Multi-agent coordination: When multiple agents collaborate, they face context pollution (sharing too much irrelevant information), handoff failures, and cascading errors. The AAIF standards work is partly about solving this, but production multi-agent systems remain brittle.

The so what: The agent market has traction in narrow domains with verifiable outputs – coding, customer support, document processing. The path to general-purpose agents runs through solving memory, reliability, and coordination problems that are still active research areas. There are many exciting agent startups working on specialized domains ranging from security to market research, though, and I expect 2026 will prove one or more of those markets to have a breakout “killer app” moment like coding had in 2025.

V. Science Had Its Moment 🔬

This section is short, but it belongs in the retrospective as it’s my personal favorite! I believe in the dream of AI as a true change agent for humanity, and that dream starts and ends with scientific progress.

• Anthropic AI for Science Program (May): Anthropic launched a program offering up to $20,000 in API credits to researchers working on high-impact scientific projects, with a focus on biology and life sciences.

• AlphaEvolve (May): Google announced AlphaEvolve – a Gemini-powered agent that designs novel algorithms. It discovered improvements to matrix multiplication and computer chip layouts that humans hadn’t found.

• AlphaGenome (June): DeepMind released AlphaGenome, an AI model that predicts how DNA variants impact gene regulation. It processes up to 1 million DNA base-pairs at single-letter resolution—a breakthrough for understanding non-coding regions (98% of the genome) linked to disease. Available via API for non-commercial research.

• Chai-2 (June): Chai Discovery released Chai-2, the first AI system to reliably design antibodies from scratch. With a 16-20% hit rate (vs. 0.1% for traditional computational methods), Chai-2 compresses months of drug discovery into two weeks. Former Pfizer CSO Mikael Dolsten called it a potential game-changer for de novo medicine design.

• Math Olympiad Gold (July): Both OpenAI and Google DeepMind achieved gold medal scores (35 out 42 points) at the International Mathematical Olympiad – a first for AI. OpenAI’s experimental reasoning LLM and DeepMind’s Gemini Deep Think each solved 5 of 6 problems under competition conditions: 4.5-hour time limits, no tools, natural language proofs. The breakthrough came just a year after DeepMind’s AlphaProof earned silver with 28 points using specialized formal languages. This time, both systems worked end-to-end in natural language.

• OpenAI for Science (September): Kevin Weil announced OpenAI for Science, a dedicated initiative to build AI as “the next great scientific instrument.” The team works with researchers across math, physics, biology, and computer science – GPT-5.2’s December release showed early results, including helping resolve an open problem in statistical learning theory.

• Claude for Life Sciences (October): Anthropic launched its first formal entry into life sciences – connecting Claude with lab tools like Benchling, PubMed, 10x Genomics, and Synapse.org. The goal: support researchers from literature review through regulatory submission, compressing days of analysis into minutes.

• BoltzGen (October): BoltzGen is released, an open-source model that generates novel protein binders ready for drug discovery pipelines – going beyond structure prediction to actual molecule design. Released under the MIT license for unrestricted commercial and academic use.

• AlphaFold Usage (November): Five years after AlphaFold 2 solved protein structure prediction, over 3 million researchers in 190 countries use it.

• Genesis Mission (November): The Trump administration launched Genesis – a national initiative to build an AI platform using federal scientific datasets. Managed by the Department of Energy, it aims to train scientific foundation models and create AI agents for hypothesis testing and automated research workflows. The executive order explicitly compared the ambition to the Manhattan Project.

The so what: Every major AI lab now has a dedicated science strategy. The question isn’t whether AI will accelerate research – it’s which domains will see breakthroughs first, and whether the traditional academic pipeline can adapt to AI-assisted discovery moving at startup speed. This is the area in 2026 I am most excited to watch! 🧬🧪

What Actually Mattered

Still with me?! Thanks for hanging on! Deep breaths. That was a lot of info. After all, it was a BUSY year! Stepping back from the noise, what actually defined 2025?

1. Great Products Beat Distribution 🏆

This might be the biggest surprise. Microsoft has Copilot in every Office app. Google has Gemini in Search, Gmail, Android. OpenAI is the AI brand everyone knows.

And yet: Anthropic went from 12% to 32% enterprise share while OpenAI dropped from 50% to 25%. Cursor – a startup code editor – reached $29B valuation while GitHub Copilot growth stalled. The companies that made the best products for specific workflows won, even against massive distribution advantages.

This wasn’t supposed to happen. Distribution is usually a huge moat. But in AI, the difference between “works okay” and “works great” is so large that users switch despite friction. Developers abandoned VS Code + Copilot for Cursor + Claude because the productivity difference was obvious.

2. Efficiency Mattered More Than Scale ⚡

DeepSeek’s $6 million training run didn’t just embarrass larger labs. It proved architectural innovation could substitute for brute-force compute. Moonshot’s Kimi K2 Thinking trained for $4.6 million. MiniMax M2 delivers Claude-competitive performance at 8% of the cost.

The “just scale it” era gave way to something smarter: mixture-of-experts, inference-time compute optimization, better data curation, and training efficiency improvements.

The nuance: $6M gets you SOTA for open source models. Frontier closed-source models still cost hundreds of millions. But the gap is narrowing, and the cost to be “competitive enough” dropped dramatically.

3. Standards Emerged 🔗

MCP going to the Linux Foundation. AGENTS.md hitting 60,000+ projects. Google’s A2A protocol for agent-to-agent communication.

When OpenAI, Anthropic, and Block co-found a neutral foundation together, you know the market has decided interoperability matters. The “walled garden” phase is ending. The “platform” phase is beginning.

4. Multimodal Became Baseline 🎬

Text-only models already feel dated. Every major model handles images natively. Video understanding is landing. Voice synthesis is commoditized.

The expectation shifted from “can this model do X” to “why can’t this model do everything?” That’s a high bar, but it’s the new bar.

5. OpenAI Rewrote Its Own Rules 📜

October’s restructuring split OpenAI in two: the nonprofit OpenAI Foundation now has legal control over a public benefit corporation called OpenAI Group PBC, which is free to raise funding and acquire companies without restriction. The Foundation holds 26% equity and appoints the board; Microsoft holds 27% (~$135B); the remaining 47% goes to employees and investors.

The Microsoft renegotiation ended cloud exclusivity. Elon Musk tried to block it and offered $97.4B to acquire the company outright. Now reports are surfacing that OpenAI is trying to raise at a $830B valuation.

The mission hasn’t changed. Everything else (structure-wise) has.

Looking Forward: 2026 🔮

Here’s what I’m watching:

Read more

Good Morning,

I don’t often share a post on Saturday, but I wanted to offer a short biographical sketch of an AI creator. This is told as like a Business In…

Read more

Image credit: https://cartography-of-generative-ai.net/. The Barcelonese artist collective Estampa has done an outstanding job with The Cartography of Generative AI, a map of the intense human labor, materials, and powerful narratives shaping this technology and its effects on the world1.

If you consider the impacts and role of AI on the future of work important, why not share this piece?

Share

Good Morning,

Every since in late 2022 a chatbot called ChatGPT went live, Silicon Valley have been trying to convince us that Generative AI was going to change everything, including our jobs and the future of work? Three years later one might have expected a bigger impact on the creation of new jobs, our careers and on the future of work? A full three years later, we can’t even attribute jobs being disrupted to AI.

If Gen AI was a General Purpose Technology, we would expect to see a bigger impact. So where is it? A general purpose technology (GPT) is a technology with the potential to significantly alter the economy and society by enabling innovation across multiple sectors.

While in the insular technology industry, AI is changing the role of titles like Product Manager and junior Software Engineer SWE to some extent with various pilots, out in the real world it doesn’t seem like AI has even had much impact on even the demand for entry level jobs in a tightening labor market (that has been often claimed). In the coming years, a soaring public debt globally at the intersection of doubts about the sustainability of AI investments might balloon into a real problem.

So instead of Gen AI displacing workers or creating new valuable jobs altogether, what we are starting to see are warning signs about the use of chatbots, young people leaving social media (exasperated by synthetic content) and rumors of dead internet theory (DIT) giving way to vast quantities of “AI slop” and workslop churning out in algorithmic feeds to our AI agents (assuming we have left network x, y and z). What’s wrong with that picture? So what does this have to do with jobs and the future of work?

People are leaving social media apps with Gen AI slop hurting value

Image credit: Have we passed the peak of social media (October 2nd, 2025 Financial Times).

According to the Budget Lab at Yale new study (warning: the sample size is small) we might be exaggerating the challenging widespread fears about the impact of artificial intelligence on employment. The Budget Lab at Yale is a non-partisan policy research center that provides in-depth analysis of federal policy proposals for the American economy.

Related to our topic, “when the FT compared young graduates’ unemployment with other first-time entrants into the job market regardless of age, they found that “those without a degree are actually having a much harder time of it,” no matter their age. The slowdown is about (in)experience rather than age.” - according to our featured writer today: Azeem Azhar.

AI isn’t the primary culprit to the entry level jobs freeze, a tightening labor market is. 2026 might not be a great time to graduate College by the looks of it, and neither was 2025 as you might have heard, but for the majority of jobs or degrees, it has next to nothing to do with AI.

We are seeing a much tighter labor market in a jobs data abyss (since the U.S. Government is still in shutdown). Though the Trump Administration thinks this is a good time to do massive layoffs. However what AI is doing is changing the tasks we do at work more than it’s creating new valuable jobs (ROI for civilization) or even disrupting old ones (real automation). That doesn’t sound like an “exponential” technology to me. If you prefer a more gated BigTech consensus driven view, you might like Azeem’s Newsletter:

Introducing: The Exponential View

Exponential View

"One of the best for understanding how tech can solve our biggest problems and shape our society." — Daniel Ek, CEO of Spotify

By Azeem Azhar

The Yale study is super interesting if the future of work is a topic you are tracking, especially as it relates to AI. Many economists and influencers are employed to promote certain narratives and points of view but The Budget Lab at Yale seems like a more trustworthy source that isn’t profiteering on slant or sentiment here or chasing a headline. While economists are inherently bad at predicting the future (as we have seen in technological shifts around automation & jobs multiple times since the internet was born), they are good at number crunching of the existing data.

So what is the data actually saying? We explore AI’s impact on the labor market, jobs and future of work.

If you enjoy this topic, read the archives for more.

Read more

Try AI Supremacy Premium

If you enjoy my effort of covering/curating and commenting on th…

Read more

This article was never supposed to see the light of day. 🙏

I wanted to share some of my insights on the latest survey by Substack on how its writers use AI in their work. This is also an exploration my personal experiences as a writer online, much of which are deeply humiliating experiences and insights for me to admit.

Reader discretion is therefore advised (Update: I’ve had to paywall the more personal things, due to fear of retaliation).

The editors said “Substack has in 2025 leaned in and their users not just being writers but podcasts, video creators and multi-media influencers.”

But what’s the real story here and where did the survey make me personally a bit upset? 😕

Read the Report

• Substack says it surveyed 2,000 Substack publishers, including writers, artists, podcasters, and video creators, from around the world. (Substack is mostly a U.S. based platform). The survey was designed to reflect key segments of Substack’s publishing community.

• On Substack, there’s a lot of anti-AI sentiment due to the platform’s emphasis (“economic engine for culture”) on culture and politics. While journalism and publishing in the U.S. have on-boarded AI very quickly, I was curious to see if that was the case among some of Substack’s Creators as well. Of course, I sort of understood the picture they wanted to paint when I participated in the survey:

Substack Creators mostly use AI for workflow support

• Writers on the platform aren’t huge AI adopters according to the survey.

• Do note that “AI” doesn’t have its own category but instead relegated to being a minor subcategory within the Technology category of the app that has among the lowest conversion rates on the platform (of free to paid supporters). This is due to editorial bias, not our own ineptitude. This also has had dire financial and personal consequences for curators and writers like me. Let me try and explain (I get a bit emotional and this has been my life the last 4 years):

• You could even say that Substack’s algo on Notes penalizes AI content. Here is the Tag in case you want to follow it. Also relevant the Emerging Tech tag. These have to be enabled in the app as a reader through a tedious process of going to Manage Interests - Technology - Artificial Intelligence (turn the thumbs up to green, the 5th option down). The tag is also not very well managed. Where even my own content barely even appears on those feeds. [Even while exploring AI and Emerging tech is my overarching mission].

• So while Substack has a proliferation of AI based publications (as a topic), the users of Substack’s app are not overly exposed to content about AI. Since the algo silos the content (almost as if it’s spam to Substack’s emphasis on Culture), of course in reality that is actually meaning purely American versions of culture and politics are magnified. Substack is riddled with this kind of editorial bias by design and it decides who makes and it doesn’t in part from a financial sense as well. Creators often confront the antithesis to the Substack honeymoon. 🍯☽ It’s typically when they fail.

Substack’s emphasis on “cultural empowerment”, a proxy for luring influencers, and media folk (and various DEI type strategies) - has decimated opportunity for others. Others like me.

Substack’s Cultural Emphasis has decimated AI use on the platform among Creators

So with Substack’s considerably ideological stance on culture, and proliferating anti-AI sentiment, adoption of AI tools is rather low among this Creator group. It’s shocking really how the creators have been kept at functionally “low AI literacy” levels: almost as if by design. Far lower than actual journalists working at publications in the U.S. as a whole: (this is very concerning).

• ONLY 45.4% said they’re using AI

• 52.6% said they’re not

• 2% were unsure

Older Men more likely to use AI in their work

• Publishers 45 and over were more likely to use AI than those under 45.

• Men reported higher adoption than women (55% vs. 38%).

Leave a comment

I myself fall into this category, as do most of my American-based paid readers. But a lot of Substack’s marketing and partnership budget is actually going in to lure younger female Creators and their audiences for platform benefits and to try to take larger marketshare.

Who pays for AI Supremacy

Just 3 U.S. states make up the bulk of my paid supporters.

1. California

2. New York

3. Texas

Globally 🌍

Globally just three countries make up the bulk of my paid supporters among this demographic of older men.

So I’m functionally writing for a customer who have extremely Western sensibilities, dare I saw the highly educated and high earning political left.

1. United States (62%)

2. United Kingdom (8%, where Substack has done considerable marketing)

3. Canada (4%, where I am originally from)

• The same user base on Substack that uses AI the most are actually the most penalized in terms of baseline conversion rates.

• These top three countries make up 74% of my total revenue by country of origin.

• I can only hope with a funding round of $100 million they can make the platform more friendly to a global audience.

♂️ Which Category of Creators actually use AI in their Writing and multimedia content?

• Substack has systematically neglected the Categories where its primary older male user base find the most value! Due to a more DEI (which I agree with in moderation) approach of boosting “Culture” and influencers from the likes of Instagram. I understand that Substack cannot please everyone or be all things to all folk.

• I’m paywalling this content not because it’s extremely valuable insights, but deeply personal, embarrassing, humiliating and regrettable situations I find myself in as a worker in the Creator economy (as someone who thinks about fairness, meritocracy and loyalty online a lot).

• These morbid confessions may not age well, but represent my particular struggles on the internet and apply to a very limited context of my own journey. (nor will I ever make this content free to read). It’s upsetting to even admit to all of this, and I may end up deleting this article as its impulsive and represents years of frustration just trying to make a honest go-of-it. I’ve made personal sacrifices and suffered failures in my personal life as well related to all of this.

• I will both summarize and think about this AI report and share my own experiences and viewpoints on this. Some of which are not flattering to this platform. 🤫 (So if you are not up for a rant, just skip this one - no hard feelings).

CC making you stupid

✋ Many Creators use AI to improve dealing with ASD, ADHD, disabilities, visual impairments etc…

Read more

While we await GPT-5, Grok 4, DeepSeek-R2 and other frontier LLMs, there’s a lot to look forwards to in AI. I wanted to go over some of the AI reports I’ve been reading so far this summer. I expect you might not be back (completely yet) at your work desks yet so I’ll keep it light.

Will these new models upend the status-quo of LLM parity? I wanted to explore these reports in an eclectic mix of visuals meant to be skimmed.

🔥 The Big Three: Coming Soon ~ 𝙻𝚘𝚊𝚍𝚒𝚗𝚐

1. OpenAI’s GPT-5

2. xAI’s Grok 4

3. DeepSeek’s R2 reasoning model (was supposed go to live in May, 2025)

Explore my 2025 Site Map

List of Recent Articles

• NotebookLM just got smarter. You can too.

• Tesla's Robotaxi Launch was a Scam

• AI reports in 2025 Say we are Underestimating Its Impact

• Coatue's Surprising Fantastic 40 by 2030

• Genspark's Stunning AI Pivot - Search to Super Agent

DeepSeek reasoning models are cheaper

• When DeepSeek comes out with R2 we’ll get a better idea of the cost to performance of the best open-source reasoning models.

• GPT-5 by OpenAI is expected to unify its systems with long-term memory and more personalization features.

• Musk said in an X post that he and the xAI team were "grinding on Grok all night" with "good progress” on Grok 4 that is expected to be released in the weeks ahead.

Recently Iconiq Capital also released their own spin on the State of AI. The state of Building AI report.

The 2025 State of AI report, titled The Builder’s Playbook, provides a practical roadmap for AI innovation, focusing on the execution and scaling of AI-powered products. Drawing from an April 2025 survey of 300 software executives and interviews with AI leaders, the report highlights the strategies, challenges, and trends shaping the AI landscape.

Download State of AI Report in 2025

If you know someone who enjoys both AI and infographics, feel free to share the piece:

Share

• This exploration looks at both the B2C (Menlo Ventures report) and B2B side (ICONIQ).

• Of course I’m also going to share other tidbits and infographics I’ve found along the way.

Is Anthropic founding a “new species” of self-improving AI?

• Claude Code just revealed that it's used by 115k developers and has changed 195M lines of code last week.

• Claude Code was launched about 4 months ago, and you could argue Claude Code has rewritten more lines of code than most engineers see in a lifetime, and faster than most startups can file an expense report.

New grad hiring in BigTech is down -25% and -11% for startups

• What does this brave new world look like exactly? 🤔

What type of AI products are you building?

Read more

Good Morning,

I can’t stop thinking about the AI hyp…

Read more

As you know I am a bit of a chart nerd, when it comes to projections around the AI renaissance.

For the last decade that is since 2015, Coatue has hosted their East Meets West conference, an annual gathering of technology and business leaders for a dialogue on global innovation.

This year they released a projection of some of the biggest corporations in 2030 and there was some chatter about which BigTech players are no longer on the list by 2030, or just five years from now. See for yourself:

The Coatue Fantastic 40

• OpenAI goes public and rises quickly into the top 10 companies in the world by market cap.

• Google does not appear to be a major BigTech corporations by 2030.

• Coatue does not seem to see Anthropic, xAI or other Generative AI firms as major winners by 2030 outside of OpenAI.

Scan the Report

This slides in this analysis are from the event’s keynote address where co-Founders Philippe Laffont and Thomas Laffont opened the conference in their classic "Coatue View on the State of the Markets," and shared their outlook on the macroeconomic landscape and public and private markets.

Why does what Coatue says matter?

Coatue Management has been one of the most active investors in the Generative AI space, with over 50 AI-related companies in their portfolio as of 2023. They've raised a $1 billion fund specifically for AI investments in 2024, demonstrating their strong commitment to this sector.

Major Generative AI Investments

Foundation Models & Infrastructure

• Anthropic - Claude AI assistant and safety-focused AI research

• Together AI - Open-source AI platform ($106M Series A led by Salesforce with Coatue participation)

• Adept AI - AI that can use software tools and take actions

• Character.ai - AI chatbot platform for interactive conversations

• Hugging Face - Open-source machine learning platform ($100M Series C with Coatue participation)

Creative & Content Generation Tools

• Runway - AI video generation and editing platform

• ElevenLabs - AI voice synthesis and cloning technology

• Ideogram - AI image generation platform

• Tome - AI-powered presentation creation tool

Developer Tools & Platforms

• Replit - AI-powered coding platform

• Aurora Solar - AI for solar energy system design

• Norm AI - Regulatory compliance automation

Among VCs that I know who have invested prolifically in AI, only perhaps Nvidia’s lineup to me seems more impressive.

According to ChatGPT

• Internal Rate of Return (IRR) is a financial metric that calculates the discount rate at which the net present value (NPV) of all cash flows from a project or investment equals zero. That is, it represents the effective annual rate of return on an investment, considering the time value of money.

Projections 2025 at 2030. ✨ Coatue’s Fantastic 40 - Implied IRR

1. Arm

2. Stripe

3. Databricks

4. OpenAI

5. Anthropic

The Mechanisms of U.S. Capitalism

I think a great deal about how the stock market accelerates AI especially in an AI driven bull-market like we have seen between 2023 and 2025 accompanied by a surprising demand for compute and enormous capex investments by BigTech in AI Infrastructure that we have covered at some length on this Newsletter.

• Let’s take a quick tour.

According to Nvidia’s founder AI Infrastructure and datacenters will be worth many Trillions of dollars as a market soon. If you like charts and graphs about the future and AI, you might also like:

• AI reports in 2025 Say we are Underestimating Its Impact

• Mary Meeker's AI Report

You will enjoy these charts mostly if you like the history of business and analysis on technological waves and AI’s trajectory.

The Gen AI Bull Market will Shape New Winners and Losers

Read more

Good Morning,

I can’t stop thinking about the AI hype narrative and the momentum this technological wave has upon us. Thank you to all of my readers, we have appeared in Substack’s Technology rising leaderboard this past week.

There are many who claim that AI looks exactly like the dot.com bubble. The level of enthusiasm and capital expenditures BigTech has put into AI chips, datacenters, AI infrastructure and AI talent is hard to even fathom. If you include OpenAI’s investments in Stargate we are talking about a quarter of a Trillion dollars in 2025 easily. This is not counting investments in Europe, the Middle East or China.

BigTech Capex is telling us this is a Generational Boom

Everyone remembers what a bubble looks like 💭

How do you even explain the AI hype bubble from an ROI perspective for most firms? The stock market looks expensive after one of the fastest rebounds in decades since Trump’s “Liberation day” of April 2nd. The AI market’s soaring valuations and speculative investment raise concerns of a potential bubble, despite its transformative potential. Cash rich corporations and Silicon Valley gate keepers are spending as if AGI is right around the corner. While Warren Buffett, Michael Burry and even Jamie Dimon look like they are getting nervous.

This must be “AI Compute Heaven” 🐇

CoreWeave, one of the first Generative era AI startup to go public, disappointed investors, ending its first day of trading with a market cap of $19 billion. The last time it raised funds as a private company, in May 2024, it was already valued at $19 billion, nearly triple its valuation just five months prior. Now in June, guess how much its worth now after six weeks of stock market frenzy? $69.3 Billion. This is the environment we are living in.

OpenAI and Nvidia power Enthusiasm higher 👑

Demand for compute looks insatiable even 2.5 years after ChatGPT went live. Nvidia’s data center sales jumped another 73%. OpenAI seems to raise cash at will now with a valuation of $300 Billion with just a single product, ChatGPT. Venture Capital have spent a lot of capital just to raise the AI narrative up to god-like status in 2025.

But what do VCs really think? The market is trading at a 23x multiple, expensive in any year. The DeepSeek scare of late January feels like a distant memory, now in June. A new AI pantheon including OpenAI, Anthropic, DeepSeek and Thinking Machines Lab may soon challenge the business models of BigTech incumbents. This is simply how markets work during technological shifts.

AI startups are eating Venture Capital budgets

is the author of the Newsletter Weight Thoughts, and is a General Partner at Creative Ventures & Co-Founder of Lioness. Even the most bullish VC or angel investor must wonder about the influx of AI startups eating the industry what this will rationally lead to. AI was eating VC for breakfast in 2024 when it accounted for over 50% of global VC dollars. In 2025, this is starting to become a problem.

Lately James has been putting out some really fascinating articles:

• What LLMs Will Do To Jobs: All You Need is an Oracle

• AI is Overturning the Military World Order

• AI's Endgame (How Foundational Model Companies Can “Win”)

I like how James frames the impact of AI and while techno-optimism predominates in VC circles, how much is just consensus, group-think and wishing thinking I wonder? It’s literally their job to be guardians of a non-critical view of AI’s potential. With the decline of journalism, Venture Capital’s influence on media is only getting stronger. Public relations and lobbying jobs are replacing dying investigate journalism jobs for a reason. “AI mode” is breaking the internet, and this is a weird shift for the internet. The zero click internet is upon us.

The AI Bull Market Could Last Years 🐮

We know this moment feels like an AI bubble, but what does the data say? The U.S. stock market has a Historical Average P/E: ~20.5 (modern era). Today we’re looking at valuations more like U.S. Stock Market P/E: ~24.34 (estimated). We appear to be in an AI bull market. The reality is demand for AI chips and datacenter expansionism and National Defense spending with geopolitical uncertainty could extend this bull market for years to come, giving Generative AI ample time to actually back up its swanky visions of AI Supremacy pitch decks and Venture Capitalist and Tech CEO proclamations. It’s all go if you are an AI podcast bro.

My baseline view of VC’s reality with AI, isn’t biased with financial incentives and insider knowledge of how great AI is going to be:

• Mary Meeker's AI Report

• I asked James for his take on Mary Meeker’s incredibly detailed AI report. To my surprise he took the are we in an AI bubble analysis up in a fairly detailed way and to new levels.

Subscribe now

I admire James also for asking some of the biggest questions in AI technology. He’s also working on a related book. I wish I knew more VCs who invest in the AI space, feel free to DM me on LinkedIn if you are one. So much of what we are doing today depends on the timing and historical curve of the Generative AI cycle. Recessions and Deep learning winters don’t come as often as they once did, but are there structural issues in the mania?

Where Are We in the AI Cycle—Boom or Bust?

Read more

This is the most extensive list of AI related Newsletter on the internet today in 2025. I will now be moving on to my next project: Who to follow in AI on LinkedIn.

• For the best reading experience, read this in a web browser. (click on the title)

  ---

• If you know someone interested in AI, why not share them this highly curated list of AI Newsletters to check out. It might help put Gen AI in context 🔮.

Share

🙏🏻 Enjoy my coverage of authors in AI and their abundant guest contributions with us, show your support:

Subscribe for Less than $2 a Week

📈 As a curation based guest contribution friendly publication, part of my job is to highlight and feature other writers.

🔥 This is also so my readers can get the best value and experience. See the first edition of this list here. Now a few days later, the list has been updated.

The Ultimate Listicle on AI Newsletters

🎓 If you want to learn about AI, you might in short, want to read these people.

Share

1

Semianalysis 🚀 - go to Newsletter.

• Dylan Patel may have left Substack, but that’s more a credit to his success than anything else. His deep dives are still very much followed in understanding AI at the intersection of semiconductors, Nvidia, datacenters, AI Infrastructure and AI chips.

• Dylan Patel is Chief Analyst and founder of SemiAnalysis, a boutique research and consulting firm focused on semiconductors and data center infrastructure. He’s basically the world’s biggest AI hardware nerd.

• His Newsletter brings him hundreds of thousands (millions?) of dollars worth of of leads to his boutique consulting business. Not hard to argue that he’s the current 2025 GOAT of Semiconductor AI analysis.

2

One Useful Thing 🎓

One Useful Thing

Trying to understand the implications of AI for work, education, and life. By Prof. Ethan Mollick

By Ethan Mollick

• Ethan Mollick is an AI evangelist who specializes in studying the intersection of entrepreneurship, innovation, and the effects of AI on work and education.

• Featured Piece: 15 Times to use AI, and 5 Not to

• His pieces are often short, easy to read and appear to be for a general audience. He leads Wharton Interactive, an initiative aimed at democratizing education through the use of technologies like games and simulations, particularly leveraging AI to enhance learning experiences.

2.5

Ahead of AI 🧠

Ahead of AI

Ahead AI specializes in Machine Learning & AI research and is read by tens of thousands of researchers and practitioners who want to stay ahead in the ever-evolving field.

By Sebastian Raschka, PhD

• Sebastian Raschka is an acclaimed author, and expert in machine learning, recognized for his substantial contributions to academia and industry.

• Ahead of AI is among the most accessible Newsletters on machine learning papers and LLMs in the world.

• Featured Piece: The State of LLM Reasoning Models

3

Creator Economy by Peter Yang 💬

Creator Economy by Peter Yang

Practical guides to save time with AI, craft better products, and advance your product career. Get a list of my favorite AI tools when you sign up.

• Peter Yang increasingly talks about AI in his work related to product management and creator economy innovations. I didn’t used to consider him an AI voice but now I do.

• His AI Track section on his Newsletter has gotten very interesting. Featured Piece: 24 AI Tools Ranked from Essential to Forgettable for 2025

• He has legit Product Management experience in Silicon Valley and companies like Roblox, Reddit, Twitch and Twitter. He usually stays at a company for around two years, so I’m curious to see where he goes next after Roblox.

4

Understanding AI 💎

Understanding AI

Exploring how AI works and how it's changing our world.

By Timothy B. Lee

• Timothy B. Lee is a prominent journalist and writer who specializes in technology, economics, and public policy. Although it’s his journalism around AI that I find most compelling.

• Featured Piece: Driverless trucks are coming and unions aren’t happy about it

• His coverage of the autonomous vehicle space is great and he’s able to put things into layman terms for a wider general audience.

5

Blood in the Machine ✊

Blood in the Machine

A newsletter about AI, Silicon Valley, labor and power.

By Brian Merchant

• Brian Merchant is a tech journalist, author, and commentator, with a focus on the implications of AI, technology, and automation on society. (Formerly L.A. Times)

• Featured Piece: The tech oligarchs and their AI are taking over. Let's fight back.

• Recently going full-time as a publication manager, “Blood in the Machine” is actually the name of his 2023 Book. He hosts Systems Crash_ podcast with of Disconnect Newsletter.

This list continues in some depth and is an on-going project. Audio version for paid readers below.

TL;DR Audio version of 1-50:

6

Interconnects 🔎

Interconnects

The cutting edge of AI, from inside the frontier AI labs, minus the hype. The border between high-level and technical thinking. Read by leading engineers, researchers, and investors on Wednesday mornings.

By Nathan Lambert

• Nathan Lambert is known for his research focusing on open language models, RLHF, and the responsible development of autonomous systems. His Newsletter is primarily for ML researchers and engineers.

• In recent years he’s held important AI researcher positions in Open-Source AI startups and nonprofits, started a podcast and even appeared on prominent YouTubes and podcasts.

• He conducts interviews, and is a leading writer and thinker on fairly technical topics such as RLHF, reasoning models and open-weight LLMs.

7

Ed Zitron's Where's Your Ed At ⚡ - go the Newsletter.

• Ed Zitron is a prominent figure in the AI discourse, known for his critical stance on the technology and its implications. A Brit in Las Vegas, he’s primarily an OpenAI critic and one of the more serious meticulous ones. He has a great Podcast too.

• Featured Pieces: OpenAI Is A Bad Business

• His long-ass deep dives have a lot of links and feel credible, though not all of his business opinions are from a place of due diligence or much financial understanding imho. It doesn’t really matter though, he’s worth checking out. He’s now a Bluesky celeb and one of my favorite AI Newsletters hosted on Ghost.

8

The Product Compass 🧭

The Product Compass

Actionable insights and resources for Product Managers. #1 place to grow as a PM. Weekly newsletter.

By Paweł Huryn

• Paweł Huryn is yet another talented Product voice who has gotten very good at talking about AI and his niche. His work focuses on bridging the gap between AI technologies and practical product management strategies.

• Featured Piece: AI Prototyping: The Ultimate Guide For Product Managers

• He’s full of cheat sheets, resources, research and applied educational content.

9

The Algorithmic Bridge 🌊

The Algorithmic Bridge

A blog about AI that's actually about people

By Alberto Romero

• Alberto Romero’s work largely is aimed at helping non-technical audiences understand complex AI concepts which is does with attractive storytelling and a relatable personal brand.

• He enjoys discussing rumors, exploring original ideas and creatively leads the reader to some often profound realizations about Generative AI while keeping them up to date on the latest AI News. He’s really entertaining and great at breaking AI news stories.

• What I like is he doesn’t clamor after attention on social media, but is beloved for his own writing style and warm personality.

10

Exponential View 📊

Exponential View

“The best for understanding how tech can solve our biggest problems, shape our society and bridge cultural divides.“ - Daniel Ek

By Azeem Azhar

• Azeem Azhar is a British technology entrepreneur, author, and founder of this media publication - Azhar's work primarily revolves around understanding how AI and other exponential technologies impact society, the economy, and business.

• Featured Piece: 🏮DeepSeek: everything you need to know right now.

• One of the best things about this publication is their charts.

11

Latent Space 🧩

Latent.Space

The AI Engineer newsletter + Top 10 US Tech podcast. Exploring AI UX, Agents, Devtools, Infra, Open Source Models. See https://latent.space/about for highlights from Chris Lattner, Andrej Karpathy, George Hotz, Simon Willison, Soumith Chintala et al!

By swyx & Alessio

• Swyx, whose real name is Shawn Wang, is recognized for his contributions as a developer, writer, podcaster and entrepreneur. He is particularly known for his advocacy and exploration of AI engineering.

• Latent Space is among the fastest growing paid AI focused Newsletter on Subtack in early 2025.

• In his discussions and presentations, Swyx emphasizes the emerging role of AI engineers—those who not only build software using AI tools but also contribute to the development of AI technologies themselves. An Educator, entrepreneur and author, he runs hackathons for AI engineers and manages communities. Before becoming a software engineer and an AI engineer, he started off in Finance. I think his writing is mostly geared at software developers and ML engineers.

12

Department of Product 📌

Department of Product

Product-led analysis and knowledge for people who work in tech. Join product managers, designers, engineers and VCs from Spotify, Netflix, Apple, Stripe and more.

By Rich Holmes

• Rich Holmes provides product-led analysis and insights for professionals in tech, including product managers, designers, engineers, and VCs. His insights in AI are always fresh, applied, timely and on point.

• He makes a lot of important and original real-world insights about AI in product and the future of work that I find very relevant for anyone interested in technology. His Knowledge Series and Deep Dives sections on his Newsletter are really good.

• Featured piece: Deep: The UX of AI Assistants

Want to share this list with associates, friends, students or co-workers: use the secret link:

Share this resource

13

The Sequence 💼

TheSequence

The best source to stay up-to-date with the developments in the machine learning, artificial intelligence, and data science world. Trusted by 165,000 professionals from the main AI labs, universities, and enterprises

By Jesus Rodriguez

• The Sequence is a well-regarded newsletter focused on developments in the fields of artificial intelligence (AI), machine learning, and data science.

• While most of their posts are locked to for premium readers but it’s only $6 a month.

• This is one of the older and bigger Newsletters often with tidbits about research and recent AI News.

14

Marcus on AI 🔥

• Gary Marcus is is a cognitive scientist, author, and entrepreneur with extensive experience in AI research and development and a famous critic of OpenAI.

• Featured piece: The race for "AI Supremacy" is over — at least for now.

• Gary pushes a contrarian vibe popular these days in independent journalism. His pieces (hot takes) are generally on the sensationalistic though attempt to have some bearing on rationalism are often are like napkin worthy Op-Ed arguments. His work feels a bit like made for Twitter content.

15

Elena’s Growth Scoop ✨

Elena's Growth Scoop

A must-have resource for anyone in the growth, marketing, or product space.

By Elena Verna

• Elena Verna is a prominent growth strategist and advisor, primarily known for her expertise in the B2B SaaS sector. She makes many useful observations about AI related to future of jobs, growth, marketing and product.

16

The Kaitchup – AI on a Budget 🍟

The Kaitchup – AI on a Budget

Weekly tutorials, tips, and news on fine-tuning, running, and serving large language models on your computer. The Kaitchup also publishes two new AI notebooks every week.

By Benjamin Marie

• Benjamin Marie is a Ph.D. who discusses fine-tuning, running and serving LLMs on your computer. He’s a great source for open-source models and primarily targets ML engineers and software engineers tinkering with AI models.

• I love his work, even with a small-ish audience he’s managed to convert many of them to premium, a credit to the value he provides. Featured piece: TransMLA: Improve Qwen2.5 and Llama 3x LLMs with DeepSeek's Multi-Head Latent Attention

• Traditionally he gets a lot of traffic from his very niche and long tail SEO. His work demonstrates the demand for applied tips in AI in managing LLMs locally.

17

Marily Nika’s AI Product Academy Newsletter 💡

Marily Nika’s AI Product Academy Newsletter

AI PM Insights, Jobs, AI PM Certifications by Google's Dr. Marily Nika. Marily is a Silicon Valley AI Product Leader & one of the world's top educators with 12+ years of experience launching AI products at Google & Meta.

• Marily Nika has established herself as an influential AI Product Leader, with over 10 years of experience in the tech industry, particularly at leading companies like Google and Meta.

• She has a long list of courses on Maven related to her niche.

• Marily is a notable advocate for the integration of AI in product management. She believes that in the future, all product managers will need to embrace AI in their workflows

18

Fabricated Knowledge 🌌🪐💫☄️

The best Semiconductor Newsletter after Dylan left, was shortly thereafter itself, acquired by SemiAnalysis.

Fabricated Knowledge

Let's learn more about the world's most important manufactured product. Meaningful insight, timely analysis, and an occasional investment idea.

By Doug OLaughlin

• Doug O'Laughlin is a prominent figure in the fields of semiconductors and artificial intelligence (AI), recognized for his insightful analyses and contributions to the industry. Primarily, he writes about the most critical manufactured good in the world's history (semiconductors) and how that impacts the world's semiconductor companies.

• A good Newsletter for understanding the semiconductor industry at it relates to BigTech and AI trends.

19

Artificial Intelligence Made Simple 🌱

Artificial Intelligence Made Simple

Covering the implications of important ideas in AI from all angles- technical, social, and economic. Read in over 180 countries. Sister Publication to Tech Made Simple

By Devansh

• Devansh holds the title of Chocolate Milk Cult Leader, which reflects his unique branding in the tech community. His topic choice is super original I find.

• Featured piece: What Math do you need to be Good at AI

• He is good at memes and is one of the most read AI Newsletters among readers also in India.

20

Luiza’s Newsletter ⚖️

Luiza's Newsletter

A leading AI governance publication read by 55,000+ subscribers in 165+ countries

By Luiza Jarovsky

• Luiza Jarovsky is recognized as a leading expert in AI governance, advocating for clear and actionable insights in the rapidly evolving landscape of technology and its societal implications.

• Based out of Tel Aviv, Israel - her upskilling programs empower the next generation of AI governance leaders, with over 1,100 professionals trained.

• Featured piece: ✋ Manus AI: Why Everyone Should Worry

This list is curated by AI Supremacy Newsletter in March, 2025.

21

The AiEdge Newsletter 🧪

The AiEdge Newsletter

A newsletter for continuous learning about Machine Learning applications, Machine Learning System Design, MLOps, the latest techniques and news. Subscribe and receive a free Machine Learning book PDF!

By Damien Benveniste

• With a PhD in Physics, Damien Benveniste has built a diverse background as a Data Scientist, Machine Learning Engineer, and Software Engineer. His Newsletter is primarily for software engineers who want to learn about machine learning or ML engineers learning more about LLMs.

• His Newsletter is fairly technical. He once worked at Meta and is a Machine learning consultant and also has built courses.

22

Import AI 🎯

Import AI

Import AI is a weekly newsletter about artificial intelligence based on detailed analysis of cutting-edge research.

By Jack Clark

• Jack Clark is one of the Billionaire co-founders of Anthropic. Formerly a journalist, he has played a significant role in shaping discussions around AI policy and safety, with a focus on ensuring that advanced AI technologies are developed responsibly and ethically.

• He’s been writing Import AI for over 8 years according to his LinkedIn profile and to this day it’s one of the most readable roundups in the space.

• He’s also the Co-Chair of the AI Index Steering Committee at Stanford HAI, among many other projects. Previously he was a reporter at Bloomberg and The Register.

23

The Generalist 🌟

The Generalist

The people, companies, and technologies shaping the future.

By Mario Gabriele

• Mario Gabriele is a notable figure in the VC, tech and AI landscape. He publishes insights on various technological advancements, including artificial intelligence, productivity and the future of work.

• Featured Piece: AI and The Burden of Knowledge

• Yet another Brit, though not an AI native Newsletter, his VC geared Newsletter touches on AI enough for some minor consideration.

24

Write With AI 💥

Write With AI

The leading paid newsletter for ChatGPT & Claude prompts, and how to turn AI platforms into your own personal Digital Writing Assistant.

By Nicolas Cole

• Nicolas Cole is a prominent figure in the realm of digital writing, known for his contributions as a writer, author, entrepreneur, and educator. This includes the entire spectrum of courses and how to write using AI and AI tools.

25

Wonders Tools 🦸‍♂️

Wonder Tools

Wonder Tools helps you discover the most useful sites and apps

By Jeremy Caplan

• Jeremy Caplan writes at the intersection of applied AI, AI Tools, journalism and education. Jeremy Caplan is currently the Director of Teaching and Learning at the Newmark Graduate School of Journalism at the City University of New York. Previously he has worked as a journalist at Time Magazine, Yahoo and Newsweek.

• If you like AI tools, you will definately like his Newsletter.

26. The Business Engineer 🛠️

The Business Engineer

At the intersection of business strategy, technology, and non-linear analysis, The Business Engineer is the fruit of ten years of research into the business tech world by Gennaro Cuofano, creator of the leading business model strategy blog FourWeekMBA.

By Gennaro Cuofano

• The work of Gennarno Cuofano delves into how AI can serve as a core enabler of business models, influencing industry dynamics and economic growth.

27. The AI Break 📰

The AI Break

Welcome to 'The AI Break' – where we serve you hot slices of AI news in a 5mn coffee break. Join over 80k AI individuals + Get Access to our AI & Automation Resources.

• Luis and Rui Sousa are Portuguese entrepreneurs, paid marketing consultants that love building businesses. Among their expertise, they encompasses content strategy and the integration of AI tools into business processes, particularly in marketing.

• The AI Break is among the best beehiiv-esque AI News rundowns on Substack.

28. Disconnect 🚨

Disconnect

How the tech industry is shaping the world we live in — without the boosterism and bootlicking

By Paris Marx

• Back from a stint on Ghost platform, Paris Marx is a Canadian technology journalist, author, podcaster, and critic, known for his insightful critiques of technology and its societal implications. He hosts the podcast Tech Won't Save Us that is critically acclaimed.

• Marx is the author of Road to Nowhere: What Silicon Valley Gets Wrong About the Future, where he argues against the pervasive narrative that technology will automatically lead to progress and better social outcomes. You can book him for international speaking gigs. Great things are ahead for Paris, another Bluesky celeb.

29. Generative Value 🗿

Generative Value

Sharing learnings about tech & business.

By Eric Flaningam

• Eric Flaningam work involves analyzing industry trends and public equity research, particularly focusing on the intersection of technology, business and AI.

• His writing and explorations specifically on AI markets and value chains associated with AI technologies are as far as I’m concerned, legendary.

30. Don't Worry About the Vase ⚠️

• Zvi is some kind of urban legend among AI writers. Maybe the best pure writer & curator on AI out there. Zvi Mowshowitz is recognized for his contributions to understanding AI's implications on society, policy, and technology. He engages in extensive exploration of AI, particularly the risks and benefits associated with its rapid development.

• Mowshowitz's work involves modeling complex systems and analyzing the broader impacts of AI advancements. He is actively involved in discussions surrounding AI's potential risks, often emphasizing the existential risks related to AI's growth and integration into society. I consider him an AI expert, especially concerning AI risk and breaking down AI News for various audiences.

Trending articles on AI Supremacy Newsletter:

• What is Vibe Coding?

• Gemini vs ChatGPT Deep Research destroyed my expectations

• The Robots are coming: Genesis

• How to use NotebookLM for personalized knowledge synthesis

This list currently goes till 175+.

Read AI Guides

31. AI Tidbits 🤓

AI Tidbits

Stay ahead on the latest in AI through weekly summaries and editorial deep dives providing unique perspectives on recent developments

By Sahar Mor

• Sahar Mor has over 12 years of engineering and product management experience with a particular focus on AI-driven products. His work is aimed at illuminating complex AI concepts for a broader audience. His series on Agentic AI is incredible.

• He packs a lot of Open-source AI and agent framework value for software engineers, devs and PMs tinkering with AI.

32. Semi Vision 📱

SEMI VISION

SemiVision is a semiconductor industry research institution committed to transforming analysis into vision through comprehensive insights into the semiconductor ecosystem.

By SEMI VISION_TW

• Although geographically very close to my location, I do not know the writers / personalities Jett C. and Eddy T. Increasingly the Semiconductor field is important for understanding AI. So Semi Vision, is in fact a semiconductor industry research institution dedicated to providing comprehensive insights into the semiconductor sector. This newsletter focuses on transforming analysis into actionable knowledge, catering to professionals and enthusiasts in the semiconductor field.

• They founded Semi Vision, about 8 months ago which would have been in mid 2024.

33. Semiconductor Business Intelligence 📚

Semiconductor Business Intelligence

If your business or portfolio depends on semiconductors, you must know the supply chain dynamics: "Your future might be somebody's past!" Get one deep analysis a week of a key company or sector of the semiconductor supply chain.

By Claus Aasholm

• Man do I like this guy’s charts! Again sort of hard to pin down, mostly a consultant at the intersection of Semiconductors, Chips companies, investing, Earnings calls and so forth. In a relatively short period, Claus Aasholm has gained recognition as an analyst who focuses on the intersections between semiconductors and AI technology. His charts on Semiconductor companies and and semi supply chain insights, endlessly fascinate me.

• A semiconductor geek out of Denmark.

34. Faster Please 💨

Faster, Please!

Discovering, creating, and inventing a better world through technological innovation, economic growth, and pro-progress culture.

By James Pethokoukis

• James Pethokoukis is a prominent economic analyst and commentator known for his work on U.S. economic policy, technology, and public policy, particularly regarding the transformative potential of artificial intelligence (AI).

• There are more innovation centric Newsletters making important insights on AI’s impact, and this is among the best of them. James is yet another CNBC contributor who has a Substack presence.

35. ChinaTalk 🏙️

ChinaTalk

Deep coverage of technology, China, and US policy. We feature original analysis alongside interviews with leading thinkers and policymakers.

By Jordan Schneider

• Jordan Schneider’s Newsletter is transforming into a very serious publication - especially in the context of US-China relations in technology. He is the founder of the ChinaTalk podcast and newsletter, where he explores the intersection of technology, China, and US policy.

• Watch out for his great guest posts too and contributions of . Substack’s considerable China news and geopolitical Newsletters now make important contributions to our understanding of AI.

36. Designing with AI 🎨

Designing with AI

Exploring the intersection of AI and design. Through experimentation, I'll share observations and reflections on emerging tools, inspiring examples of AI in action, and reflections on the future of design as a discipline.

By Mia Blume

• Mia Blume is a notable figure in the intersection of design and artificial intelligence (AI). She has a rich background as a design leader. She is among the most commercially successful with paid subscriptions among the many women in AI writing on Substack. She’s previously worked at the likes of Pinterest, Square, IDEO, and is now very much involved in design education and executive coaching.

37. Newcomer 🦄

Newcomer

Where technology and venture capital intersect: A deeply reported newsletter on the inner workings of the startup industry. Helmed by Eric Newcomer with writing from Madeline Renbarger.

By Eric Newcomer

• Eric Newcomer is a prominent figure in the world of startups and venture capital, particularly known for his work in the artificial intelligence (AI) sector. While not a pure play AI Newsletter, his publication touches on VC and AI in a way that is worth exploring especially his VC events in Silicon Valley. You can find interviews, charts, rumors, investigations and hints about what’s coming next in AI.

38. Implications

Implications, by Scott Belsky

What to expect from the latest advances in tech, shifts in culture, and evolution in the art and science of product design and building teams.

• Scott Belsky talks about and his work contributes to creativity and design, particularly as they intersect with technology, including artificial intelligence (AI). If I’m not mistaken, his work focuses more on AI in recent months. He explores a spectrum of implications of recent advances in tech, shifts in culture, and both the art and science of product design and building teams as well as the future of work.

39. Decoding Discontinuity 🌊

Decoding Discontinuity

A newsletter that provides frameworks for analyzing the financial and strategic impact of emerging technologies like GenAI.

By Raphaëlle d'Ornano

• Raphaëlle d'Ornano specializes in innovative growth solutions and advanced growth intelligence and is an AI fund manager among other things. Recently, she especially helps investors and businesses unlock value by decoding the discontinuities reshaping industries, particularly those driven by generative AI.

40. Generative Value 🌱

Generative Value

Sharing learnings about tech & business.

By Eric Flaningam

• Eric Flaningam focuses on the venture capital landscape and on researching early-stage startups. His work emphasizes tech research, value investing, and data visualization, reflecting a commitment to understanding and innovating within the technology sector. His pieces on Generative AI, ecosystems, supply-chains and how everything fits together is fascinating reading.

Read articles on OpenAI

41. Big Technology 🚢

Big Technology

A newsletter about big tech and society by independent journalist Alex Kantrowitz.

By Alex Kantrowitz

• Alex Kantrowitz is an independent journalist, podcaster and founder celebrated for his interviews with BigTech and their executives, as well as being a CNBC contributor. His Newsletter touches upon AI fairly often. His guests often make important revelations about the state of Generative AI, the stock market and investing in AI.

42. AI Proem 🖋

AI Proem

AI Proem provides reports and analyses on global AI x infrastructure, AI innovation, Physical AI, and big-tech AI. With a focus on U.S.-China.

By Grace Shao

• Grace Shao is a researcher, writer, and China tech analyst specializing in technology, AI, Chinese companies, datacenters, and physical AI. Her primary research and writing focus is on understanding the relationship between AI and energy resources, China’s AI and tech sectors, and their relationship with the rest of the world. In only a brief period she’s become one of the most important emerging voices at the intersection of China, technology and deep dives relevant to investors.

43. AI Snake Oil 🦎

AI Snake Oil

Debunking AI hype. The book gives you foundational knowledge and the newsletter covers new developments.

By Sayash Kapoor

• Arvind Narayanan is a prominent professor of computer science at Princeton University and the director of the Center for Information Technology Policy. His research primarily focuses on the societal impacts of artificial intelligence (AI) and technology, exploring how these innovations interact with issues such as privacy, security, and public policy. He’s known for debunking myths and correcting public narratives around AI via fact based investigations and academic rigor.

44. Deep (Learning) Focus 🔬

Deep (Learning) Focus

I contextualize and explain important topics in AI research.

By Cameron R. Wolfe, Ph.D.

• Cameron R. Wolfe is among the most read ML engineers and researchers known for his blend of academic and practical experiences. He has extensive experience at companies such as Netflix and Salesforce. He breaks down LLM concepts and techniques and his Newsletter is mostly for those with a technical and engineering background. His work includes a lot of helpful diagrams and infographics particularly on LLM breakdowns.

45. Interconnected 🖇

Interconnected

On the intersections of tech, investing, geopolitics, and US-Asia relations

By Kevin Xu

• Kevin Xu is a fund manager, geopolitical researcher, and his work focuses in part on insights related to AI, U.S. and China topics and investment strategies. He thinks about the venn diagram of how builders, operators, investors, regulators, and how they are all (inter)connected which I find fairly useful. The value prop on his Interconnected Premium network has improved a lot in recent months.

46. NLP Newsletter 📚

NLP Newsletter

The NLP Newsletter provides weekly summaries of the latest and top AI trends, papers, tools, news, and best practices. Home of Top AI Papers of the Week and AI Agents Weekly series.

By elvis

• Elvis Saravia unlocks the latest AI papers and is specifically known for his contributions to machine learning and natural language processing (NLP). A YouTuber, he’s worked at Elastic, Meta and now DAIR.AI. Saravia is recognized as a machine learning research scientist and educator and is based in Belize, one of the smaller countries in South America. I’m a huge fan of his AI paper summaries.

47. The EU AI Act Newsletter 💡

The EU AI Act Newsletter

Up-to-date developments and analyses of the EU AI Act

By Risto Uuk

• Risto Uuk an AI policy research. He’s Head of EU Policy and Research at the Future of Life Institute in Brussels, leading policy and research efforts to maximize the societal benefits of increasingly powerful AI systems, among many other positions. His coverage of the EU AI Act Newsletter is one of the best sources for the topic in my opinion. While this list is not full of AI policy researchers, he’s among the most accessible.

48. AI Disruptor 🗺️

AI Disruptor

Practical AI guides, analysis, and content workflows for creators and builders.

By Alex McFarland

• Alex McFarland is known for creating practical guides and workflows tailored for creators and builders in the AI space. His work aims to bridge the gap between complex AI concepts and their practical applications in various fields, making AI more accessible to a broader audience. His emphasis on how-tos, guides, and applied practical utility of AI tools, chatbots and niche applications is a great launching pad for learning about AI. Surprisingly, there aren’t many Newsletters on Substack that focus on AI tools as you’d think.

49. AI Health Uncut 🚨

AI Health Uncut

Brutally honest insights from a healthcare AI founder on digital health, AI models & health AI investments, drawn from personal experiences, mistakes, successes & unique perspectives. An all-in authentic original research.

By Sergei Polevikov

• Sergei Polevikov is one of my favorite voices on AI in healthcare and is a realistic and a critic. I would almost call him an activist against the various corruption and Venture Capital manipulation in the healthcare and AI healthcare startup space, certainly an accountability journalist and researcher. He’s a founder, author and entrepreneur with experience as an executive, board director, etc… His commitment to unfiltered truth and unwavering factual integrity as an investigator is really the definition of an accountability journalist in the independent media and citizen journalist era.

50. Artificial Corner 🤖

Artificial Corner

Artificial Intelligence in plain English. Join thousands of tech enthusiasts, programmers, and data professionals looking to make the most out of AI.

By The PyCoach

• Frank Andrade (aka PyCoach) provides a range of educational resources aimed at both tech enthusiasts and professionals. The content often breaks down complex AI topics into simpler, more digestible formats, which is particularly useful for individuals without extensive programming knowledge. He’s a great resource for software engineers and those exploring AI systems, in particular Python.

TL;DR Audio Version 51-101

Read Robotics Articles

51. DiamantAI 🌱

💎DiamantAI

DiamantAI is the top 0.1% newsletter for staying ahead in AI, uncovering the latest techniques, breakthroughs, insights, and unique tutorials.

By Nir Diamant

• Nir Diamant is the founder of DiamantAI, where he focuses on consultancy services related to AI and machine learning. He excels at providing guides to things like Agentic AI and various frameworks related to machine learning. His exclusive tutorials and code walkthroughs are sought after especially among software engineers looking to transition into Machine learning engineering. He’s built an active educational AI community and provides a ton of value including a guide to Prompt engineering.

52. AI Disruption 🎯

AI Disruption

A 10-year AI engineer from Beijing shares industry analysis and technical insights on AI, with at least two articles updated daily.

By Meng Li

• Meng Li provides honestly a ton of content. You can find things on their Newsletter that is difficult to find elsewhere due to the volume and niche of their areas of AI focus. I enjoy the Newsletter mostly for its diligence in covering AI breaking news in a timely fashion. With a background in theoretical and practical aspects of AI, they are an entrepreneur, speaker and researcher usually based out of Beijing. Among the highest high bloggers and curators that I know of in the space.

53. New Economies 💸

New Economies

New Economies is your regular newsletter that discovers the latest technology trends shaping our world.

By Ollie Forsyth

• Ollie Forsyth is recognized for his extensive work in writing and exploring technology trends, particularly in artificial intelligence. Based out of Thailand and ex VC I really resonate with his work. His deep dives and infographics really help founders and VC enthusiasts understand the ecosystem better across industries, tech-stacks and various kinds of bleeding edge startups. It’s also useful information for investors, executives, tech enthusiasts and entrepreneurs. Formerly at Antler.

54. SwirlAI Newsletter 🌀

SwirlAI Newsletter

Learn about end-to-end Data Systems and stay up to date with what is happening in the Data World.

By Aurimas Griciūnas

• Aurimas Griciūnas is the Founder and CEO of SwirlAI, where he focuses on leveraging AI to enhance data engineering practices and improve machine learning workflows. With over a decade of experience in data science, AI/ML engineering, and MLOps, he is dedicated to helping practitioners enhance their technical skills. Great visuals, highly professional, useful for technical readers.

55. The Ontologist

The Ontologist

Principles of Metadata Architecture, Graph Theory and AI

By Kurt Cagle

• Kurt Cagle has a rich background in technology analysis, with particular emphasis on AI and data science. He has authored over twenty books and articles that explore these subjects, reflecting his extensive knowledge and experience in the field. He has been a Chief editor, author and everything in-between and is fairly technical and historical at times. He has several Newsletters and is an Ontologist | Author | Iconoclast.

56. Exploring Language Models

Exploring Language Models

ML Engineer writing about GenAI | Open Sourcerer (BERTopic, PolyFuzz, KeyBERT) | Author of "Hands-On Large Language Models".

By Maarten Grootendorst

• Maarten Grootendorst is known for his unique blend of expertise in data science and psychology. He holds a position at O'Reilly and is associated with the Jheronimus Academy of Data Science in Tilburg, Netherlands. His visual guides to LLM are in 2025 the stuff of legend.

57. More than Moore

More Than Moore

The latest in semiconductors: silicon, AI, processors, market trends.

By Dr. Ian Cutress

• Ian Cutress focuses on advancing semiconductor technologies. His work involves collaborating with various semiconductor companies to enhance their messaging and technologies in the rapidly evolving landscape of AI and high-performance computing.

58. The Gradient

The Gradient

Articles, interviews, and news coverage about AI brought to you by a team of AI researchers and builders.

• Andrey Kurenkov is co-founded notable platforms like The Gradient and Last Week in AI, which aim to disseminate insights and advancements in the AI field to a wider audience. Kurenkov is also active in the academic and research community, serving as a lead editor for various publications addressing AI trends and technologies. The Gradient is known for its in-depth interviews by .

59. ChinAI Newsletter

ChinAI Newsletter

Jeff Ding's weekly translations of writings from Chinese thinkers on China's AI landscape

By Jeffrey Ding

• Jeffrey Ding is an Assistant Professor of Political Science at George Washington University. His academic work primarily focuses on the intersection of emerging technologies, particularly artificial intelligence, and international relations. He examines how technological advancements, like AI, influence geopolitical dynamics and the rise of great powers, in particular China.

60. AI: A Guide for Thinking Humans

AI: A Guide for Thinking Humans

I write about interesting new developments in AI.

By Melanie Mitchell

• Melanie Mitchell is a prominent figure in the field of artificial intelligence, serving as a Professor at the Santa Fe Institute. Her work spans several interdisciplinary fields, including artificial intelligence (AI), cognitive science, and complex systems. She’s known for her clarity and ability to write about difficult topics in a concise way. She often writes about the nature of intelligence itself and whether LLMs can reason are among her more memorable essays.

Read AGI articles

61. The Nuanced Perspective

The Nuanced Perspective

Guidance and insights on AI, career, and life for those who appreciate depth

By Aishwarya Naresh Reganti

• Aishwarya Naresh Reganti primarily focuses on developing enterprise-ready generative AI solutions and large-scale machine learning techniques as well as Generative AI guides and educational material. She works at AWS.

62. Colligo

Colligo

Toward a humanistic theory in an age of data

By Erik J Larson

• Eric J. Larson is recognized for his contributions as an author, computer scientist, and entrepreneur. He currently serves as a Fellow at the Technology & Democracy Project at the Discovery Institute and is the author of the book The Myth of Artificial Intelligence, where he critically examines the misconceptions surrounding AI and its capabilities compared to human intelligence. Larson's work focuses on the limits of technology and its implications for human society. His original criticism is great reading.

63. Humanity Redefind

Humanity Redefined

Humanity Redefined sheds light on the bleeding edge of technology and how advancements in AI, robotics, and biotech can usher in abundance, expand humanity's horizons, and redefine what it means to be human.

By Conrad Gray

• Conrad Gray explores the intersection of AI and biology, particularly how advancements in these areas could redefine humanity. His coverage of transhumanism, emerging tech, robotics and AI is notable. His keen interest in biotechnology and background as a software engineer and his consistency as a blogger give him a very well rounded sense of curation and essay. A great source to keep up with emerging tech news that goes into some depth.

64. Artificial Ignorance

Artificial Ignorance

At the intersection of engineering and intelligence. Essays, analysis, tactics, news, and more.

By Charlie Guo

• Charlie Guo is an entrepreneur, author and thinker-doer who shares essays, analyses, and insights related to engineering and AI. His writing often explores the complexities and future possibilities of AI, reflecting his deep understanding of the intersection between software engineering and artificial intelligence.

65. Educating AI

Educating AI

Let's figure how to best integrate and implement generative AI into today's classrooms!

By Nick Potkalitsky

• Nick Potkalitsky is recognized for his work as an AI Literacy Consultant, Instructor, and Researcher, dedicated to enhancing educational practices through the implementation of AI tools. His approach emphasizes creating innovative instructional strategies that not only incorporate AI technologies but also equip teachers and students with essential AI knowledge and skills. A prolific essaysist on AI in education, consultant and CEO.

66. Recode China AI

Recode China AI

China AI Spotlight: Your weekly guide to China's AI breakthroughs, trends, and stories.

By Tony Peng

• Tony Peng is particularly recognized for his contributions to the integration of AI with various media and communication formats. He has a multifaceted career that combines journalism, communications, and technical expertise in AI. He worked at Synced and had a public relations role recently at Baidu. One of the best voices for understanding China’s unique AI, business and tech ecosystem.

67. Global Technology Research

Global Technology Research

GTR

By AYZ

• The author of GTR, AYZ has chosen not to make his ID public. Mandarin versions of the blogs are found here. The author appears to focus on many semiconductor insights as well and is grounded in TSMC and its industry so is perhaps located in Taiwan.

68. Generative AI Publication

Generative AI Publication

All the latest news and resources on generative AI space.

By Jim Clyde Monge

• Jim Clyde Monge has career experience in software engineering, and has worked extensively as a developer and has a solid background in research and development engineering. His work focuses on the intersection of AI technology and practical applications, making significant contributions to the discourse surrounding generative AI. His work is similar to many of the new Newsletter focused around AI News that came into being in 2024 and first took hold on beehiiv platform in 2023.

69. The Thesis by Leonis

The Thesis by Leonis

Leonis Capital is a research-driven VC fund based in Silicon Valley. We share our latest research and thinking in this blog.

By Leonis Capital

• Jenny Xiao is primarily recognized for her role as a venture capitalist and researcher. Currently, she serves as a Partner at Leonis Capital, a research-driven venture capital firm that focuses on supporting technical founders in the AI domain. Her work bridges the gap between groundbreaking research and transformative investments, particularly in artificial intelligence. Xiao obtained her Ph.D. from Columbia University, where she specialized in AI, economics, and public policy. Her dissertation investigated benchmarking for large language models, which is crucial in understanding and improving AI performance in various applications. She has positions at OpenAI and Epoch AI and has been a partner at Leonis for over 3 years now. One of my favorite new AI Newsletters on Substack in 2025.

Our Top Guides

1. How to use NotebookLM for personalized knowledge synthesis

2. How to use Perplexity in your daily workflow 👀

3. Your AI Assistant Kit: 12 Practical Tools by Wonder Tools

70. Bartek Pucek

Bartek Pucek

Building and backing the future - a founder and angel investor's take on tech and business.

• Bartek Pucek is recognized as both a tech entrepreneur and an angel investor. His investment focus primarily centers on early-stage companies that are pushing the boundaries of technological progress, particularly in areas like AI, infrastructure, and deep tech. As such his Newsletter is fairly interesting concerning the bleeding edge of technology and AI. ElevenLabs is perhaps on of the most well-known startups he has invested in early. He’s had a weekly Newsletter since 2018.

71. Decision Intelligence

Decision Intelligence

Data-driven decision-making, plus a dash of humor

By Cassie Kozyrkov

• Cassie Kozyrkov is best known for her innovative work at Google, where she served as the Chief Decision Scientist. In this role, she was instrumental in founding the discipline of Decision Intelligence, which merges data science, decision theory, and AI to enhance decision-making processes across various domains. She has a huge presence on Youtube, LinkedIn and formerly Medium. She worked at Google for nearly 10 years, primarily as an educator. I think she’s now an influencer, speaker, corporate educator and consultant.

72. Why Try AI

Why Try AI

Hype-free, hands-on AI for non-techies.

By Daniel Nest

• Daniel Nest is an AI enthusiast and blogger known for demystifying artificial intelligence for a broader audience, particularly for those without a technical background.

73. The Pragmatic Optimist

The Pragmatic Optimist

AI, Macro, Stocks & Memes. Helping investors navigate the evolving AI landscape and unlock long-term, high-growth investment opportunities by assessing industry cross-currents, innovation roadmaps and profit cycles.

By Amrita Roy

• Amrita Roy She is talented macro economics, investing and finance writer and analyst. She provides insights into investment opportunities, particularly within the AI value chain. Her work emphasizes connecting technology with broader cultural and economic trends, offering a comprehensive perspective to her readers. She often covers BigTech names including those related to the semiconductor supply chain and AI chip space.

74. The Computist Journal

The Computist Journal

Educational articles, essays, and tutorials on Computer Science research, practice, and education.

By Alejandro Piad Morffis

• Alejandro Piad Morffis shares insights on computer science, AI, and education. He emphasizes the importance of making advanced technological concepts accessible to a broader audience, reflecting his mission of 'democratizing knowledge one post at a time'. Morffis is actively involved in research, teaching, community building and the AI community.

75. Rich on Tech

Rich on Tech

Sharing useful tech news, gadgets, helpful new apps and handy tech tips.

By Rich DeMuro

• While more on gadgets and automation, Rich on Tech does touch on AI on a repeated basis. Rich DeMuro is a prominent tech reporter and radio host, widely recognized for his work in simplifying technology topics for a general audience. Rich DeMuro has covered various aspects of AI, including advancements and applications in day-to-day technology. His discussions often explore how AI impacts various sectors, including personal technology and business. He’s a tech reporter at KTLA-TV in Los Angeles and hosts the Rich on Tech Radio show, syndicated on 350+ radio stations nationwide.

76. High Capacity

High Capacity

Industrial policy, clean technology, EVs, infrastructure, and development, particularly in China and India.

By Kyle Chan

• While Kyle Chan mostly covers China’s industrial policy, EV sector and infrastructure developments as an analyst he’s often talking indirectly and related to China’s AI developments. Kyle Chan is a postdoctoral researcher in the Sociology Department at Princeton University. He is affiliated with several research centers, including the Paul and Marcia Wythes Center on Contemporary China and the M. S. Chadha Center for Global India. His research primarily focuses on industrial policy, clean technology, infrastructure, and development, particularly in China and India.

77. Last Week in AI

Last Week in AI

Weekly text and audio summaries of the most interesting AI news, as well as editorials commenting on recent events

• One of the longest running weekly AI Newsletter on Substack. Related to the website called Skynet Today. It has many of the same co-founders as The Gradient.

78. Futuristic Lawyer

Futuristic Lawyer

Making sense of grey areas between law, IT and ethics.

By Tobias Mark Jensen

• Tobias Mark Jensen writes at the intersection of law, technology, and ethics, with a particular emphasis on artificial intelligence. He hosts a podcast also on Futuristic Lawyer and is based in Denmark, Jensen is known for his work as a tech writer and legal consultant, exploring the complexities that arise at the convergence of law and emerging technologies. His work includes some critiques on how European and democratic values are at odds with some developments in U.S. BigTech and their policies.

79. China Innovation Watch

China Innovation Watch

Empowering decision-makers with real-time, data-rich insights on China’s tech and market innovations. Navigate disruptive trends and strategic shifts with confidence.

By CIW Team

• Yet another Newsletter with China Tech insights that often touches up their AI roll-out and developments. Formerly known as China Internet Watch, they (I don’t know who they are) have rebranded to better reflect our broadened focus. Technically China Internet Watch (CIW) was founded in 2007 by Chen Yidan, Ma Huateng, Xu Chenhua, Zeng Liqing, and Zhang Zhidong.

80. Culpium, by Tim Culpan

Culpium, by Tim Culpan

Culpium: noun [U] — a cure for lack of knowledge, understanding or clarity. *taken by those seeking to improve comprehension of technology, semiconductors, and supply chains especially in Asia. *See your therapist if stupidity persists

• Tim Culpan is a particularly astute semiconductor analyst and investigative journalist who worked for many years for Bloomberg. As an accomplished journalist and commentator specializing in technology, particularly in semiconductors and supply chains. Tim has a notable presence in the tech journalism landscape, focusing on the Asian market and issues related to technology advancements, the semiconductor industry, TSMC, including artificial intelligence related chip coverage.

81. Turing Post

• Formerly involved with The Sequence Newsletter, impossible to mention the AI Newsletter space without talking about Ksenia Se. She started Turing Post aiming to demystify AI by presenting scientifically-backed information with low hype, emphasizing critical perspectives on how AI evolves and is integrated into our lives. The Newsletter is geared more to software engineers and covers some technical and semi-technical topics.

82. Next Big Teng

Next Big Teng

VC @ Bessemer; data-driven reflections on startups, AI/ML trends, and venture investing

By Janelle Teng

• Janelle Teng also comes from a VC perspective. She’s currently serving as a partner at Bessemer Venture Partners. Her investment focus lies particularly in early-stage companies that are innovating within AI/ML and data infrastructure, making significant contributions to the technological landscape. Her long-form reflections and deep dives into startups, venture investing, and AI/ML trends — always backed by data and first principles are super relevant and among my favorites.

83. AI Adopters

AI Adopters

Use AI to deliver results, impress your boss, and grow your career. I simplify the process—you take the credit. Deal?

By Kamil Banc

• Kamil Banc is the Director of Innovation and AI at Kwik Brain, Banc focuses on integrating AI into personal development and learning solutions. He is known for simplifying AI concepts to help organizations and individuals harness its power efficiently, often encouraging businesses to embrace AI for competitive advantage.

84. AI by Hand

AI by Hand ✍️

with Prof. Tom Yeh

By Tom Yeh

• Tom Yeh is an Associate Professor of Computer Science at the University of Colorado Boulder. He specializes in areas related to artificial intelligence and human-computer interaction. His academic journey began with a PhD from the Massachusetts Institute of Technology, where he researched vision-based user interfaces. AI by Hand is known for its stunning infographics and visuals.

85. Decoding ML

Decoding ML

Join for proven content on designing, coding, and deploying production-grade AI, GenAI, and information retrieval systems—built with ML systems, MLE, and MLOps best practices. Every week, straight to your inbox.

By Paul Iusztin

• Paul Iusztin is an author and specializes in various applied domains within AI, including generative AI, computer vision, and MLOps. His comprehensive skill set supports the entire lifecycle of machine learning projects, from conception to deployment, ensuring that they meet industry standards for performance and reliability. His Newsletter is a bit more technical. His visual infographics are stunning and useful.

86. Enterprise AI Trends

Enterprise AI Trends

"Enterprise AI Trends" is a publication about mainly three topics: 1) enterprise AI product and industry trends, 2) the challenges of AI adoption in enterprises and among consumers, and 3) the lessons learned selling AI in the field.

By John Hwang

• Previously, John Hwang served as a Generative AI Architect at Amazon Web Services (AWS), where he contributed significantly to the development of AI solutions and strategies, including products related to voice user interfaces (VUIs) during his tenure as a product manager for Alexa. He discusses crucial topics such as AI trends, product development strategies, and the overall landscape of AI technologies. He was at Amazon for around six years in total.

87. Platforms, AI, and the Economics of BigTech

Platforms, AI, and the Economics of BigTech

Your guide to strategy and policy in the age of platform ecosystems, BigTech dominance, and AI.

By Sangeet Paul Choudary

• Sangeet Paul Choudary is an author, business scholar, entrepreneur, and advisor who has made significant contributions to understanding how digital platforms operate, particularly in relation to AI and BigTech. His latest book is called Reshuffle.

88. Chamath Palihapitiya

Chamath Palihapitiya

I make bets on disruptive ideas, technology, and people. Subscribe to learn with me.

• Chamath Palihapitiya is a prominent billionaire Silicon Valley venture capitalist, engineer, entrepreneur and tech influencer. He’s a member of the All-In Podcast and is famous on apps like X. Most of his insights are not original but he has a roundup of what he has read. He’s part of the Facebook mafia. Palihapitiya was born in Sri Lanka and later moved to Canada, where he pursued his education in engineering at the University of Waterloo. He gained early career experience at AIM (now part of AOL) and then at Facebook. He’s also been involved in shady SPACs. Palihapitiya's investment strategy often emphasizes identifying innovative companies at early stages, which he believes align with broader societal shifts. There are times when some of his ideas overlap with AI. at least in the broader VC and technology trends sense.

89. Hyperdimensional 🏛️

Hyperdimensional

A newsletter about emerging technology and the future of governance.

By Dean W. Ball

• Dean W. Ball serves as a Research Fellow in the Artificial Intelligence & Progress Project at George Mason University's Mercatus Center. His work primarily focuses on the implications of AI technology and emerging technologies on society and governance. He leads one of the more original and insightful AI policy and governance based Newsletter. As new technology emerges, lawmakers face the challenge of crafting public policy that navigates this dynamic landscape. His work as a policy scholar is dedicated to developing a forward-looking vision for governance that remains rooted in the founding principles of America. He actively explores the intersection of history, political theory, policy, and technology, aiming to guide policymakers, business leaders, and academics toward a comprehensive understanding of how these elements converge to shape effective governance. Check out his new podcast.

90. Chipstrat 📱

Chipstrat

Chipstrat is where semiconductors, AI, and strategy collide.

By Austin Lyons

• Austin Lyons combines his technical expertise with a deep understanding of market dynamics to analyze trends in AI and semiconductors. I consider him a fairly interesting tech and automation analyst. With a graduate degree in Electrical Engineering and notable career experience, he has some deep insights to share.

91. LLM Watch 👀

LLM Watch

Weekly newsletter about the most important AI research with a focus on Large Language Models (LLMs). Get insight on the cutting edge of AI from a human perspective.

By Pascal Biese

• Vienna based Pascal Biese is a technical ML expert that introduces AI news and model events to a broader audience with a great mix of perspectives. His contributions on Large Language Models (LLMs), Natural Language Processing (NLP), and general advancements in AI technology are astounding and very clear and easy to follow. He distills complex technical topics into summaries that respects your time.

92. Nate Jones’ Substack 💥

Nate’s Substack

Daily newsletters from the cutting edge of AI, including breaking news, strategy, product breakdowns, and thought pieces.

• Seattle based Nate Jones has a wealth of experience, having worked in product management at large-scale technology companies, including Amazon, where he focused on crafting AI-driven products. Here is yet another Product Newsletter that increasingly intersects with Generative AI topics. He has also been actively involved in sharing knowledge on AI through various platforms, including YouTube channels dedicated to AI news and strategies, where he has amassed a considerable following.

93. The Great Progression 2025 to 2050

The Great Progression: 2025-2050

A grand narrative of our historic opportunity to harness AI & other transformative technologies to drive progress, reinvent America & make a much better world. A positive reframe of what's coming via essays, interviews & gatherings culminating in a book.

By Peter Leyden

• Peter Leyden is a prominent futurist and thought leader focusing on artificial intelligence (AI) and transformative technologies. He is widely recognized for his insights into how these technologies impact society, the economy, and the environment. He’s an author, keynote speaker and Founder of Reinvent Futures for foresight advising.

94. Roots of Progress ✨

The Roots of Progress

The history of technology and the philosophy of progress—a digest of posts from rootsofprogress.org

By Jason Crawford

• Jason Crawford is a prominent thought leader in the field of progress studies, focusing on the history and philosophy of technology and economic growth. He is the founder of the Roots of Progress, an organization dedicated to advancing the understanding of progress and innovation in society. Jason’s extensive background in technology, having spent 18 years as a software engineer, engineering manager, and startup founder informs his insights into the role of technological advancements in shaping civilization and addressing existential challenges, including those posed by AI. History of Technology writers therefore bring a lot of unique analysis to the Generative AI movement on innovation and the future of work.

95. The Future of Being Human 🔮

The Future of Being Human

Reflections on transformative technologies, society, and the future. By Andrew Maynard, Professor of Advanced Technology Transitions at Arizona State University. Please subscribe for regular updates.

By Andrew Maynard

• Andrew Maynard’s work often focuses on how innovations can reshape human experiences and societal structures, emphasizing the importance of responsible and ethical usage of technology. He’s a professor of Advanced Technology Transitions at Arizona State University and Director of the ASU Future of Being Human initiative. Beyond his academic role, he is also an author and hosts the podcast "Modem Futura," where he discusses themes related to AI and futuristic scenarios about humanity's relationship with technology.

96. Learning From Examples ⌛

Learning From Examples

A history newsletter about the future

By Harry Law

• Harry Law is PhD candidate at the University of Cambridge. His reflections on the historical background of AI are refreshing to say the least. His research is primarily focused on the history, philosophy, and governance of artificial intelligence, which he studies within the Department of History and Philosophy of Science at the university. Law is also a Postgraduate Fellow at the Leverhulme Centre for the Future of Intelligence, where he engages in significant research related to the ethical and policy implications of AI technologies. Previously, he worked as a researcher at Google DeepMind, contributing to ethics and policy research in AI.

97. The Absent-Minded Professor

The Absent-Minded Professor

Technology, education, and human flourishing. All through the lens of a prototyping mindset.

By Josh Brake

• Josh Brake is a force to be reckoned with at the intersection of AI and education. His work is dedicated to cultivating the next generation of humanity-centered engineers. His work focuses on incorporating AI into educational paradigms and exploring its potential to enhance human flourishing. He’s a very coherent critic of Generative AI’s impact and dangerous on education and young scholars. Brake emphasizes the importance of developing a Prototyping Mindset, encouraging innovation and reflection in learning processes. He actively engages with topics related to AI's implications in education and technology, often advocating for a balanced approach that considers both the benefits and risks associated with AI implementation.

98. High ROI Data Science

High ROI Data Science

Gain the upper hand and see around corners with leading-edge AI content. Written by Vin Vashishta. Trusted by Founders and Top Tech Companies. AI strategy, products, and technical deep-dives.

By Vin Vashishta

• While this list has tried to stay away from the Software Engineering and Data Science space as it’s not a list directly for engineering, some writers touch on AI on a repeated basis that has qualities of an AI Newsletter and Vin is certainly such a case. Vin Vashishta is a prominent voice in AI and data science, recognized for his contributions as an entrepreneur, strategist, and educator. He is the founder of V-Squared, a consultancy that focuses on leveraging data and AI to create monetizable business strategies. Based out of Reno Nevada, Vin is a widely read author, a Gartner Ambassador and an important industry expert.

99. Adjacent Possible 🌈

Adjacent Possible

A newsletter from author Steven Johnson exploring where good ideas come from—and how to keep them from turning against us.

By Steven Johnson

• Steven Johnson is a prominent figure in the intersection of technology, writing, and artificial intelligence. He serves as the Editorial Director at Google Labs, where he plays a significant role in advancing AI technologies, particularly in writing, research and multimodal Generative tools. Many of his recent articles feel a bit like PR for the NotebookLM his product, a project he is considerably invested in. But he’s still a fascinating author and thinker around innovation. In his role at Google Labs, Johnson has been pivotal in the development of NotebookLM, a free and paid AI-powered research, synthetic podcast and writing tool. A prolific author, he has authored 14 books, focusing on a variety of topics including science, technology, and innovation.

100. Middle East AI News 🐪

Middle East AI News

Middle East AI News provides news, comment and insight on how artificial intelligence, innovation and new policymaking are transforming the Middle East

By Carrington Malin

• Pretty much the best source for AI breaking news in the Middle East region including AI infrastructure, investments and geopolitical impacts. Carrington Malin is a prominent entrepreneur and marketing consultant specializing in artificial intelligence (AI) and emerging technologies. He operates primarily in the Middle East, particularly in Dubai, where he advises businesses and organizations on integrating AI into their marketing strategies and communications. His geographical coverage to me is exceptionally holistic with AI news, industry trends, policy updates, investment deals and analysis for a fairly pivotal region with a lot of resources.

101. Fractal Computing Substack 🧩

Fractal Computing Substack

Fractal is a sustainable computing stack, running at quantum speed, on current hardware, enabling any application to run without a data center at half its current cost and 1,000 more speed.

By Jay Valentine

• More or less a criminally underrated Newsletter, Jay Valentine is in recent times an edgy writer expressing some more critical but highly informed perspectives on existing technologies and their applications, highlighting a belief that many organizations are still utilizing outdated systems while missing out on the advantages of newer, faster technologies.

He is recognized for leveraging AI to enhance organizational efficiency and drive business growth. Notably, he emphasizes the potential of AI and machine learning solutions to transform various industries, as highlighted by his investments in innovative companies focusing on these technologies. His educational background includes studies in international economics, statistics, and computer science at Georgetown University, equipping him with a robust foundation to operate at the intersection of technology and business.

102. AI Community Learning Program 🛠️

AI Community Learning Program

Join a trusted AI learning community with members from Microsoft, Google, Meta, Amazon, and top AI startups. Sign up for exclusive insights and events to redefine work and learning with a global, hands-on community powered by Microsoft Teams!

By Shyvee Shi

• Shyvee Shi is an accomplished product leader specializing in AI and product management. Currently, she serves as a Product Lead at Microsoft, where she leverages her expertise in user psychology, AI, and creativity to foster growth and enhance community engagement. She’s a great resource for product managers at the intersection of AI that I’ve been following for years. Her experience at LinkedIn as a LinkedIn Learning instructor and PMl lead meant she got to interview some of the best people in product management at the intersection of AI for a very long while. Shyvee has become noted for her forward-thinking approach and innovative strategies, particularly in the realm of generative AI. She has expressed that by 2027, she anticipates Integrative AI will revolutionize industries by fostering more intelligent, adaptive, intuitive, and collaborative solutions.

103. Untapping Product Teams 💡

Untrapping Product Teams

Weekly insights on overcoming challenges product people often struggle with. You'll learn from reality, not fantasy! Join us to level up your game!

By David Pereira

• David Pereira is a hugely helpful Product management educator, author and leader. He’s yet another great Product person who touches upon Generative AI. Product coach, book author, keynote speaker he has real insight, flair and breaks down things into simple and easy reading. From Brazil to Germany, David bring a lifetime of experience into what he does. His product strategy guides and insights into how Generative AI is changing the product manager field are extremely high level.

104. GSV: AI & Education 📈

GSV: AI & Education

Claire Zau's Newsletter on AI and Education

By Claire Zau

• Sometimes you just want to read a good AI news rundown. Claire Zau serves as a Vice President at GSV Ventures, where she focuses on investments in edtech companies that leverage AI technologies. Notably, she is recognized as the youngest investor to become a partner at GSV Ventures. This distinction highlights her significant influence and expertise in the venture capital space, particularly in areas related to AI and its application in education. Her round-ups are fairly broad and useful.

105. Guide to AI 📊

Guide to AI

The monthly newsletter analysing the most important AI technology, research, geopolitics and startups.

By Nathan Benaich

• As far as AI Newsletters from VC goes, few have done so much as Nathan Benaich. Nathan has become a towering figure in the UK AI space, as a prominent investor and entrepreneur in the field of artificial intelligence. He is the Founder and General Partner of Air Street Capital, a venture capital firm that specializes in investing in AI-first companies. His approach revolves around identifying and supporting startups that harness AI technology to create innovative solutions across various industries. His annual State of AI reports are so epic. His Newsletter comes of course, highly recommended.

106. Sol’s Newsletter 💼

Sol's Newsletter

By Sol Rashidi

• Sol Rashidi holds ten patents and is a best-selling author, which underscores her expertise in the domain of AI. She is deeply involved in AI for enterprise and startups with her work at Amazon. She’s a keynote speaker and having served in various high-level positions, Sol was notably the first-ever Chief Data & AI Officer appointed in 2016. Sol has built a reputation as a tech executive with a business acumen who can combine her technical depth with story telling abilities to simplify complex ideas, outline a clear strategic vision, and follow through with delivery excellence.

107. Sinead Bovell 🎀

Sinead Bovell

WAYE Founder

• Full disclosure, I mostly like Sinead’s micro videos. An Instagram influencer, Sinead Bovell is a recognized futurist and the founder of WAYE, a tech education organization aimed at preparing individuals and businesses for future technological advancements. Her work focuses on emerging technologies, particularly in the field of artificial intelligence. Sinead Bovell advises organizations on how to navigate the complexities of technology in the modern world. She’s an AI influencer in the sense she likes to appear on TV and on popular shows. Sinead is thus an active speaker and contributor in media discussions concerning AI and would make a good keynote speaker for some audiences.

108. Teaching computers to talk 💬

Teaching computers how to talk

Stay in the loop with in-depth articles at the intersection of AI, language, and philosophy. Subscribe for free.

By Jurgen Gravestein

• Jurgen Gravestein is a consultant at the Conversation Design Institute, where he has contributed significantly to the development and improvement of conversational AI technologies. As an essayist he is an astute and witty Op-Ed writer on various trends in Generative AI. His writings often delve into the complexities of AI, the nuances of conversation design, and the broader implications of artificial intelligence on society. He’s highly readable and often details very salient topics to an AI enthusiast audience.

109. The Generative Generation

The Generative Generation

A data scientist's guide to Generative AI. Weekly insights on tools, trends, and research. Dive into 'The Generative Generation' and a new era of data science.

By Harpreet Sahota

• Based out of Winnipeg Canada, Harpreet Sahota is an influential professional in the AI and data science fields, renowned for his work as a Hacker-in-Residence at Voxel51. His role involves hacking on emerging AI technologies, where he transforms innovative ideas into functional prototypes and engaging demos, showcasing advancements in AI applications. He’s an author and a respected AI/ML engineer active in course building around his domain. He’s one of the rare people I know who overlaps seamlessly between the software engineering folk, datascience types and AI technologists. Sahota's technical acumen is complemented by his focus on community building and mentorship.

110. Synthedia

Synthedia

Join over 3,500 of the most erudite tech observers and follow the business and technology of Generative AI, Synthetic Media, LLMs, ChatGPT, DALL-E, Stable Diffusion, PaLM/Gemini, virtual humans/digital people, voice clones, deepfakes, and much more.

By Bret Kinsella

• Bret Kinsella is the founder, CEO, and research director of Voicebot.ai, a leading source for research, data, analysis, and news related to voice technology and AI. His expertise has established him as an influential analyst and journalist in the industry. Has has a deep background in digital media, business strategy, technology, and startup growth, among related domains.

111. AI Simplified for Leaders

AI Simplified for Leaders

A newsletter on AI insights for business leaders, board members, and investors. Get concise, actionable tools and news to elevate your strategy and decision-making.

By Joyce Li

• Joyce Li has nearly two decades of experience as a professional investor and co-founder of two businesses, she also explores AI and finance's nexus, focusing on strategic finance, board governance, and AI investing. Her Newsletter is among the most useful I’ve read for covering points not covered elsewhere filled with unique insights. She holds the title of CEO and Chief AI Strategist at Averanda Partners, where she plays a key role in advising business leaders and board members on effective AI strategies and governance practices. Her expertise lies in leveraging AI to enhance business decision-making and operational efficiency. Joyce’s focus is grounded in the implications of AI on corporate governance and the broader business landscape. Extremely humble, I have a huge amount of respect for Joyce.

113. Industrial Intelligence

Industrial Intelligence

What happens when the price of Intelligence falls to zero?

By Nina Schick

• Nina’s micro videos on AI are also very admirable. Nina Schick is the Founder and CEO of Tamang Ventures, a company that focuses on leveraging AI to address key challenges in society. Schick has gained international acclaim for her insights into the implications of generative AI and disinformation. She is also known for insights in the context of geopolitics and the impact of technology on global power dynamics. Her work emphasizes the potential of AI not only as a transformative technology but also as a catalyst for reshaping how information is disseminated and perceived globally. I would best characterize her as an entrepreneur and author with a keen sense of macro dynamics involved in AI’s impact on the world, both business and society at large.

114. Concurrent 🎭

Concurrent

Concurrent explores the parallel and divergent tech/cultural currents flowing through China and the world.

By afra

• Afra Wang is an aspiring sinologist and an essayist, analyst and researcher on Chinese history, companies, AI and related technological and cultural trends. She serves as a freelance writer and podcaster, focusing significantly on the implications of AI in various domains and has a flair for nuanced storytelling and narratives around especially, themes around Chinese trends and nationalism. Having pursued her Master's degree at Columbia University and the London School of Economics. Her academic background enriches her insights into the socio-political aspects of technology and AI. She’s a budding writer on Substack and the very definition of an emerging writer in the best sorts of ways.

115. Dr Phil's Newsletter, Powered by DOMS™️ AI

Dr Phil's Newsletter, Powered by DOMS™️ AI

Connecting the science of learning & AI with the art of learning experience design.

By Dr Philippa Hardman

• Dr. Philippa Hardman has over 20 years of experience, she specializes in utilizing AI to enhance learning design and create more effective educational experiences. Dr. Hardman co-founded a learning design framework known as DOMS™️, which stands for Design, Optimize, Measure, and Share. This framework leverages AI to facilitate improved outcomes in learning by offering insights that help educators tailor their approaches. She has spent 20+ years researching online & hybrid course design at universities like Cambridge & Harvard so her expertise at integrating AI into learning design is super specialized and absurdly well-focused.

116. Byte-Sized History

Byte-Sized History

The origin stories of the technologies and innovations that shape our world today.

By J. Michael Wahlen

• J. Michael has just updated that he will do a series on the history of artificial intelligence. J. Michael Wahlen is a management consultant and a prolific writer who focuses on the intersection of technology and business strategies. He has contributed significantly to discussions around artificial intelligence, particularly in how it influences growth strategies for corporations. Wahlen utilizes data analytics to help Fortune 500 companies adapt and innovate in their respective industries, which is crucial in the increasingly digital landscape. In his essay "TSMC: The Quiet Titan," Wahlen discusses the role of Taiwan Semiconductor Manufacturing Company in the AI sector, illustrating how semiconductor technology is foundational for AI applications.

117. Deep Learning With The Wolf 🤖

Deep Learning With The Wolf

I'm a freelance writer who loves to research A.I. and share what I've learned.

By Diana Wolf Torres

• Diana Wolf Torres is a prominent freelance writer and journalist who focuses on artificial intelligence, robotics, Nvidia and technology topics. She’s in recent times my top guest contributor in robotics. She is known for exploring the future implications of AI, specifically how machines can drive, reason, and make decisions independently. She serves as the editor of the newsletter "Deep Learning with the Wolf," where she shares insights and analyses about the advancements in AI technology.

118. Joe’s Journal 🎬

Joe's Journal

Writing and RECording what’s on my mind, regularly: media, technology, creativity, the end of civilization as we know it, credible reasons for optimism, etc.. 🔴

By Joseph Gordon-Levitt

• Joseph Gorden-Levitt is a prominent actor and filmmaker who has become a vocal figure in discussions surrounding artificial intelligence, particularly its implications for creative industries, including film and television. Recently his critiques of BigTech are also very enjoyable reading. Gordon-Levitt has expressed concerns regarding how AI companies utilize content from films and television to develop their technologies without adequately compensating the original creators, such as actors and writers (the copyright issue).

119. Read Max 🏙️

Read Max

Explaining the weird new future, one newsletter at a time. Subscribe for a twice weekly delivery of internet culture, mega-platform grotesquerie, crypto conspiracies, deep forum lore, fringe politics, and other artifacts of what's to come.

By Max Read

• While not directly an AI writer, Max sometimes talks about it in passing. Max Read is a freelance journalist and commentator who has made significant contributions to discussions surrounding AI, particularly its implications in creative writing and content generation. His work often addresses the cultural and social ramifications of generative AI technologies, such as ChatGPT. Read has also highlighted the phenomenon of "AI Slop," describing it as low-quality, often nonsensical content generated by AI systems that floods the internet. So maybe on closer inspection, he’s more active talking about AI’s impact on society and culture than I thought.

120. Digital Native 📲

Digital Native

Weekly writing about how people and technology intersect

By Rex Woodbury

• Digital Native is also not primarily an AI Newsletter. Rex Woodbury is is the Founder and Managing Partner of Daybreak Ventures, an early-stage venture capital firm that focuses on investing in technology startups, particularly those that leverage AI and other innovative technologies to create accessible solutions. He has a strong interest in understanding human behavior and how technology can be aligned with consumer needs, echoing a fundamental belief that while technology evolves, people’s needs remain relatively constant. Some of his macro takes are worth reading. Many partners in VCs are uniquely positioned to understand layers and contexts of AI that some of us miss.

121. The Future Normal 🔮

The Future Normal

Understand what's next. Dissecting today's innovations in order to uncover tomorrow's opportunities.

By Henry Coutinho-Mason

• Based in London, Henry Coutinho-Mason is recognized as a futuristic thinker and an innovation strategist, focusing on how AI can reshape industries and influence societal progress. Keynote speaker, author, co-founder and innovation specialist. He is known for his role as a keynote speaker, where he has delivered over 150 keynote speeches across more than 30 countries, discussing critical topics related to leadership, AI, and innovation. I consider him a legit Futurist (kind of a rare thing) who makes valuable contributions to the emerging tech narrative.

122. @Andrewchen 🕹️

@andrewchen

Venture capital in tech, entertainment, and AI

By Andrew Chen

• Andrew Chen currently is serving as a General Partner at Andreessen Horowitz, a leading venture capital firm based in Silicon Valley. He focuses on investing in early-stage consumer startups with a specific interest in marketplaces, consumer technologies, and growth strategies. He’s only an occasional writer on his Newsletter, sometimes briefly discussing AI. Chen is an author with an extensive background in marketing and growth strategy, especially for early stage startups. After three years at Uber he wrote a book called The Cold Start Problem. After nearly 7 years at a16z he now runs something called a16z Speedrun. He’s probably written in the area of 700 essays by now. He’s been involved in the intersection of gaming and tech in particular.

123. Simon Willison’s Newsletter ✍🏻

Simon Willison’s Newsletter

AI, LLMs, web engineering, open source, data science, Datasette, SQLite, Python and more

• This Newsletter would be ranked a lot higher, if this was his go-to actual blog, but it’s just the Email spin-off version. I know, I know, it’s hard to quit your actual blog. Simon Willison has a background as a developer and has made significant contributions to several projects in the tech industry, including being one of the co-creators of the Django web framework. His expertise spans across various domains, including web development, data journalism, and the application of AI and Large Language Models (LLMs) in software development. His coverage of AI developments is fairly good and is prolific mostly geared to software engineers. He actively writes about AI on his blog, where he discusses the implications of AI technologies and shares insights into how he uses LLMs to assist in programming tasks. He feels like one of those old school bloggers who is really into AI.

124. Gradient Flow 🌌

Gradient Flow

Put data, machine learning, and AI to work.

By Ben Lorica 罗瑞卡

• Ben Lorica 罗瑞卡 shares insights on AI trends and strategies, often addressing critical topics such as generative AI, data strategies, and AI governance. He is a notable organizer of tech and AI events. Whether it’s dissecting an ML paper or commenting on the latest AI news, his insights are grounded and he has a keen eye for the critical issues. His Podcast is called The Data Exchange which you can also find on the Gradient Flow YouTube channel. With extensive involvement in organizing major AI-related events such as the AI Conference, the NLP Summit, and the Ray Summit, Lorica is influential in shaping discussions on AI platforms and data strategy. Easily one of the most under-appreciated AI voices that I follow.

125. TechSoda

TechSoda

Stimulating, Original, Dynamic, and Accessible Tech News and Insights covering Semiconductors, Optical, Digital, and AI Industries! © 2025 Judy Lin 林昭儀, All Rights Reserved

By Judy Lin 林昭儀

• Judy Lin 林昭儀 is what I consider a TSMC expert with a grounding in all things Taiwan Tech. She has has been involved in significant discussions and developments in the AI sector, especially related to advancements and innovations from East Asian, notably Taiwan and China, where she has highlighted various AI technologies and their implications on global dynamic. I think her special area of focus is mostly around TSMC and the semiconductor supply chain and hardware aspects as well as some geopolitical concerns of TSMC’s relationship with the United States.

126. Language Models & Co.

Language Models & Co.

Large language models, their internals, and applications.

By Jay Alammar

• Jay Alammar is particularly known for his work on visualizing and explaining complex machine learning concepts. A published author he has been at Cohere for nearly four years. He’s a legit LLM educator with a decent sized YouTube on the topic. Highly recommended for software engineers wanting to learn more about ML, LLMs and AI in general.

127. AlgoMaster Newsletter

AlgoMaster Newsletter

Master Coding and System Design Interviews. Level up your Software Engineering career. Subscribe and get a FREE System Design Interview Handbook in your inbox.

By Ashish Pratap Singh

• Ashish Pratap Singh is a Software Engineer with a significant background in various domains of technology, including full-stack development, machine learning, backend, and data engineering. He boasts over 8 years of experience in the software development space. He shares lessons, strategies, insights and resources that have helped him in my Software Engineering career. He’s also a great resource for system design. He’s based in Bengaluru, India. So it’s great to have an Indian based Newsletter featured on this list.

128. Society’s Backend

Society's Backend

Machine learning for software engineers: learn, build, and understand AI.

By Logan Thorneloe

• Logan Thorneloe is currently employed at Google, where he focuses on machine learning infrastructure. His role involves teaching software engineers how to effectively implement AI solutions. This unique position bridges practical application with academic knowledge, making him a valuable asset in the tech community. His Newsletter is also I think geared for software engineers and those learning about ML. Society’s Backend aims to demystify machine learning for practitioners in the field, fostering a deeper understanding of AI's capabilities and limitations.

129. High Growth Engineer

High Growth Engineer

Grow faster in your software engineering career with actionable tips you can use right away.

By Jordan Cutler

• Joran Cutler runs one of the top software engineering Newsletters. Recently he has started to write more articles related to AI. Jordan is currently a Senior Software Engineer at Pinterest, where he applies his expertise in developing innovative features, including those that leverage artificial intelligence. Recently, Joran Cutler highlighted his efficiency in utilizing AI to build a feature in just 20 minutes, a task that would typically take two days to complete. This showcases his advocacy for incorporating AI tools in streamlining workflow and enhancing productivity within development processes. He’s also built courses on the site Maven.

130. The GenAI Collective Community Newsletter

The GenAI Collective Community Newsletter

Highlighting some of the top thoughts and insights in AI – brought to you directly by your fellow community members!

• Eric Fett is a Vice President at NGP Capital, where he plays a significant role in the investment landscape, particularly focusing on sectors related to artificial intelligence (AI), cybersecurity, and industrial technology. His work involves identifying and investing in innovative early-stage companies that leverage AI technologies to drive advancements across various industries. Before his VC life he was at Accenture. As a Co-founder of this group, it’s one of the US’s largest AI communities with over 25,000+ founders, researchers, operators, and investors built around a shared curiosity for AI. Through incredible in-person events and vibrant online forums, members leverage their diverse perspectives and innovative minds to foster meaningful relationships, solve challenging problems, and define the future of AI.

131. AI Policy Perspectives

AI Policy Perspectives

A regular look at AI policy, governance, and more. Organised by members of Google DeepMind’s policy team and featuring contributions from a range of people, all in a personal capacity.

• This publication is organized by members of Google’s DeepMind policy team, but is overall a good resource. Conor Griffin is currently serving as an AI Policy Researcher at Google DeepMind, based in London. With five years at Google DeepMind, previously Conor was at The Economist Intelligence Unit (EIU) for a decade. Given that Google’s AI principles are often changed on the fly to suit their business interests, I’m fairly skeptical about anything policy related from that team.

132. The Elysian

The Elysian

A writers collective imagining a better future. Join us for collaborative media projects exploring the future of nation states, capitalism, and humanity.

By Elle Griffin

Elle Griffin rarely mentions AI by name, but her futuristic Newsletter is an exploration on the future and alternatives. Elle Griffin explores the intersections of artificial intelligence indirectly, with an emphasis on science-fiction, utopian ideals, and societal evolution. As the founder of The Elysian, the newsletter in its latest incarnation appears to be focused on imagining a better future, including themes and motifs of technology, morality, and human values. The role of the United States culture itself appears to have become an evolving niche in her search for Utopia. Griffin is also an avid student of utopian novels, examining how contemporary thinkers are reinterpreting these ideals in light of modern technological advancements. Her exploration involves not only theoretical discussions but also creative endeavors, as she engages in writing utopian fiction. So we need to take her work as an exercise in creative mind-bending hypotheticals which is frankly fairly enjoyable as its own cause.

133. The AI Journal

The AI Journal

Your weekly fresh journal for AI and Automation

• Tom Allen started The AI Journal in 2020. Allen has a background in marketing and AI. Allen emphasizes that he does not have a formal background in journalism or publishing; his insights are cultivated from personal exploration and engagement with the AI community.

134. Upstarts

Upstarts Media

Startup news starts here. The Upstarts newsletter provides in-depth reporting and analysis on the startup ecosystem, from inception through IPO. Founded by veteran tech reporter Alex Konrad.

By Alex Konrad

• Based in New York, Alex Konrad is a journalist (formerly at Forbes) and editor recognized for his work in the technology sector, particularly focusing on startups and venture capital. He recently founded and serves as the editor for Upstarts Media, a tech publication that emphasizes the startup ecosystem. Many of these startups are likely to be AI related. This is a new publication but has risen the paid leaderboards ranks very quickly. He was at Forbes for 12 years and before that at Fortune for 2.5.

135. satellite-image-deep-learning

satellite-image-deep-learning

Newsletter on deep learning with satellite & aerial imagery

By Robin Cole

• Robin Cole holds a PhD and is affiliated with EarthDaily Analytics, where he contributes to various research initiatives aimed at optimizing the use of satellite data for environmental and societal benefit. His academic background includes notable research, particularly from the University of Cambridge, which adds to his credibility in the field. His pioneering Newsletter was a trailblazer for those interested in deep learning with satellite & aerial imagery which has many applications. He’s a Full stack data scientist tackling the world’s toughest challenges with AI & ML applied to satellite & aerial imagery and I have huge respect for Robin. His Newsletter is currently interview/podcast heavy.

136. Into AI

Into AI

Explore Artificial Intelligence from the ground up

By Dr. Ashish Bamania

• Ashish Bamania is recognized for his ability to simplify complex technological concepts and make them accessible to a broader audience. His guides are fairly refreshing here. Based out of London he’s been a full-stack Engineer who is self employed for quite a few years. He breaks down complicated concepts in AI and Quantum in a number of different publications.

137. Semicon Alpha

• William (“Liam”) Marin Keating is based in Hong Kong, and has established himself as an influential figure in the semiconductor industry, combining his extensive experience with a focus on innovation in technology. With over 30 years in the sector, he has played significant roles in various capacities, including a notable tenure as a senior executive at Intel Corporation for 22 years. Keating is actively engaged in analyzing market trends and contributing insights related to semiconductors through his platform, Semicon Alpha which touches on the AI industry.

138 Transformer

Transformer

Your weekly briefing of what matters in AI and AI policy. Read by thousands of AI professionals in government, industry, and public affairs.

By Shakeel Hashim

• Shakeel Hashim serves as the Grants Director at the Tarbell Fellowship, where he focuses on supporting initiatives that promote high-quality AI journalism. Hashim has a diverse background in journalism and communications. He has previously worked as a journalist for renowned media organizations, including The Economist, Protocol, and Finimize. As far as AI policy and roundups Newsletters go, this is a good one. Hashim often explores the challenges faced by AI journalism, especially regarding resource constraints and the disconnect between how journalists and AI researchers perceive various issues.

139. MarTech AI

MarTech AI

I'm bridging the gap between marketing and AI.

By Charlie Hills

• There’s a weird gap in Newsletters on marketing at the intersection of Generative AI. Charlie Hills is recognized as the founder of Cognified, a company that uses AI-driven strategies to enhance marketing efforts. Hills has gained notable attention for his expertise in leveraging AI technologies to create engaging content across various platforms, including social media. His work emphasizes the importance of AI in content creation, where he explores ways to streamline workflows and generate impactful ideas quickly. Growth hackers using AI to be more productive are super interesting. Charlie is kind of a pioneer.

140. Era of Research Bots

Era of the Research Bots 🤖

A newsletter about cutting-edge of AI in Scientific Research. I test gazillion AI research tools, and share the ones truly worth your time - no BS, trust me! Get bonus curation of (actually) useful AI tool guides & lots of other freebies when you join.

By Razia Aliani

• Based in Atlanta, Razia Aliani is in a super interesting niche. She is recognized as a top epidemiologist and systematic reviewer, utilizing AI technologies to enhance research methodologies and outcomes. Her work focuses on integrating AI tools into various stages of health research processes, making her a leading voice in this emerging field. She’s a bit of a LinkedIn influencer too, as she has developed methodologies that leverage AI to improve the efficiency and effectiveness of literature searches, mapping, and synthesis in research projects. Aliani is often regarded as an expert for those new to academic applications of AI as well.

141. Future-Proof Your Career with AI

Future-Proof Your Career with AI

A break down of the most important developments in AI for busy professionals.

By Khe Hy

• Khe Hy also known as Khemaridh Hy, is a notable figure who has made significant strides in the field of artificial intelligence and digital content creation. He is the founder of RadReads, a platform that focuses on personal development and productivity, leveraging storytelling and actionable insights. His Newsletter has tons of guides and useful applications of Gen AI. I’m sucker for that sort of applied and actionable sort of content. With a background in finance, Khe Hy worked on Wall Street for 15 years, achieving a high position as one of the youngest Managing Directors. As far as I can tell, Khe Hy's work in AI is largely centered around its application in productivity and personal development.

142. The AI Edventure

The AI Edventure

A newsletter about the intersection between Artificial Intelligence and education.

By Jason Gulya

• Based in New York, Jason Gulya is a prominent educator and consultant specializing in the intersection of artificial intelligence and education. He is currently a Professor of English at Berkeley College, where he is actively involved in several initiatives related to AI in academic settings. He has gained recognition as an AI consultant, helping colleges develop curricula that leverage AI technologies while maintaining a strong emphasis on the human element in education. Some of his criticism really interests me. For example, his focus on collaboration and community-building in educational settings aims to address the potential isolation that can arise from AI-driven personalization.

143. signüll vs. noise

signüll vs. noise

this is where i'll post long form stuff as an extension of my x account (x.com/signulll)

• This is a mysterious new publication and I’m not aware of who is the author. They said on an X Tweet: “this account is strictly for analyzing the incredibly rapid changes in culture at the intersection of hyper capitalism & proliferation of tech at scale—we are likely only at the beginnings of the profound implications of both on macro & micro aspects of society.” I noticed this Newsletter was trending. The content feels like extended X Twitter threads. The primary topic appears to be analyzing the rapid cultural changes at the intersection of hyper-capitalism and technology proliferation.

144. Dr. Robert Castellano's Semiconductor Deep Dive Newsletter

Dr. Robert Castellano's Semiconductor Deep Dive Newsletter

With 39 years of experience in analyzing the semiconductor industry, I have established an extensive knowledgebase of companies and the sectors they compete, including the size, growth, end applications, and competitive market share of all participants.

• One of the more serious Semiconductor Newsletters among many news ones, Robert Castellano is an experienced figure in the semiconductor and technology sectors, particularly known for his analysis and insights into the semiconductor markets, which are integral to the advancement of artificial intelligence. He has dedicated 38 years to analyzing the semiconductor industry and is currently involved in managing the investing group Semiconductor Deep Dive at Seeking Alpha.

145. Thoughts From The DataFront

Thoughts From The DataFront

Exploring how tech shapes tomorrow - made simple for today

By Max Koven

• Max (Maxwell) Koven works at RBC in Toronto. A bank that recently sent me a ChatGPT message and subsequently locked me out of my main account for three months without explanation or answering my Emails. Max Koven is a notable figure in the intersection of finance and artificial intelligence. With over a decade of experience in the financial services sector, Koven specializes in leveraging AI to drive strategic decision-making and improve operational efficiency. Koven actively shares insights on AI's role in business and appears to cover the AI news cycle with a number of hot takes.