👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. I’ve been tracking robotics and I’m noticing a significant convergence with National Defense spending. It’s a DARPA moment coming for our citizens, cities and economies.

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Good Morning,

I want to share what I’ve been thinking about recently as an emerging technology analyst but also from a humanitarian and civilization based perspective. How this trend scales and compounds is going to be extremely capital intensive.

“Automation, tighter labor markets and a transformed future all within one generation. But at what costs?”

What happens when our capacity to build the future outruns even the leverage of our capital systems? When it’s pushed so aggressively, people and communities begin to rebel? The AI, datacenter and robotics capex is going to find out. I am starting to become a little bit concerned. Venture Capital and BigTech are beginning to diverge from the public good in a new era of Neo-Nationalism. A dominant State backed position towards the future of technology is taking shape in the 2020s.

For America’s financial elite, funding AI datacenters, AI chips and HBM chips has been so profitable they will surely do the same thing with robots and physical AI. This is related to the proposed increase in National defending funding that will pour into drones, rocket companies and space-technology as well. At time when America’s national debt is becoming unsustainable - they will do so at a great cost to future citizens and passing it on to future generations. As I track AI’s development and Venture Capital trends this movement seems increasingly unhinged from what consumers and citizens actually want (more on this in future articles).

It’s at a scale of capital expenditures, R&D and funding that is fundamentally divergent from the past. It will profoundly change the human order of things. A capital frenzy period before a decade where a debt crisis will linger like a coming Tsunami. The robots and debt are coming and this introduces a new Geopolitics and pro-innovation and Defense style of Government that we have not seen in many generations (ironically becoming more like China). Including Physical AI in Silicon Valley and Wall Street’s push of AI, that appears to be the next phase in an organized mechanism to extend the stock market boom by several years.

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👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. I’ve been tracking the U.S. vs. China dynamics of AI and its future for nearly six years.

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How do you summarize the heat that is July, 2026 in the AI industry? It’s been a very bizarre and multi-layered drama. We are witnessing history.

Geopolitics and AI on the Front Burner 🔥

As you likely know, Chinese company Moonshot AI released a new version of its Kimi model called Kimi K3 that is causing a lot of Enterprise AI to switch to open-weight models. It might be one of the biggest AI moments of 2026. With the Iran war unresolved in the strait of Hormuz and the Tech heavy NASDAQ 100 in freefall, it’s becoming a geopolitical and Trump Administration catch-22. There are no clear solutions in war and AI, as it turns out.

Generative AI models are evolving, but likely slowing the revenue growth of AI behemoths OpenAI and Anthropic. With American hyperscalers approaching negative free cash flow via incredible AI capex and datacenter investments, you have to wonder whether it’s all worth it - if Chinese models that are getting larger and more efficient and can replicate the performance while under cutting the cost. It has the potential to become an AI crisis in the stock market even as the Semiconductor boom seems to have hit a bear market correction, after the U.S. listing of South Korean HBM leader, SK Hynix. South Korea (the KOSPI) is now a leading indicator.

With Chinese DRAM maker CXMT about to go public in Shanghai, it’s a very charged China vs. U.S. setup in the future of AI. With DeepSeek’s stunning funding rounds and planned IPOs for DeepSeek, Moonshot, OpenAI and others in 2027, it’s shaping up to be quite a year next year too. DeepSeek raised around $7.4 billion in June last month. We have to assume Databricks has also been one of the beneficiaries of this pivot of Enterprise AI to routing and cheaper tokens of open-weight players in a world where Databricks announced a new round of funding that values the company at $188 billion.

Google’s Gemini 3.5 Pro has been crucially delayed at the worst possible moment. The launch of SpaceXAI’s new model Grok 4.5 was completely overwhelmed by the Kimi K3 moment. Anthropic Fable 5 confusion has given China the ultimate return of that DeepSeek moment vibe back from the dead of January, 2025. OpenAI’s own GPT 5.6 Sol release has also been nearly entirely overshadowed.

The Trump Administration quick to restrict Mythos class models has a serious problem, what if Chinese models are able to approach those same capabilities with open-weight models that were thought to be many more months behind? The Trump administration is showing signs it could ban Chinese cutting-edge models and take drastic steps to try to curtail China’s rise in AI. I thought they were not going to regulate the AI industry. So much for global free market capitalism.

The Brave New World of Token Efficiency Looks Chinese

With Microsoft, Amazon, Meta and even Google behind the Big 7 hyperscalers have lost some of their AI talking points and credibility in this cycle. The mishandling of Mythos class models by the Government and the rise of Kimi K3 type models is the perfect storm that is seeing many Enterprise companies pivot to more rational token usage that’s radically more cost efficient.

While Open-Router isn’t representative of the entire situation, it’s an interesting data sampling point of the overall macro trend: it appears like cheaper open-weight models from China are winning over marketshare.

In my opinion, some of the best Open-weight models from the U.S. are Thinking Machine’s Inkling (about a week old), and whatever Reflection is likely to put out soon. Nvidia’s Nemotron is an often cited alternative to the previous leadership by Meta. The problem is the real lack of leadership in open-source AI in the United States. For America this is a potential disaster in its AI leadership on the frontier of models, tokens and Enterprise adoption.

To make matters even more peculiar, Chinese President Xi Jinping’s most significant recent remarks on artificial intelligence were delivered via a keynote address at the World Artificial Intelligence Conference (WAIC). President Xi Jinping attended in Shanghai the opening ceremony of WAIC 2026 and delivered a keynote speech titled “Joining Hands to Build a Just and Equitable System for Global AI Governance.” China appears to be more advanced in AI governance and regulatory leadership than the U.S. trying to actively build global collaboration around the theme.

Alibaba’s own Qwen 3.8 Max (preview) will also have an open-weight component with an aggressive international token pricing plan. Kimi K3 is not aimed at hobbyist developers but at Enterprise customers in order to ramp ARR before they also IPO in about six months time. The U.S. and China competition in models, even at a time when there are few great application layer products is exaggerating the demand for compute at a time when China has both cheaper token generation and more abundance energy. At a time when the Trump Administration’s key mandate appears to be keeping the AI boom on the stock market rolling for the financial elite and business class. Meanwhile everyone from Anthropic to Moonshot AI are positioning themselves to maximize their IPO hype and revenue sales momentum.

Do Ranking Models even Matter Any Longer?

If you go by Artificial Analysis Intelligence Index, and rank by smartest model, the ranking is:

The state of affairs on peak model performance is roughly as follows:

1. Anthropic – Claude Fable 5

2. OpenAI – GPT 5.6 Sol

3. Moonshot AI – Kimi K3 (open weights*)

4. SpaceXAI – Grok 4.5

5. Zhipu (Z.ai) – GLM 5.2 (open weights)

These lists and benchmarks that they models are trained to perform on are fairly artificial and likely to change next week and certainly by next month.

Compare Models

The “AI Disconnect” is Getting Worse 🔎

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👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. I’ve been tracking AI sources on LinkedIn long before I started this publication.

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Good Morning

Over the years I’ve spent an absurd amount of time on LinkedIn, for work. Hopefully you don’t have to. But the time you do spend there, should be optimized to bring you the right or best information.

The following list took me a lot of time to hand-pick and curate carefully. Over the coming weeks I plan to refine and expand upon it. I wanted to find the most valuable LinkedIn posters about AI. It’s getting a little bit tricky.

According to Pangram, one in four social media posts are now fully synthetic or AI generated. Of all posts they flagged as AI-generated, two-thirds came from LinkedIn. That’s not to say LinkedIn isn’t useful for networking and for AI News. I wanted to look into who are some of the top people to follow for AI Enthusiasts. This article will be my first humble attempt to do so in quite a while.

According to their report, Substack is the “most human” and LinkedIn is the least. This is not an endorsement (or sponsor) but if you want to try their Chrome extension you can do so here.

LinkedIn has the most longform AI Content; Substack the Least

Pangram claims that only 53.2% of long-form posts on X are identified as being written entirely by humans, even Satya Nadella (see blog version) or Demis Hassabi’s PR looks AI generated. I’m really not that AGI-pilled to overlook this, it’s hardly readable. LinkedIn prides itself on professionals who are credible and the platform has improved a lot in connecting you to your (search) intent, while helping you to track AI News and AI related industry topics is my aim in this list. So if you are more interested in AI at the intersection of your profession, product, marketing, management, AI infrastructure (datacenters), energy, big technology, or whatever else, you can find it.

Beyond the AI Slop

If you are news obsessed and want to stay in touch with the beat around AI, you will have to try to look beyond the slop.

Why Care about the Linkedin Feed for AI?

Not all interesting sources of AI News frequent LinkedIn but a sizeable number do. Especially specialized consultants, venture capitalists, niche creators and educational sources.

• The variety of insights if you curate a good feed can be helpful to give a holistic (and global) picture of what is going on. They are delivering insights on a regular basis that are easier to digest and not always found in Newsletters.

• (None of the links in this list are endorsements, promotions or affiliates).

• Although I have made an effort to include Newsletter writers and European sources.

If you follow these AI sources on LinkedIn, I believe it will improve the quality of your feed to stay in touch with the industry. While I do my best to not include AI executives or VC type figures, some of them do curate great AI News tidbits. I also tried to balance the list away from technical ML topics but to include new developments like datacenter, energy and AI infra considerations. Overall the list is curated for a general reader that is seeking to keep up with the latest AI News with a selection of sources from many angles.

Preliminary Top 2025 AI LinkedIn List

These are my favorite and top picks for LinkedIn sources to follow for AI enthusiasts to improve your feed. This is not an exhaustive list but can substantially improve your access to the latest information relating to the AI industry even if you are only an occasional user of the LinkedIn platform.

• You can save or bookmark this article, or simply take the few minutes required to follow the recommended AI sources below: the list section links called Posts takes you to their latest posts where you can judge for yourself if they are good for a follow.

This article list basically took me the majority of the week to put together. As such it’s going to be exclusively for paid readers of this publication.

There are obviously thousands of decent AI sources on LinkedIn, but if you could only pick a few which are the most informative, useful, inspiring, factual and educational for a general AI enthusiast and reader? This is what I set out to do.

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👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. I’ve been doing this for five years and before ChatGPT came along.

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How will AI become more accessible? Are older workers who are laid off in a tough spot due to AI? I didn’t think I’d have to write about OpenAI again. But some events are like the echoes of history.

Is AI increasing Ageism in the workplace? 🧐

At a time when there’s going to be a Physical AI and AI wearables race in the consumer AI economy kicking off in 2027, OpenAI’s plans to even compete in the AI device race might be under serious threat, with increased scrutiny and even legal delays. The weekend news is an Apple lawsuit which looks very damaging to OpenAI’s already badly eroded brand and ability to secure meaningful partnerships and business relationships. I’m not sure what kind of Enterprise customer would want to do business with them at this point in 2026. But how about ChatGPT users?

OpenAI’s last 24 hours: (Saturday 11th, of July)

> Top Exec unexpectedly departs (claims health)
> Shuts down browser tool after 9 months (Atlas, another failed product)
> Sued for trade theft by Apple
> Caught selling product to China against sanctions and lastly:

>OpenAI's head of safety systems, Johannes Heidecke, is leaving the company.

The complaint accuses OpenAI of orchestrating a broad effort to systematically acquire and exploit Apple's ‌confidential information and trade secrets is very serious. The evidence looks daming.

Read the Legal Filing

How do you even recover from this? I expect Microsoft to also bring a lawsuit to them in the coming months in relation to their betrayal in favor of Amazon that was against Microsoft’s terms.

Apple is seeking (Ed Ludlow explains):

• A jury trial.

• An order requiring OpenAI to stop the alleged misuse of Apple's trade secrets.

• Destruction of any Apple proprietary materials in OpenAI's possession.

• Redesign of upcoming OpenAI hardware products so they do not incorporate Apple's technology.

Chronology of Events

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👋 Hey there, I’m Mike. Each week I share AI articles at the intersection of tech, business, society and the future. I also try to share the work of writers from all around the world. If you want to support the channel or gain full-access to my work, go here. Read Archives | See Substack Notes | Visit our community Chat | Visit Homepage. I’ve been doing this for five years and AI is still a worthwhile topic.

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Our guest writer today is Weng Honn Kan, from Malaysia. This is the second article in our Claude for Investing series, you can read the first article by here.

Claude AI for Equity Research

Claude’s Fable 5 model has quite the story. Hurry to use it for Investing purposes as Paid Claude users get just four more days with Fable before it shifts to pay-per-token pricing on July 12th. Agentic AI is about to really change how we do investing and pick stocks.

writes the publication How to Invest with AI.

How to Invest with AI

Discover the best AI stock analysis tools and investing strategies.

How to Invest with AI

Discover the best AI stock analysis tools and investing strategies. We test every AI tool with real money to show you what works and what doesn't , so you can build an AI investment strategy that actually pays off.

By Weng Honn

• Weng Lab: Building, Testing, and Reviewing AI Investing Tools, Learn more About.

Related Articles and Resources

• How to use Claude for Investing: the 4-Level System (AI Corner)

• Find the winners of any market trend with claude (Compound with AI)

• Build your own stock analyst with Claude

Read Compound with AI

Let’s get into today’s guide:

Claude Fable Guide for Stock Analysis

The Complete Guide to Using AI to Spot Undervalued AI Stocks

How I set up Claude Fable 5 for stock research , and which of my 3 skills actually need it .

The model they tried to ban is back. Here’s how I point it at stocks.

For about two and a half weeks, the most capable AI model you could legally touch simply… vanished.

On June 12, 2026, the U.S. Commerce Department ordered Anthropic to suspend Claude Fable 5 (and its locked-down sibling, Mythos 5). The trigger was a jailbreak that Amazon’s researchers found , a prompt that got the model to flag software flaws and, in one case, write code showing how one could be abused. Because the order applied to any foreign national and Anthropic couldn’t check every user’s passport in real time, they pulled the plug for everyone.

Then, on June 30, the controls were lifted. Fable 5 came back online on July 1 across Claude.ai, Claude Code, and Cowork.

I’m not going to tell you it was “taken out because it’s too powerful and might shock the world.” That’s the internet’s version. The real version is more useful to you as an investor: the single most capable model Anthropic has ever released to the public was considered serious enough that a government reached for emergency export controls — and it’s now sitting in the same app you already use. That’s the part worth paying attention to.

So this week is a hands-on one. I’ll show you exactly how I set Fable up for stock research, what it’s genuinely better at, and — the part most people get wrong — which of my three skills actually need it, and which ones you’d be silly to waste it on.

Let’s get into it.

In this sharing you will get:

1. What Claude Fable 5 actually is (and why it’s different)

2. What Fable is genuinely best for — and what it’s overkill for

3. The framework: the Fable Decision Grid

4. How I set up my investment AI system using Claude Fable .

5. How to set up Fable for your stock research — step by step

6. Get the right skills to do the right job.

Let’s dive in…

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I took a few days off (still not quite at my usual cadence) not to annoy my American readers who have been celebrating Independence Day and spending more time with family. However there are some urgent developments worth mentioning briefly. A lot of American trends are demonstrating some issues with AI actually not boosting productivity.

In my opinion a major change has taken place in June, 2026. Let me try to explain. On June 12th, 2026 the U.S. government abruptly restricted Anthropic’s Mythos class of models. This among other related things has significantly broken down trust in closed-source models and companies like Anthropic and OpenAI. It’s a big shift.

If 2025 was the year where vibe coding failed to contribute meaningful products at scale, 2026 is the year when tokemaxing led to high Claude code bills and became token-minimization where AI agents failed to demonstrate as much value as it was hoped that they would at some of the biggest and most powerful companies. This has predictably led to more widespread adoption of open-weight models out of China. This is a marked change for the future of AI and illustrates how AI has rising elements of class struggle, geopolitics, AI policy impacted risk mitigation and a problematic declining public perception and negative sentiment towards AI.

I’ve never seen such division in the AI community over closed source vs. open-source models before as I have in the weeks near the end of June, 2026. A world where the U.S. government not only puts Anthropic on a supply-chain risk sanction list (back in February) but restricts their breakthrough Mythos class of models. Where Palantir, a company embedded within the Pentagon and U.S. administration is openly questioning the value proposition of Anthropic and closed-source model makers. This made me very uncomfortable because you have someone embedded in the National defense complex making an argument for open-weight models that China currently dominates.

2 Minutes 49 seconds Clip - Alex Karp CEO of Palantir

While Palantir has business reasons to make this argument1 (since Anthropic is likely a direct Enterprise AI competitor), to watch the Pentagon and Palantir (who are supposed to be protecting American interests) hurt the AI leadership of America with brash arguments that favor China and Chinese AI products is very disconcerting and drankly disheartening.

This is leading to a big transfer from closed-source models to open-source models that will make some of China’s AI startups way more profitable. Many businesses can’t work with AI companies that are restricted or whose models can be shut down at any time, and who are as expensive as Mythos (Fable 5) models are relative to the competition. Businesses have had to pivot. The Trump Administration have significantly damaged America’s AI leadership in the past few weeks.

Meanwhile, the build out of AI infrastructure is not slowing down, it’s speeding up.

The Mega Neo Clouds are Arriving in 2026

In early July, not only has SpaceX but now Meta and Softbank (via SB Neo) have entered the Neo Cloud arena of selling compute and developing massive datacenters with an aggressive monetization plan.

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June 30th, 2026. 1

Good Morning,

Can AI further science? How are hugely well funded AI labs like OpenAI trying to prove this? Today’s article explores the fascinating case of the frontiers of Mathematics. I geek out also about AI’s impact on science as evidenced by a new breed of AI startups generally understood as Neo Labs. To me these are moonshots that are typically highly funded AI research labs, often founded by elite ex-researchers from giants like Anthropic, OpenAI, DeepMind, and Google Brain.

Meanwhile I’m always reading AI and economic reports, and the Bank for International Settlements (BIS) compares the capital trajectory of the current Artificial Intelligence boom against four major historical economic bubbles and innovation cycles.

While drawing structural analogies to the 1840s railways and the 1990s dot-com era, the BIS highlighted several unprecedented, highly concerning anomalies unique to the 2025–2026 AI investment cycle.

Read the Report

The Exponential View is reporting that the generative AI economy has generated $110 billion in sales over the past 12 months. Check out their State of the AI Economy Report as well for some great summer reading.

View the Infographics

The Exponential Demand for Compute is Accelerating Revenue

AI Exuberance in an era of Token Maxing and renewed Token Minimalism

2

The Impact on the Labor Market due to AI Remains Highly Uncertain

Key AI News Stories I’m Following & A Sampling of AI Neo Labs (startups)

• Apple and Microsoft have raised consumer prices (around 20%) on hardware and electronics in part due to the HBM supply chain crisis due to the datacenter build-out.

• The pace of “Neo Lab” (a new category of AI startup) creation, AI labs designed to focus on pushing AI faster have received considerable recently funding like Mirendil, Engram, General Intuition, Prometheus, Trajectory and more.

• Mirendil is building "self-accelerating" AI that can do the actual work of an AI researcher. For instance, they train frontier models that are expert at AI R&D and build the product around it.

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June 25, 2026.

Good Morning from typhoon drenched Taichung, Taiwan. I try to give my readers broad exposure to AI’s evolution from multiple angles. There’s a surprising number of aspects to this.

AI definitely doesn’t move as fast as you think, just take smart cars and autonomous vehicles. Even the best companies doing this in the world are taking decades to scale.

• On the topic of Physical AI there are the frontiers and then there’s the reality. An important part of how we as consumers experience AI in the physical reality is going to be autonomous vehicles (AVs).

• Let’s be real, difficult more physical manifestations of AI and emerging tech like AVs, robotics, humanoids, Quantum computers with millions of qubits and even more speculative ideas like datacenters in space are going to be exceedingly difficult to turn into reality. They will on the whole take more time, be slower to arrive and be less capable than you think. Innovation is hard, and God knows we’ve been patient. [The idea that AI is moving so fast isn’t empirically correct]. I’d like to see us cover AI with more realism.

• Think about how long it’s taken even Waymo to arrive at this point. Waymo was originally founded in January, 2009. On June 11th, 2026 Waymo finally launched a premier subscription tier for $29.99 a month in select cities (called Premier). It’s starting this year in select cities such as San Francisco, Los Angeles and Phoenix. In terms of AV startups, I’m also really bullish on Wayve, an Nvidia backed UK based startup who are building AV based software and AI models for autonomy.

  What’s your taxi ride preference? 🗺️

Driver or no-driver, consumer preferences might shift radically in the years ahead. If price wasn’t a factor what would you use?

Physical AI is Hard, Autonomy is Tricky

AVs and robotaxis are still years away from scale and while some of us have experienced them, most of us still have not. The build out of physical datacenters and AI Infrastructure at scale is hitting a crazy number of bottlenecks. Manifesting AI in the real world is just incredibly challenging. By the time we arrive in the 2030s however it’s going to be pretty exciting. Autonomous vehicles (AVs) and Robotaxis have to be one of the most fascinating case studies of this. As will another industry I’m also becoming pretty obsessed with, space-technologies.

Today’s article is going to be primarily about Waymo. I also want to introduce you to some of the AV and mobility related Newsletters I follow.

Harry Campbell of the Driverless Digest Newsletter shared this image recently:

Besides Waymo, there are many other interesting names. There’s the likes of (Amazon’s) Zoox and Mobileye who are also making headway and bigger plans in the Robotaxi direction. Intel majority owned Mobileye is aiming for and initial 100-vehicle fleet into a major U.S. city in 2027 and hoping to scale the fleet to roughly 17,000 vehicles over the next five years.

Google spin-off Waymo is however the outright leader, with a $16 Billion funding round earlier this year and a valuation of over $126 Billion. Alphabet’s stake in Waymo is estimated to be likely well over 70%. So when we say Google is a full-stack AI company - we aren’t just talking vertical integration and the application layer but the most tangible things like transportation and TPUs, the nuts and bolts. All of this is compounded by how well Google has raised capital in 2026. Autonomy and AI infrastructure are just two areas where Alphabet’s future is exceedingly bright.

Waymo will be taking on Uber in its own way but have several global rivals such as Baidu Apollo (Apollo Go), Pony.AI, WeRide, Tesla and a host of others. In March, Uber announced a massive partnership to invest up to $1.25 billion through 2031 to deploy up to 50,000 fully autonomous Rivian R2 robotaxis exclusively on the Uber platform. There are so many players and so many partnerships, it’s a bit confusing even for us who watch the space. How will Waymo challenge Uber and how will all of these partnerships pan out in different regions of the world?

Waymo’s track record is also fairly stunning when it comes to the driver and passenger saftey aspect: Even as Waymo has scaled into increasingly complex environments like airports and new cities, the safety benefits kept compounding. It’s a good sign for the AV industry. While there’s always the funny or scary story of some headline mishap, for the most part the tech is improving.

Waymo is marketing itself a bit like the Anthropic of the road, and as being 10x safer than an average human driver. It certainly makes you pause and wonder.

In case you are interested in following autonomous vehicle news one of my favorites is . I asked him to do a deep dive for us on Waymo, todays’ piece.

The AV Market Strategist

The AV Market Strategist

The AV Market Strategist breaks down strategic developments, market dynamics, and competitive moves in the autonomous vehicle industry to reveal where the market is truly heading.

By Daniel Abreu Marques

• Deep Dive Pony.ai: Business Model, Unit Economics, Fleet Data, Financials and More

• WeRide Hits Madrid, Tesla’s Map Grows but Its Fleet Doesn’t, NVIDIA Wants to Be the Robotaxi Standard

• Waymo’s Shocking Data Release, Uber Invest $100M in Robotaxi Infrastructure

• Mobileye Joins the Robotaxi Race

• Waymo’s Master Plan

So what does a Waymo look like from the inside?

Autonomous AV and Neo Mobility Newsletters of Note ✇

Check out some of the community Newsletters for this topic:

• The Driverless Digest

• Self Driving Insights

• Ottomate

• Movements

• The Curbivore

I don’t know what the future holds but there’s probably going to be a Waymo in it.

Let’s get on to our deep dive now by Daniel.

Waymo: The Company That Solved Self-Driving and Now Has to Scale It

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June 23, 2026.

AI is at a very awkward stage in its development in 2026, for language based Generative AI models to become generally useful in society will require many things to go right in the years ahead. I’m not even talking about AI agents.

Inherent limitations in the technology to better understand the physical and human world will require a lot more funding in a convergence of emerging technologies we are now starting to see. This is positioning the 2030s and 2040s as the key decades to develop a real unified computing paradigm of a truly multi-spectrum AI. We need to remain focused on the big picture.

• Generative AI

• Physical AI

• Unified computing (world models, Quantum, ambient computing, new architectures of AI)

• Orbital Compute and a Space Economy

• Scientific AI (superintelligence in biotechnology, chemistry, materials development, self-improving Labs)

Read more

Good Morning,

AI Supremacy is also a Newsletter where we track the intersection between BigTech, BigAI and the best AI startups competing for future marketshare.

• Incumbents will be put under pressure. Microsoft backed OpenAI is sort of in incumbent territory already. Today, let’s take a closer look into Codex.

• In March we learned that OpenAI want to create a “Super-app” that combines ChatGPT and Codex. With just a few months before a supposed IPO, that’s an awkward pivot for OpenAI, where ChatGPT no longer even has a 50% marketshare.

Until January, 2026 ChatGPT commanded over 50% market share, but by May's end, it had fallen to 46.4% thanks to the rise of Gemini (27.7%) and Claude (10.3%). Now with Meta’s AI app gaining initial momentum, who knows where ChatGPT will even be by year’s end. There’s also a problem with OpenAI’s pivot to Enterprise AI, SpaceX just finished the acquisition of Cursor.

“For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon.” - SpaceX

Why OpenAI is Under Pressure in Marketshare

Meanwhile the Meta AI app is experiencing a massive surge in momentum, driven by deep integration into Meta's 3.5 billion daily active users ecosystem, standalone mobile app growth, and aggressive rollouts of new native features like "AI Mode" across Facebook. How fast can that increase?

On the Enterprise AI side outside of Anthropic’s dominance, Cursor’s ARR hit $4 Billion in June. OpenAI thus has competitive pressures both in B2C and B2B. This means OpenAI’s execution risk in merging ChatGPT with Codex is high and the result might determine what kind of future the business will have in such a competitive market.

is the author of The AI-Augmented Engineer. He will be covering the Codex section of the article.

The AI-Augmented Engineer

Teaching software engineers how to accelerate their careers with AI. Deep, technical guides on Claude Code, Codex, Cursor, and more.

By Jeff Morhous

Cursor’s acceleration of revenue and entry into AI agents makes it an ideal fit to help scale SpaceXAI’s bold ambitions to scale Enterprise AI customers that makes up a generous part of SpaceX’s speculative TAM (total addressable market in its S-1) to say the least. While ChatGPT has hit a supposed 1 Billion users (MAUs), it’s losing marketshare very rapidly. The latest iteration of a State of AI mid 2026 report goes into some great details:

I really enjoyed this SenseTower report, they are not an affiliate.

View the Report

ChatGPT’s 3.5 Year First Mover Advantage is Shrinking

Sensor Tower’s State of AI Report also found that users are increasingly willing to switch between assistants. ChatGPT will be put under pressure by Google’s Gemini, Claude, SpaceXAI, Meta AI as well as a well funded DeepSeek, Alibaba Qwen, Moonshot AI and Z.AI and ByteDance that are evolving rapidly.

Sense Towers State of AI Report has a lot of tidbits as well for those of us who follow AI closely. Like for instance, that Anthropic’s Claude earns more revenue per user than ChatGPT does. That emphasis on B2B and superiority in coding models is really turning out to be a better commercial strategy.

ChatGPT fast to 1 Billion MAUs but Trouble is Ahead

Claude’s average revenue per user on mobile in the US rocketed from under $0.50 last September to $2.76 in May.

Today’s article will have many interesting OpenAI Codex related links.

• Read: Codex wants to work on more than just code

• Using NotebookLM to learn new things

• The ultimate guide to Codex goals

• How OpenAI prompts Codex for the best results

Meanwhile both contemporaries and younger AI startups are getting serious funding that will challenge OpenAI’s dominance. I project China’s AI ecosystem to have a really breakout 2027.

SpaceXAI Acquiring Cursor (Anysphere) for $60 Billion

SpaceX expects the merger to close during the third quarter of this year and they are already collaborating rapidly on new coding models. This gives what was formerly xAI (a relative failure vs. cash burn), a serious boost in revenue and momentum. It also entirely changes the landscape and puts more pressure on OpenAI, given the wild success of the SpaceX IPO. At time the time of writing ticker is up 31% since its IPO last Friday with a market cap that overtook Amazon and even briefly reaching the market cap of Microsoft.

I had already believed Anthropic and Google were putting pressure on OpenAI and had overtaken them in certain ways. Now the rise of SpaceXAI and Meta AI via their AI app means OpenAI is highly likely to continue to struggle.

All of this totally changes the future of AI.

Cursor exits with a $4B in run rate growing 7x YoY. It’s hard to find such an MIT startup success story in the history of technology. The four 25yo MIT founders will make ~$2.7B (each) in a span 4yrs and first 50 startup hires ~$20-500M each. It’s an AI coding exit for the ages.

They could have gotten another round in funding where before SpaceX came knocking, Cursor was on track to close a $2 billion funding round from the likes of Andreessen Horowitz, Thrive, and Nvidia that would have valued the AI coding startup at $50 billion. But that never materialized, getting a compute deal with SpaceX quickly escalated into an acquisition deal. With the costs of compute, Cursor was burning cash too fast (at that point in time) even with its meteoric growth. SpaceX being heavily in debt and unprofitable, can absorb those types of loses.

Where to learn more about working with Codex

Let’s say you have an open mind to using Codex as an AI tool.

The OpenAI Academy (not an affiliate) has a lot of workshops and live sessions on using Codex. OpenAI’s spending on marketing and education has been considerable the past few years, but then again Codex might evolve into a useful general purpose tool. If OpenAI ever hopes to have a path to profitability, Codex needs to shine.

• ⚡ Codex for everyday use

• 🖥️ Building websites with Codex Sites

• 💐 Codex for creative building

ChatGPT’s marketshare is declining rapidly

The Generative AI trend is a story of rapidly shifting business and consumer preferences and more and more options.

I am Obsessed with AI and Trust - Public Poll:

I conducted similar polls on LinkedIn and Substack Notes and there appears to be a growing consensus. In the above poll I add SpaceX as the Cursor acquisition changes xAI’s abysmal execution and performance substantially.

The story of OpenAI’s Codex plan is even more particular. I’ll turn it over to now.

What’s new in OpenAI’s Codex

Codex used to be easy to explain.

It was OpenAI’s tool for developers. You pointed it at a repo, gave it a coding task, and it helped you turn ideas into working software. If you’ve heard of Claude Code, it was just OpenAI’s version of that tool.

But something weird is happening. Codex is starting to outgrow code.

OpenAI is turning Codex from a developer tool into a general-purpose agent for knowledge work. Gmail, Calendar, PowerPoint, computer use, and even an upcoming merge with ChatGPT.

Codex is no longer just where software engineers go to automate coding tasks. It’s becoming the place where OpenAI wants work to happen.

Codex has historically been for developer

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Good Morning,

AI Supremacy Newsletter is also committed to getting a variety of some of the top voices around AI, …

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We don’t really know what AI could become…

Good Morning,

The two biggest events this week are likely the reaction to Fable and the SpaceX IPO.

I’ve been struggling a little trying to think about what’s really new that was announced at Google I/O, Microsoft Build Conference and Apple’s own more recent developer conference of WWDC 2026. There was a tangible sense of how empty many of their tech announcements were, especially with regards to AI.

I can’t even put my finger on why this is, maybe it’s the AI overload of the news cycle, the exaggerated hype or how lacking in meaningful products and application layer innovations we’ve even seen after three years of LLMs (so many models) and more datacenters. I can’t help put have the feeling that I was expecting more in the 2020s that we are likely to see from Generative AI.

Hopefully next year in 2027 with a deluge of AI devices this will feel different. Will a Codex version of ChatGPT feel different? Apparently, a senior OpenAI executive went so far as to say that “chat is dead,” shifting its focus toward a platform centered on agents and coding tools. It just goes to show how ChatGPT’s success story is fading so badly. But how would OpenAI ever compete with Cursor or Anthropic at this point for Enterprises and companies where trust is a major factor. OpenAI might have to try to lower prices, but they are already burning so much capital. Cursor who now have $4 Bn. in ARR and are accelerating even faster.

There certainly will be winners and losers to paraphrase Sam Altman. His eye-scanning startup isn’t fairing any better.

Will BigAI Disrupt Incumbents by 2030?

Will the hyperscaler names be re-written by AI too? 🤔 I had written about this back in June, 2025:

The verdict on how BigTech (incumbents) react to BigAI is still unclear? Outside of Google, it doesn’t look so good for the others. Their capex to AI execution is looking rather poor in more than one case.

Let’s first see how the 2026 IPOs pan out but Apple, Microsoft, Amazon and other incumbents don’t feel like they are active participants at the frontier of Generative AI. Apple’s lineup of AI devices looks fairly impressive however for 2027 and 2028.

China’s Massive AI Compute Announcement

With news that DeepSeek is getting $7 Billion in funding a week ago along with massive Capex increases from ByteDance and Alibaba for compute - China is going all in. China is preparing to spend around 2 trillion yuan ($295.43 billion) over the next five years on building data centers ​across the country, Bloomberg News reported on Tuesday, as ‌Beijing looks to challenge the U.S. in the intensifying AI race.

So instead of relying purely on private tech giants like Alibaba, ByteDance or Tencent to build isolated clouds, the National Development and Reform Commission (NDRC) is spearheading a blueprint to knit the country's scattered computing facilities into a unified national network by 2028. If China feels they have to do this too, it’s going to be a brave new world. Curiously how Beijing is boosting Huawei isn’t so different how the Trump Administration has been supporting Nvidia with circular financing of the entire ecosystem in a spider-web of deals. But what exactly are we building for civilization in the big picture.

We Don’t really know what we are getting ourselves into…

Claude Skills Guides

• KDNuggets (not an affiliate) has an interesting Anthropic’s Complete Guide to Claude Skills Building.

• The Claude (Content) skills I use to run Growth Unhinged by

• How to use Claude AI for Investing (the first post in our series on AI in Investing got a lot of bookmark saves on X).

Reactions to the Frontier Model of Anthropic

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As SpaceX, OpenAI and Anthropic IPOs approach in the days and months ahead, how we define the narrative around the future of AI is also taking shape. With Anthropic expanding access to its new class of LLM called Mythos to more organizations, the U.S. Department of War appears to be using Mythos for Cybersecurity attacks, reports the FT.

In recent weeks several significant seed rounds have been given to AI labs in the U.S. working on various aspects of recursive self-improving AI capabilities, or RSI. We have to conclude that Mythos as an LLM step-up might represent the first RSI-native Model. If Anthropic’s framing is correct, we are heading into unchartered territory.

Claude 4.8 already seemed like solid advancements but the Mythos class appears relatively distinguished compared to its competitors at Google, OpenAI or China. This is giving Anthropic a feeling of grandeur heading to its landmark IPO that might end up being the highlight of these Mega IPOs of 2026. Now in a blog post on its website on Thursday, Anthropic wrote about the risks of AI progressing to a point where it could improve itself autonomously.

Anthropic reported a landmark blog titled When AI Builds Itself, while the U.S. Government is discussion about taking equity stakes in the biggest AI companies. That is for real, Senior U.S. officials held preliminary discussions with major AI companies about the potential for the government to buy some shares in their firms. These are unprecedented and gravely risky endeavors as Nation States seek to mould AI in their image.

OpenAI CEO Sam Altman has discussed the idea with government officials since President Donald Trump began his ​second term, the report said. Sam Altman and Bernie Sanders have different ideas on how that could look. This is in sync with Trump and his financial elite friends to create a Sovereign Wealth Fund for the United States. Anthropic is not having conversations with the administration about providing equity to ​the government and it’s not clear what Sam Altman or OpenAI’s motives are to enter into such a deal.

A White House meeting is reportedly being set up with leading AI firms to explore the concept

Anthropic’s Mythos has raised concerns that new AI models might be capable of, including and especially in cybersecurity. Anthropic confidentially filed its IPO prospectus with the SEC and said it will offer Mythos to the European Union along with an additional 150 partners in 15 countries. Mythos is becoming more than just a frontier model however, it’s becoming part of a larger debate around what recursive self-improving AI might do if it’s real across industries.

Anthropic’s cryptic Tweets are also unsettling at a time when Anthropic is clearly working more closely with the Department of War while being held semi-hostage with a rather nefarious designation as a supply-chain risk.

Defense Secretary Pete Hegseth has denied Anthropic’s request to reconsider the AI startup’s designation as a national security risk, the Pentagon told the D.C. Circuit Court of Appeals on Thursday.

It appears like the Trump Administration has a special relationship with Sam Altman and OpenAI and is trying to supress whatever Anthropic represents. If Mythos is being used for cybersecurity offense (supposedly against China) then this is not a good sign of AI becoming a geopolitical risk in an era of more automated systems in National defense.

Anthropic, is Everything Alright?

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Good Morning, everyone.

It’s a very hot and humid June here near Taichung, Taiwan.

Welcome back to AI Supremacy where we cover AI at the intersection of business, finance, tech, society, culture and civilization. We also try to deliver to you a few AI guides each month.

I’m not sure if Anthropic is 'midwifing a deity' according to VC Bill Gurley, but they have seemingly beaten OpenAI to a confidential IPO filing that enables them to fast-track what will likely be the biggest AI IPO in history in September, or October later this year. It’s a frantic situation for some of the fastest AI startups in history.

“The AI supercycle has 4 bottlenecks: compute, memory, power and now photonics.” - Crack the Market Newsletter ()

It’s an exceptional time, Google wants to raise another $80 billion in stock, including through a $10 billion investment by Berkshire Hathaway for the unique challenges of more AI Infrastructure and power solutions.

Claude for Equity Research

Meanwhile our guide on using Claude for investing by got a lot unexpected organic traffic and bookmarks on X, where people are using AI for equity research, and beginning to use agents for investing. What struck me about this piece is the number of bookmarks, free trials and buzz it was getting across social media.

Read our Guide

The Datacenter Acceleration & Backlash 🚨

There are a lot of Datacenter stories that I want to catch up to drive and give you a holistic picture from many angles about the space and the reality not just from the VC and corporate side but from the more human, energy, local community and environmental perspectives as well.

In April, Alphabet updated its full-year capital expenditure range to as much as $190 billion and others like Meta and Amazon may go even further so there’s a steep increase in corporate foreign bonds (debt) and various projects around Energy and Datacenters. With SpaceX having to sell compute to Anthropic just to make ends meet pre-IPO, Meta might become a glorified Neo Cloud as a side gig. These my friends are weird times. Google had already last month announced a TPU based Neo Cloud with Blackstone.

In this article I’ll try to cover some trends I’m noticing and some Datacenter stories that caught my eye over the past few weeks. Scroll down for more on this.

AI Startups are Eating Pre Generative AI Startups: Fallen Unicorns 🦄

In Venture Capital’s obsession with AI, they are funding newer startups that are AI-native post 2023. For instance, AI is “disrupting” startups pre ChatGPT. Nearly half of America’s 857 unicorn startups haven’t raised fresh funding in three years, PitchBook data shows.

While business creation appears to be higher, there’s carnage in the startup world. Nobody told you more than 220 companies that once hit billion-dollar valuations are now considered “fallen unicorns”.

The concentration of capital is also damaging - in that, the AI boom that has funneled more than $250 billion into OpenAI and Anthropic and reset valuations on entire classes of startups. There’s a kind of price for this kind of American innovation. It’s pure carnage in the land of startups and Silicon Valley doesn’t like to admit the obvious:

“Startups that last raised in 2021 are now worth 68% less on average, while those that last raised in 2022 saw a 52% decline, according to Pitchbook’s own valuation estimates.” - CNBC

Startups that raised just 4 years ago, in 2022, are down 52%. Just like I predict now, startups born with agentic AI might destroy AI startups pre Agentic AI, for example pre 2026. AI in many ways is a great destroyer of capital not just in Capex but in the cost of Venture Capital FOMO on all the other industries that would ordinarily be getting funded.

It’s not just the demand for compute that’s accelerating, it’s the speed of adaptation.

Time to Revenue has Been Sped Up

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The antics of AGI of 2023 is going to turn into the race to recursive AI (RSI) of 2027. Recursive self-improving AI could fundamentally reshape how we experience the world and fundamentally accelerate digital transformation in the years to come.

While Anthropic has been claiming they use Claude for the majority of their coding since quite a while, there are no signs that we are on the cup of RSI just yet in mid 2026.

However there are a surprising number of new AI startups that claim they are building recursive capabilities of AI into super valuable industries, like chip design. Many of them claim this is their academic focus now and the startup called Recursive Superintelligence really comes to mind most recently. You can imagine how AI engineering their own improvements can scale fairly quickly once and if it gets good at this.

But will this propel a new era of science, R&D and innovation broadly speaking? And what are the chances of these buzzy startups at being commercially successful and actually succeeding in a commercially viable way at what they propose will soon be possible? Let alone with just Generative AI technology.

“At its core, recursive self-improvement (RSI) is a process where an artificial intelligence system reviews, rewrites, and optimizes its own source code or architecture to become smarter.”

• I believe 2027 will indeed feel like the entry point into a fundamentally different world post the three major AI IPOs of 2026. The vibe-shift in the AI ecosystem is going to be tangible.

• DeepSeek’s senior management has told potential investors in its ongoing 70 billion yuan ($10 billion) funding round that the startup will prioritize groundbreaking AI research over short-term commercialization.

• With AGI not a commercial benchmark worth talking about seriously, RSI becomes a much more concrete proposition. The idea of AI improving itself exponentially is a fundamental inflection point in the theory around the Technological singularity. Ray Kurzweil, in his book The Singularity is Near, (that I used to obsessed over many years ago) famously predicted that the singularity will occur by 2045. Now some believe that it could arrive anywhere between the years 2030 and 2045. Some see the rapid improvements of Generative AI’s capabilities as evidence it is indeed on the way to happening.

From AGI to RSI Goals for the Future of AI

"Today's systems are nowhere near [AGI]. Doesn't matter how many Erdős problems you solve… I think it's far, far from what a true invention, or someone like Ramanujan, would have been able to do." - Demis Hassabis, CEO of Google DeepMind and Nobel laureate for AlphaFold

Context: Demis Hassabis isn’t just Google DeepMind’s Czar, it turns out he’s an angel investor in Anthropic. It’s a tightly woven interconnected web of influence - where the network of startups spun out by DeepMind alumni have collectively raised a collective $14 billion plus since 2021.

Now the same is occurring with OpenAI alum.

Hassabis invested personally in the early/angel stage, before Anthropic became a major player valued in the tens or hundreds of billions, and I’d estimate could have up to a $2 Billion personal stake. These financial conflicts of interest are becoming quite common in the AI ecosystem especially clustered around OpenAI, Google DeepMind and Anthropic and their Alum. AI executives increasingly are angel investors on the side.

“People familiar with the matter said Hassabis was an angel investor in Anthropic, which has since become a key AI rival and among the world’s fastest-growing start-ups. Google has separately invested billions of dollars in Anthropic as part of its cloud and AI partnership with the company.” - The FT

How much of an impact was Hassabis on Alphabet itself investing huge sums into Anthropic and using their TPUs do you suppose? Or decisions to partner with Blackstone on new Neo Cloud do you suppose? These are newly available factors in the circular financing argument.

Manufactured Geniuses hidden in Rising demand for Compute

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Good Morning,

I’m still digesting the Google I/O conference news and some of the key AI trends I’m noticing and while I do so, I wanted to share something a bit different from the usual. It’s a potentially really useful guide since we are in an AI boom of unprecedented opportunity and stock market euphoria that is perhaps a unique window.

Michael Fritzell is an independent financial analyst, investor, and writer based in Singapore. He is best known as the founder and author of Asian Century Stocks, a popular investment newsletter. Michael is a friend of mine and one of the most successful financial writers I know who grew his Newsletter on Substack pretty early on.

This is going to be a guest post by Michael Fritzell who runs one of the most useful investing Newsletters I know of especially for Asian equities. I wanted to share this practical guide since how investors and analysts are using AI in Finance is changing very fast. This is a hands-on guide that should give you a lot of ideas on where to start to use Claude for your investing decision making.

Sign up to Asia Century Stocks

Michael’s Newsletter is no longer on Substack but moved to the Ghost platform. A lot of investors are of course using Claude for their investing activities.

The author briefly describes his Newsletter publication: 1 min 28 seconds. 🎬

• You can find more of his recent interviews with Substack investing, FinTwit and equity folk here.

Many of my readers are also investors and think about technology and businesses at a very deep level.

• Read his recent Deep Dives.

• Follow Michael Fritzell’s Portfolio.

• View his Thematic Reports

If you want to dig deeper to get full access to the work of someone that’s been studying Asian equities for nearly two decades, consider a full sub to Asian Century Stocks.

Get full Access to ACS

One way to think of using Claude for Equity Research is the following:

1. Research

2. Projects

3. Skills

4. Cowork

Claude has evolved a lot when it comes to Agents for Financial Services. Download Claude Cowork.

Some Starting Ideas

• Investors instruct Claude Code to scan the web, pull down the latest 10-K forms, SEC filings, and earnings call transcripts directly into local directories.

• Live portfolio analysis: with Anthropic's Model Context Protocol (MCP), users are plugging Claude directly into live financial databases and brokerages.

Claude for Equity Research

By

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Good Morning,

AI Supremacy is a Newsletter that explores the impact of AI on the future of business, technology, culture and society.

This is starting ot mean a lot for the lives of different kinds of people, consumers, investors, graduates, entrepreneurs, citizens and residents. The pressure of AI on real people and their communities is becoming more tangible this year.

A Pivotal AI Week Ahead

With Google’s I/O Conference starting tomorrow, Nvidia Earnings and the SpaceX IPO filing, this might be one of the most pivotal weeks in AI of 2026 (week of May 18th). Elon Musk is expected to start meeting with investors very soon ahead of an IPO for SpaceX, which was valued at $1.25 trillion after merging with xAI in February. I’m noticing a lot of subplots in the AI ecosystem in a rather bizarre geopolitical, inflation, bond story and Silicon Valley backdrop. Let’s dive into some of the most important among these.

Earnings Calendar this Week

Last week Anthropic announced Claude for Small Business, less than a year now from its IPO likely in December, 2026. You hear a lot of stories of SMBs struggling to implement Generative AI technology. This is especially true in an era of rising backlash against AI slop, datacenters and Billionaire incentives to praise the AI era as if it’s going to save us all.

At the time of writing today, Cursor released Composer 2.5, and I believe after Anthropic, Anysphere is one of the top B2B and Enterprise AI startups. From a product perspective I think this improves or at least enhances Cursor’s in-house model intelligence, long-running agentic behaviors, and the overall team development ecosystem within its IDE. Cursor is becoming known for its ability to multitask its strong parallel processing with async subagents.

The midpoint of 2026 marks an extremely cringe time in the history of AI, where entry level jobs are being impacted, and people are already extremely fed up. According to Axios, the “disdain spans generations” and political parties. An Economist/YouGov poll released this week showed over 70% of Americans think AI is advancing too quickly, with 68% of Republicans and 77% of Democrats saying it’s moving too fast.

The American Billionaire AI Rush 2026-

Capital, compute and the AI boom of elitism. What’s taking shape is not necessarily making many of us more hopeful about the future.

With three huge IPOs, SpaceX, Anthropic and OpenAI supposedly all coming in 2026 or early 2027, there’s a lot of capital at stake for a lot of rich people and Venture Capital funds, BigTech and the perception that America is ahead in AI.

A jury in Oakland, California, ruled against Elon Musk in his dramatic court battle with Sam Altman and OpenAI. Sam Altman is among a new breed of AI Venture Capitalists that are powerful angel investors while assuming CEO duties of one of the most powerful AI startups ever in OpenAI. I’ve been arguing that it is a company in decline. Whatever it is, it’s a child of a new era in Venture Capital history dominated by a few big funds.

Venture Capital Power is becoming more Concentrated

The Q2 2026 ranking of US unicorns shows a rather high concentration of VCs involved. They are roughly as follows:

A small handful of VCs are seeing the majority of the returns in the AI boom to the detriment of mid-sized VCs. Generative AI is narrowing the power and concentration base of Silicon Valley that was already previously highly concentrated.

AI is creating fewer winners in VC, BigTech and the Future

GenZ is waking up to the danger of BigTech in 2026

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Good Morning,

Innovation in AI is occuring at many of the latest AI Research labs. This has huge ramifications for the future of AI.

What if AI models could deliver experiences that were more human like? As an avid user of Voice AI, I’ve often wondered about this. This week we finally got to see what Thinky is up to.

Thinking Machines Lab, the AI startup founded last year by former OpenAI CTO Mira Murati, that has weirdly enough been mercilessly poached by OpenAI, and yet they have been able to attract some of Silicon Valley’s top AI talent. Thinky wants to move beyond the era of “turn-based” AI interactions and, I think they are on to something.

If they can pull it off, this will essentially deliver way more real and human-like AI interactions in real-time. Think about it, traditional AI models function sequentially—listening and then responding—whereas its new model aims for simultaneous input processing and response generation, akin to a phone call.

What are Interaction Models?

While Lilian is telling a story, the interaction model can track when she is thinking, yielding, self-correcting, or inviting a response; there is no specific built dialogue management system.

Lilian Weng is a Co-founder at Thinky.

Interaction Models are a new category of AI systems with micro-turn architecture, a system that processes data in 200ms chunks. This could literally make AI interactions a lot more useful in the real physical world and social world we actually live in. That’s more human-like for sure Thinky! Murati is no deer in the headlights, she’s just Albanian and the technical term for this is “full duplex,” and the company claims its model, TML-Interaction-Small, responds in 0.40 seconds, which is roughly the speed of natural human conversation and significantly faster than comparable models from OpenAI and Google.

I really dialed into this story since this will clearly lead to a lot of other interesting AI products. If you are a builder, developer, investor or power-user of AI - this is incredibly exciting.

A More Natural AI Interface is Emerging

Essentially AI should serve us but since 2023 we’ve been forced into bad interactions. There’s still a long ways to go. Thinking Machines argues that the back-and-forth interactions with current models forces human users to “contort themselves” to the interface. If you are a regular Voice AI user you know exactly what I’m talking about.

Could we have Benevolent AI that actually looks out for us?

Instead of AI trying to scam us with pleasing words?

Tessa's quality of life has improved a lot with some nagging.

I actually found this pretty funny and would be fine with an AI that nags me in a good way. Can we envision a time when AI is a benevolent advisor and implementer across human institutions and helping to guide humanity across civilization scale challenges? Perhaps like me you are familiar with how the concept of an artificial intelligence "Oversoul" is famously explored by author Orson Scott Card in his 5-book science fiction series, the Homecoming Saga.

For me, Interaction Models point to that world perhaps decades away.

So what would it be like to interact with an AI that isn’t so fake and contrived? The Interaction models have real potential to humanize AI in a way that I think is fairly positive. The interaction models is essentially a new AI system built to enable real-time, native collaboration across audio, video, and text without relying on external scaffolding. You an almost feel the feminine touch in Thinky’s product focus. AI doesn’t have to be awful and feel flawed and sycophantic. Is there a better way to represent and build products with this technology?

‘Full duplex’ simultaneous input/output processing

Thinking Machines is essentially here helping to solve the "collaboration bottleneck” in how we relate with AI in a more realistic manner.

Read the Blog

“We think interactivity should scale alongside intelligence; the way we work with AI should not be treated as an afterthought. Interaction models let people collaborate with AI the way we naturally collaborate with each other—they continuously take in audio, video, and text, and think, respond, and act in real time.” - Thinking Machines Blog.

Capabilities of Interaction Models

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Good Morning,

I’ve been following the Elon Musk trial vs. OpenAI and Sam Altman and there’s reason to believe OpenAI is on a downward spiral. To put it bluntly, OpenAI’s momentum has now been overtaken by that of Anthropic, Google and other AI labs. I’m not sure how it rebounds from this. In terms of LLMs and AI products this is how I see the ecosystem and companies with positive momentum and who are falling behind.

It took me many hours and many days to compile this, so I hope you enjoy it. Pre IPO for the biggest three AI IPOs in history in Anthropic, SpaceX and OpenA, it’s sort of a big deal.

Who’s Hot 🔥

• Anthropic

• Anysphere (Cursor)

• Google

• DeepSeek: aiming to raise up to $7.35 billion (50 billion yuan) at a valuation potentially reaching $50 billion.

• Moonshot AI: $2 billion in a new funding round.

Who is Not 🤯

• OpenAI: credibility loss, investors doubts and scaling back compute

• Microsoft: lagging in internal models and reputation

• Meta: poor execution and exodus of talent

• Amazon

• Apple

OpenAI’s has Executed Poorly and No longer has a material Compute Advantage

OpenAI’s leadership credibility and reputation is also taking a hit from the legal case against them that is being reported on by the media in detail. While Google and Anthropic have executed well in their Generative AI efforts, OpenAI has fumbled their priorities while losing considerable marketshare over the last year. Anthropic’s historical May 6th, 2026 deal with SpaceX AI (formerly xAI) for compute means Anthropic is no longer behind in compute. Anthropic signed an agreement with SpaceX to use all of the compute capacity at their Colossus 1 data center.

OpenAI Talent Exodus Continues

OpenAI keeps losing key talent and this week it was head of private equity Paul Zimmerman, who joined Alphabet Inc.‘s Google as Managing Director and Global Head of Private Equity. Meanwhile, James Dyett, OpenAI’s head of sales, also departed after three years, joining venture capital firm Thrive Capital as Operator in Residence. OpenAI had already lost several key executives and AI researchers earlier in 2026. Meanwhile its poaching more corporate types and executives from SaaS companies in prep for its IPO. I’m fairly skeptical that their Codex campaign on X is even true.

We have to compare OAI with Google, Anthropic and the top Chinese labs at every step now not just in model benchmarks, but in product execution, confidence in their business model, marketshare and revenue momentum (ARR) vs. cash burn. Just months for a supposed IPO later this year, OpenAI do not appear product or confidence ‘ready’.

Anthropic not OpenAIm is the AI Company Everyone is Talking About

While SpaceX, OpenAI and Anthropic are all going public in 2026, Anthropic is the one that is actually performing in the space. explained what Silicon Valley and China are noticing too:

• Anthropic Q1 alone $10B ARR to $30B.

• Anthropic in April, 2026 went from $30B to $44B and that's $96 million in new ARR added every single day.

• OpenAI has not seen similar ARR momentum, in fact their revenue growth has been slowing as they have lost markets to Google and Anthropic in the last year in key areas.

Anthropic on Pace for a $2 Trillion in Revenue by 2030

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