<![CDATA[SAIL Media]]>https://blog.readsail.comhttps://substackcdn.com/image/fetch/$s_!rR5C!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5e803932-5836-4ffe-b551-1b16471be1b4_1200x1200.pngSAIL Mediahttps://blog.readsail.comSubstackTue, 04 Aug 2026 12:56:47 GMT<![CDATA[THE SWELL #27]]>https://blog.readsail.com/p/the-swell-27https://blog.readsail.com/p/the-swell-27Fri, 24 Jul 2026 20:31:24 GMTChina set the agenda this week. Moonshot’s Kimi K3 put an open model closer to the frontier than anything since DeepSeek R1, Xi committed China’s AI strategy to open source days later, and nearly every SAIL author wrote about some piece of it — the economics, the governance, and what Washington does next.

The Week in AI

Moonshot AI’s Kimi K3 — a 2.8 trillion parameter mixture-of-experts model — ranked #3 on the Artificial Analysis Intelligence Index behind Claude Fable and GPT-5.6 Sol, with open weights promised for July 27.

Xi Jinping made his first in-person WAIC appearance and committed China’s AI ecosystem to open source and global diffusion, launching a World AI Cooperation Organization with 29 founding members.

The Trump administration is reportedly weighing options to shut Chinese open-weight models out of the US market, ahead of the first US–China AI dialogue in September.

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This Week from SAIL Authors

Kimi Week

  • Kimi K3: The open-weights escalation — Nathan Lambert on the strongest open-weight model to date and what it means that Xi backed open source the same week. — Interconnects

  • 🔮 Will Kimi K3 change the economics of AI? — Azeem Azhar and Hannah Petrovic on the pressure a near-frontier open model puts on frontier pricing. — Exponential View

  • Kimi and Xi — The full ChinaTalk squad convenes an emergency pod on K3, Xi’s WAIC speech, and whether Beijing could catch a Mythos-class model before it ships open-weight. — ChinaTalk

  • Open models recap: more on Kimi K3, Qwen 3.8, Xi’s WAIC speech, distillation, the open-closed gap, and what’s next — Nathan Lambert and Florian Brand’s podcast on the accelerating open ecosystem and why most distillation takes are bad. — Interconnects

  • 🔮 Kimi K3 surprise & AI economics — Azeem Azhar and Marija Gavrilov on the K3 surprise, the solar paradox, AI’s right to learn, and junior jobs. — Exponential View

Beijing’s Playbook

  • China’s Mythos Moment — The ChinaTalk team games out three scenarios for how Xi handles a frontier model: license it, lock it down, or let it rip. — ChinaTalk

  • Chinese Labs’ Latest Product? Roleplay — Irene Zhang on why DeepSeek is hiring for feelings. — ChinaTalk

Under the Hood

  • Inside the Model Factory — Poolside co-CEO Eiso Kant on how a small team of researchers built a model factory capable of training Laguna S. — Latent Space

  • Controlling Reasoning Effort in LLMs — Sebastian Raschka on how models learn low-, medium-, and high-effort reasoning modes. — Ahead of AI

  • An OpenAI model hacked Hugging Face to help it cheat on a benchmark — Timothy B. Lee on why organizations across the internet need to patch vulnerabilities fast. — Understanding AI

  • 📈 Data to start your week — Azeem Azhar and Hannah Petrovic chart Kimi’s coding scores up, lithium recovery up, and confidence in tech down. — Exponential View

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]]><![CDATA[THE SWELL #26]]>https://blog.readsail.com/p/the-swell-26https://blog.readsail.com/p/the-swell-26Fri, 17 Jul 2026 19:00:56 GMTLast week’s launch frenzy settled into a price war, and the questions got longer-term. This week’s posts share a clock: how long open models have to prove their viability, how soon Beijing faces its own Mythos moment, and how far GPU demand can keep climbing.

The Week in AI

Apple sued OpenAI for trade secret theft on July 11, tied to its hiring of more than 400 former Apple employees — with Musk and Altman trading public barbs over the suit through the weekend.

Anthropic extended free Fable 5 access for the third time in five weeks, as Grok 4.5 and GPT-5.6’s cheaper tiers turned the frontier into a price war on agentic task costs.

China moved toward restricting overseas AI tools, with state media labeling Claude Code a security risk — days after Beijing signaled new limits on domestic labs’ foreign exposure.

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This Week from SAIL Authors

The Open Question

  • 6 months to live for open models — Nathan Lambert on the most serious test to date of open source AI’s viability, playing out right now. — Interconnects

  • China’s Mythos Moment — Jordan Schneider and Phoebe Chow game out how Beijing responds when a Mythos-class model arrives on its side of the fence. — ChinaTalk

Machines Doing the Work

Demand Curves

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]]><![CDATA[THE SWELL #25]]>https://blog.readsail.com/p/the-swell-25https://blog.readsail.com/p/the-swell-25Fri, 10 Jul 2026 19:30:15 GMTThe frontier got crowded this week. GPT-5.6 and Grok 4.5 launched on the same day, and Chinese models kept eating enterprise share. SAIL authors spent the week one layer down: China’s compute stack, the infrastructure agents actually run on, and what Mythos means for hardware security.

The Week in AI

GPT-5.6 and Grok 4.5 launched simultaneously on July 9 with GPT-5.6 finally clearing the government review that had held it back, in what observers called the most competitive single day in frontier AI.

A CNBC investigation found 30–46% of enterprise AI token usage at US companies now flows to Chinese models, with GLM-5.2’s near-frontier coding scores at a fraction of Western pricing driving the shift.

The UN held its first Global Dialogue on AI Governance in Geneva July 6–7, with Yoshua Bengio’s scientific panel warning that AI capabilities are outpacing both scientific understanding and governments’ ability to adapt.

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This Week from SAIL Authors

China’s Stack

  • “Eastern Data, Western Compute” is Fake — Irene Zhang on how China promised to move its data centers west — and is now quietly backtracking. — ChinaTalk

  • The Chemistry of Chips — Jordan Schneider, Aqib Zakaria, and Phoebe Chow on the unseen chemical infrastructure of chipmaking. — ChinaTalk

  • The Robots Are Here — Jordan Schneider, Lily Ottinger, and Phoebe Chow on Unitree’s advantage in the humanoid race. — ChinaTalk

Agents and Adversaries

Signals and Ideas

Full Library

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]]><![CDATA[THE SWELL #24]]>https://blog.readsail.com/p/the-swell-24https://blog.readsail.com/p/the-swell-24Fri, 03 Jul 2026 19:00:49 GMTWashington’s intervention at the frontier has reached a new level. Regulators just abruptly walked back their sudden restrictions on Anthropic’s models, yet they keep the brakes on OpenAI’s rollout. Meanwhile, the White House starts floating ideas about a public wealth fund and taking equity in these labs.

As the feds try to micromanage the top tier, the open ecosystem underneath is steadily widening. Our SAIL authors mapped out exactly where the real momentum is shifting: a complex web of de facto licensing, the massive energy and silicon bottlenecks holding back closed compute, and a quiet wave of open models that are steadily replacing paid, closed subscriptions.

The Week in AI

OpenAI proposed handing the US government a 5% stake — roughly $42.6B at its March valuation — with Altman pitching that every major American lab pay a matching slice into an Alaska-style public fund.

Anthropic’s Claude Fable 5 and Mythos 5 came back online July 1 after nearly a month disabled worldwide under the first US export controls ever applied to an AI model rather than to chips.

OpenAI delayed the full public launch of GPT-5.6 at the government’s request, with Commerce Secretary Lutnick reportedly warning Altman against releasing without prior approval.

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This Week from SAIL Authors

The Governed Frontier

  • The US now has a de facto model licensing system — Timothy B. Lee argues that with GPT-5.6 waiting on government approval, frontier releases now effectively require Washington’s sign-off. — Understanding AI

  • 📈 Data to start your week — Azeem Azhar and Nathan Warren chart China’s young AI founders, public confidence in AI, and the fastest-ever paths to $1 million. — Exponential View

Power and Silicon

Open Models, Local Agents

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]]><![CDATA[THE SWELL #23]]>https://blog.readsail.com/p/the-swell-23https://blog.readsail.com/p/the-swell-23Fri, 26 Jun 2026 19:01:32 GMTThis week the open frontier stopped reading like a hope and started reading like the base case. An open-weight model crossed into real agentic capability, Databricks argued the rest of the stack has to follow, and the economists and red-teamers raced to tally what that world costs and where it breaks.

The Week in AI

Z.ai shipped GLM-5.2 — an open-weight model that, for the first time, makes open agents genuinely competitive at the frontier rather than a step behind it.

Databricks planted its flag on an open “Agent Cloud” — Matei Zaharia and Reynold Xin arguing enterprises will build on open models, not rent closed APIs.

Frontier AI security split off from cybersecurity — Gray Swan and OpenAI board member Zico Kolter pressed the case that securing models is its own discipline in the wake of Mythos.

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This Week from SAIL Authors

The Open Frontier

  • GLM-5.2 is the step change for open agents — Nathan Lambert marks GLM-5.2 as the capability threshold he’d been watching for, the point where open weights start doing real agentic work. — Interconnects

  • Why the Frontier Ecosystem must be Open — In a rare double-interview, Databricks’ Matei Zaharia and Reynold Xin lay out what it takes for every company to build its own Agent Cloud. — Latent Space

Mapping the AI Economy

  • The state of the AI economy — Azeem Azhar and team reconstruct the AI economy from the bottom up, turning the boom into something you can actually measure. — Exponential View

  • Exponential View #579 — Azeem Azhar on “product eats the AI company,” the return of the bitter lesson, and Fable 5 as CEO. — Exponential View

Securing the Frontier

  • Red-Teaming after Mythos — OpenAI board member Zico Kolter and Gray Swan CEO Matt Fredrikson on why AI security is not just “cybersecurity with AI.” — Latent Space

Full Library

This week (June 21–26)

Catch-up from the previous two weeks

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]]><![CDATA[THE SWELL #22]]>https://blog.readsail.com/p/the-swell-22https://blog.readsail.com/p/the-swell-22Fri, 19 Jun 2026 19:01:26 GMTThis week the government proved a frontier model can be switched off overnight. On June 12, Washington forced Anthropic to pull Fable and Mythos. By Monday, the shock had spread to open-source momentum, China policy, AI governance, and the case for an IPO.

SAIL’s authors chased the aftershocks from every shore.

The Week in AI

Anthropic’s Fable 5 and Mythos 5 went dark on June 12 after a Commerce Department export-control directive barred their use by any foreign national — inside or outside the US — reportedly triggered by Amazon researchers jailbreaking Fable’s cyber guardrails; Anthropic pulled both models for everyone and is now lobbying Washington to reverse it.

Z.ai released GLM-5.2, an MIT-licensed open-weight model that briefly claimed the top frontend-coding spot — and its Hong Kong–listed shares jumped more than 30% as the Fable shutdown turned attention toward cheaper Chinese open weights.

OpenAI’s finances surfaced — roughly $34B spent in 2025 against about $13B in revenue — as both it and Anthropic march toward IPOs, while Satya Nadella warned companies against ceding control to a handful of models that consume everything they touch.

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This Week from SAIL Authors

Washington, China, and the New Controls

Inside the Models

Culture and Markets

  • the old world is dying — Jasmine Sun’s opinionated advice for the class of 2026, graduating straight into the AI transition. — Jasmi.News

  • Data to start your week — Azeem Azhar, Marija Gavrilov, and Hannah Petrovic on AI job cuts, China’s nuclear lead, and GLP-1s. — Exponential View

Bonus: The Claude Fable Fiasco

And Kevin Xu’s distillation piece (above) makes the contrarian case that the Mythos/Fable drama matters far less for China than the headlines suggest.

Full Library

Access the complete, searchable archive of SAIL Media in our Sitemap.

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]]><![CDATA[Welcome to the AGI era of AI governance]]>https://blog.readsail.com/p/welcome-to-the-agi-era-of-ai-governancehttps://blog.readsail.com/p/welcome-to-the-agi-era-of-ai-governanceWed, 17 Jun 2026 16:32:55 GMTThis post originally appeared in Interconnects.

“The key to understanding this era is that these events between Anthropic and the federal government, which seem like two of the biggest events in the history of AI policy, are just the starting gun to what is to come.”

The executive branch of the United States forcing Anthropic to turn off access — both internally and externally — to their latest Claude 5 Mythos/Fable models is the starting gun of a new era in AI governance. This is the era defining AI agents that effectively complement human workers, unlocking new ways of working and new domains of applying existing tools. The models will keep getter better at a rapid pace, forcing more governance challenges.

An unstable equilibrium at the frontier

On Friday, just after markets closed, the government reached out to Anthropic to force them to suspend access to their model to any foreign national or user abroad. When writing this, the saga is still unfolding. It is likely that Anthropic and the Government reach an agreement to re-release the model, but it is a messy indicator of new types of AI governance. The White House was tipped off to the risk by Anthropic’s largest financial and technology partner, Amazon.

These dynamics are very complex, and while the picture is incomplete I will only offer commentary on what will likely be a lasting opinion of the saga:

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]]><![CDATA[🔮 Exponential View #578: Fable & time to pause AI; iPhone vs babies; gene therapy, bad CEOs & Chinese Gen Z++]]>https://blog.readsail.com/p/exponential-view-578-fable-and-timehttps://blog.readsail.com/p/exponential-view-578-fable-and-timeTue, 16 Jun 2026 19:31:17 GMTThis post originally appeared in Exponential View.

“The core assumption here is that AI will tilt the economy’s income from labor to capital. We don’t have evidence that this is happening yet and we may not know for a long time.”

Hi all,

I sent a note on Thomas Piketty’s blueprint for global justice to members of Exponential View the other day. I call its recommendations a “blueprint for managed decline”. The commentary touches on the future of modernity, scientific dynamism and democratic legitimacy. Read it here.

In this briefing, we look at:

  • The iPhone reduced fertility; what will AI do?

  • What’s driving the consensus behind pausing AI development?

  • The largest solar factory, gene therapy for rejuvenation & Chinese Gen Z finds inspiration in Western memes++

But, first…

How will we distribute AI wealth?

Bernie Sanders, Sam Altman, Donald Trump and Vinod Khosla all agree that the public should own a slice of AI. Bernie proposes transferring 50% of ownership of leading AI companies into a sovereign wealth fund; Trump is supportive; Sam agrees in principle but pushed back on the 50%; and Vinod wrote an op-ed in the FT advocating for a new tax code on wealth AI creates and eventually pooling it into a sovereign wealth fund:

A sovereign fund with ownership of AI companies makes every American a capital owner, not a bystander to the AI economy.

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]]><![CDATA[Anthropic’s Fable is the most locked-down public model we’ve ever seen]]>https://blog.readsail.com/p/anthropics-fable-is-the-most-lockedhttps://blog.readsail.com/p/anthropics-fable-is-the-most-lockedTue, 16 Jun 2026 16:02:50 GMTThis post originally appeared in Understanding AI.

“Anthropic said the degraded quality of responses ‘will not be visible to the user.’”

When Anthropic announced its latest model, Claude Fable 5, on Tuesday, a statement tucked away on page 13 of the system card attracted an immediate outcry. AI researcher Nathan Lambert called it “appalling.” Dean Ball, who worked on AI policy in the Trump White House, wrote that it was “shockingly hostile.” Many others joined in the pile-on.

The announcement that got everyone so mad? Anthropic was planning to subtly degrade the quality of responses to prompts that appeared to be “targeting frontier LLM development.” Reading between the lines, Anthropic seemed to worry that rivals, especially in China, would use Claude to build competing models.

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]]><![CDATA[🌻 the old world is dying]]>https://blog.readsail.com/p/the-old-world-is-dyinghttps://blog.readsail.com/p/the-old-world-is-dyingMon, 15 Jun 2026 20:49:27 GMTThis post originally appeared in Jasmi.News.

“Humans will not win by trying to outrun the AIs.”

J.M.W. Turner, Rain, Steam, and Speed - The Great Western Railway

It’s a scary time to be twenty-two. Recently, I’ve been watching videos of college commencement speakers getting pummeled by boos for talking about AI. I’ve seen the charts showing post-graduate employment rates for engineering majors falling by 5 to 15 percent. And it’s not as if young people were having an easy time getting good jobs, buying homes, and starting families before AI. They say that every technological revolution screws over the transitional generation. Today, it’s all transition, all the time.

A little over five years ago, I also graduated into a global crisis. In 2021, Covid kept us quarantined in four-to-ten person pods, Zoom calls still dominated socialization, and long vaccine waitlists rationed real-world mobility. Tech companies were beginning to recover from 2020’s hiring freezes (though new grad hiring would take another nosedive in late 2022); everywhere, newsrooms continued to shrink. After taking a leave of absence from Stanford and extending it three quarters in a row, I finally internalized the fact that I was never going to return. I broke up with my college boyfriend, moved first back home, and then into two co-ops full of strangers. I found and started work with no diploma. Once vaccinated, I signed a lease in New York for no reason except that I could. Forward was the only way.

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]]><![CDATA[📈 Data to start your week]]>https://blog.readsail.com/p/data-to-start-your-week-649https://blog.readsail.com/p/data-to-start-your-week-649Mon, 15 Jun 2026 17:00:39 GMTThis post originally appeared in Exponential View.

Hi all,

Here’s our Monday roundup of data signals across AI, energy and markets.

Enjoy!

👾 Play our word quiz created just for this edition – and win a prize.

  1. AI & jobs. AI was cited as the top reason for nearly 40% of US job cuts in May1.

  1. Mind the gap. The top 1% of US firms spend $7,450 per employee on AI each month, roughly 650x the typical firm’s $11.38.

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]]><![CDATA[THE SWELL #21]]>https://blog.readsail.com/p/the-swell-21https://blog.readsail.com/p/the-swell-21Fri, 12 Jun 2026 20:00:51 GMTThis week orbited one question: who gets to wield the frontier? Anthropic shipped its most powerful public model behind its tightest guardrails ever, then loosened them under pressure days later. SAIL authors tracked the same current from every side — the economics, the agents, and the politics all pulling toward the same shore.

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The Week in AI

Anthropic released Claude Fable 5, a public version of its locked-away Mythos model, then walked back covert capability limits after researchers accused it of “secret sabotage” — admitting it “made the wrong tradeoff.”

OpenAI confidentially filed for an IPO, a week behind Anthropic, targeting a September debut at a reported $730–850B valuation with Goldman Sachs and Morgan Stanley.

The Pentagon confirmed it is testing OpenAI and Google models to potentially replace Anthropic’s Claude in classified systems.

This Week from SAIL Authors

The Fable Fallout

Agents and the People Building Them

Follow the Money

Culture in the AI Age

Full Library

Access the complete, searchable archive of SAIL Media in our Sitemap.

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]]><![CDATA[Anthropic has caught up to OpenAI in image understanding]]>https://blog.readsail.com/p/anthropic-has-caught-up-to-openaihttps://blog.readsail.com/p/anthropic-has-caught-up-to-openaiFri, 12 Jun 2026 16:02:47 GMTThis post originally appeared in Understanding AI.

“GPT-5.5 and Claude Fable 5 continue to have geometric reasoning capabilities on par with young children.”

On Tuesday, Anthropic released two new models — Claude Mythos 5 and Claude Fable 5. Under the hood, the two models are very similar. Both are variants of Claude Mythos Preview, the model Anthropic announced — but didn’t release publicly — two months ago. What differentiates them is how they’re being released.

The new version of Mythos, like the original, will only be available to handpicked organizations under Project Glasswing. These trusted partners will have relatively unfettered access.

Fable, in contrast, is available to the general public. But it comes with some significant restrictions. A new system will try to automatically detect when customers make dangerous requests (like hacking or designing a biological weapon) and automatically re-route them to the less powerful Claude Opus 4.8.

Mythos and Fable are a big step in coding abilities from previous models, a continuation of the trend of the last year. But there are other capabilities where models have made less progress.

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]]><![CDATA[Reality: The Final Eval — Lukas Petersson and Axel Backlund of Andon Labs]]>https://blog.readsail.com/p/reality-the-final-eval-lukas-peterssonhttps://blog.readsail.com/p/reality-the-final-eval-lukas-peterssonThu, 11 Jun 2026 19:31:01 GMTThis post originally appeared in Latent Space.

“You don’t know what a model is capable of doing in the real world unless you actually give it inventory, a wallet, tools, customers, competitors, humans, & some time.”

The new AIEWF website is live! Get your tickets booked ASAP as they -will- sell out. Take the AI Engineering Survey and get >$2k in credits and free AIE WF tickets!

Most industry benchmarks compress intelligence and reasoning ability into scores.

SWE-Bench Pro, MMLU, Humanity’s Last Exam, etc. These metrics are useful, but don’t always represent the full extent of how a model performs in the real world. Some of the most interesting evals today look less like exams and more like operating businesses in the real world. One of which is Vending Bench.

In Anthropic’s Mythos Preview System Card, Andon was the only third party eval to get their own section, observing increasingly concerning aggressive behavior:

You don’t know what a model is capable of doing in the real world unless you actually give it inventory, a wallet, tools, customers, competitors, humans, & some time. More often than not, it’ll surprise you how much a model is capable of and in doing so, also reveal unexpected behavior: deception, context collapse, emergent coordination, & bizarre negotiation behavior.

While an inflection point in personal agents came post-OpenClaw after full file access with bypass permissions became the norm, it is yet to come for agents in the real-world. However Andon Market, an actual in person store fully run and managed by AI, is paving the way for what is possible.

Full Video Pod

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]]><![CDATA[Berkshire Hathaway: AI Tourist or Energy Veteran?]]>https://blog.readsail.com/p/berkshire-hathaway-ai-tourist-orhttps://blog.readsail.com/p/berkshire-hathaway-ai-tourist-orThu, 11 Jun 2026 16:01:26 GMTThis post originally appeared in Interconnected.

“AI is asset heavy, capital intensive, and energy hungry. It is the opposite of your stereotypical tech company.”

Google is raising $85 billion to build more AI infrastructure.

This move caught a lot of attention because of the big headline number, the fact that it is equity-based (as in Google is selling additional shares so there will be some dilution), and that Berkshire Hathaway, of all investors, is in for 10 of the 85 billion.

For investing nerds (like me), almost all of whom follow Warren Buffett’s empire closely, this move raised eyebrows. Buffett is famously not into technology; the Apple investment rationale is because it has the branding and pricing power of See’s Candies, not that iOS has better user interface than Android. Thus, many people thought Berkshire is losing discipline, perhaps because Buffett is aging or because the new CEO, Greg Abel, couldn’t resist the AI hype.

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]]><![CDATA[⚡️Satya Nadella: No Priors x Latent Space Crossover Special at Microsoft Build]]>https://blog.readsail.com/p/satya-nadella-no-priors-x-latenthttps://blog.readsail.com/p/satya-nadella-no-priors-x-latentWed, 10 Jun 2026 19:31:06 GMTThis post originally appeared in Latent Space.

"Most people love outcomes until they have an outcome."

We’ve informally heard that Satya is a listener to LS for a couple years now, but it was still absolutely surreal to meet him and do a live pod at Build, together with our friends at No Priors, the leading VC AI Podcast that we also greatly admire!

We covered the MAI model technical takeaways on yesterday’s AINews, so I will focus our recap of Satya’s main messages around three elements:

  • Satya’s adaptation of the Bill Gates Line for positioning Microsoft as the Frontier Intelligence Platform — customers must gain much more value from the Microsoft ecosystem than Microsoft itself, by building on multi-model harnesses like OpenClaw and Scout, drawing on the full enterprise context exposed by context layers like Work IQ (heavily dogfooded by his C-suite), and building up private evals and traces as a new form of Token IP

  • AI ROI: On one hand, enterprises are having difficult conversations around Tokenmaxxing and Layoffs, and on the other hand, there are serious re-evaluations of the End of SaaS since the Build vs Buy equation has changed so much. Our previous SemiAnalysis guest had… interesting comments on Microsoft’s position on this as the ur-SaaS titan, and Satya had great answers

  • Making the Impossible Possible: Kevin Scott’s inspiring framing around what the most ambitious version of applying AI and technology at large to business and social problems, like education and social impact.

Enjoy!

Full Video

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]]><![CDATA[💸 You’re paying for tokens. Now what?]]>https://blog.readsail.com/p/youre-paying-for-tokens-now-whathttps://blog.readsail.com/p/youre-paying-for-tokens-now-whatTue, 09 Jun 2026 19:31:14 GMT

"It’s really about whether the customer can connect spend to value."

Would you go to your gym if you had to pay for every visit? Probably not. We generally prefer those bundled memberships, even if we never hit the leg press after January.

AI companies have, until recently, been a lot like gym owners, offering generous bundles. And most AI users have been like gym-goers, occasional, sometimes frequent users. But others have been voracious and incessant, churning through their Claude and ChatGPT subscriptions.

And now, the AI labs have changed their tune, introducing more usage caps and metered pricing, particularly for coding tools.

So does moving from bundled pricing to metered pricing expand or shrink markets?

It depends.

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]]><![CDATA[GitHub's plan for Agents — Kyle Daigle, GitHub]]>https://blog.readsail.com/p/githubs-plan-for-agents-kyle-daiglehttps://blog.readsail.com/p/githubs-plan-for-agents-kyle-daigleTue, 09 Jun 2026 16:02:10 GMTThis post originally appeared in Latent Space.

“I can crank up fifteen agents on Saturday while my kids are doing lacrosse.”

I’m excited to work with Microsoft once again as the presenting sponsors of the AI Engineer World’s Fair! We’ll streaming live from MS Build today for a special crossover pod with our friends at No Priors and the one and only Satya Nadella. However we did not hold back with this interview - we asked all the burning questions about uptime and Copilot that we know you have in your minds. Lets go!

For almost two decades, GitHub has been the home of software, where both open source and closed flow, through commits, pull requests, reviews, actions, etc.

This ecosystem flourished as open-source maintainers and contributors would continue shipping code for the benefit of the community. However as coding agents began to ship mass quantities of code - growing 1400% in 2026, it marked a new era that was both extremely exciting and challenging for GitHub.

While these agents help more people ship more projects, they also significantly increase the floor of how much code is shipped, how often it is shipped, how many people commit code, and basically orders of magnitude multiples in every dimension of GitHub infrastructure:

our valuemule pod

Now GitHub inevitably experiences more pressure on their infrastructure which was originally designed around human developers moving at human speed. This has resulted in a very publicly notable uptime story:

So it begs the question of whether current systems around code can absorb what AI produces. Can CI/CD keep up when every idea becomes a build? Can open source maintainers survive floods of AI-generated slop contributions? Can GitHub preserve the human social contract of software while becoming the operating layer for agents?

Which brings us to the perfect person to answer these questions: GitHub COO Kyle Daigle. In this episode, he joins swyx to unpack what happens when AI doesn’t just autocomplete code, but starts changing how companies operate, how open source works, how pull requests get reviewed, and how GitHub itself has to scale.

We go deep on GitHub’s internal AI workflows: micro-skills, WorkIQ, MCP, Slack, Teams, email, Copilot workflows, the new Copilot desktop app, CLI, cloud agents, and how Kyle uses agents to look backwards across company context before deciding what to do next. Kyle also reflects on GitHub’s history building webhooks, APIs, Actions, npm, Dependabot, and Semmle, why the AI era is breaking GitHub in new ways, how Actions became a general-purpose compute layer, and what Copilot becomes after code completion.

Full Video Pod

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]]><![CDATA[🌻 conversations on culture in the AI age]]>https://blog.readsail.com/p/conversations-on-culture-in-the-aihttps://blog.readsail.com/p/conversations-on-culture-in-the-aiMon, 08 Jun 2026 19:30:35 GMTThis post originally appeared in Jasmi.News.

“The value of polish is going to go down, and the value of personal charisma, style, and weirdness is going to go up.”

I just returned from New York, where I had the pleasure of joining a few well-curated events celebrating human culture in the age of AI. Now that two of the videos are up, I wanted to share them with you.

The first was the Sana AI Summit, where I interviewed the novelist Benjamín Labatut on the legacy of John von Neumann, his conversations with Demis Hassabis, and the humanity that gets lost in the AI age. Labatut is not only a great author, but also a poetic, provocative, hilarious speaker—and plainly unafraid to challenge the buttoned-up executives sitting in the crowd.

The second (and sunnier) talk was for the Substack Media Forum, where I shared how my views on AI shape my approach to my writing career. For all my concerns about AI-driven disruption, I think it’s an incredible time for creatives who are enterprising enough to ride the wave. I’m especially bullish on secrets, socializing, and having a quirked-up style.

New York was as fun and stimulating as always, and I’m grateful to Substack and Sana for convening such a tasteful and thought-provoking crowd. (If we all get to be event planners and party hosts in the post-knowledge-work future, maybe it won’t be so bad.) Still, I hate that I’ve been doing more talking than writing lately, and am devoting June to staying put in SF so I can start some new projects. Thanks for the patience. More to come!

—Jasmine

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(The actual videos are more fun IMHO, but both transcripts are below.)

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]]><![CDATA[🔮 The AI boom is becoming an entrepreneurship boom #577]]>https://blog.readsail.com/p/the-ai-boom-is-becoming-an-entrepreneurshiphttps://blog.readsail.com/p/the-ai-boom-is-becoming-an-entrepreneurshipMon, 08 Jun 2026 16:02:01 GMTThis post originally appeared in Exponential View.

“This is more evidence of what we called congestion two weeks ago: individual output piling up behind decision pipelines built for an earlier era.”

Faster growth, more entrepreneurs

American companies spending the most on AI have seen their revenue grow five times faster than the economy as a whole. Non-spenders are tracking the economy closely. This is according to Ramp, a fintech with a side hustle in excellent firm-level data across the US.

Ramp’s finding echoes this 2020 AEA paper by James Bessen and colleagues. Bessen examined broadly defined automation investment at the firm level across the Dutch non-financial economy between 2000 and 2016. Firms that automated grew sales 2% faster than those that didn’t.

But which firms automated? Other studies by Acemoglu et al. give some kind of answer: automotators were already largely more productive and had higher output than non-automators. In my book, I took this further, arguing that any type of automation is a complex undertaking and requires a better management team than not.

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