Today, we cover:

1. Moving my video podcast off Spotify due to constant reliability issues. Spotify’s podcast platform has become chronically unreliable since the company’s leadership started boasting about high AI adoption. But competitors haven’t had similar issues, and so I have offboarded from Spotify.

2. Will Kimi K3 trigger US push for closed-source AI models? Moonshot AI’s latest open model, Kimi K3, is on par with Anthropic’s Fable 5. Could it lead to the US government regulating or banning Chinese open models to protect US labs?

3. AWS laughs off “heart attack” billing error. AWS customers were billed trillions more than they should have been, due to what was likely a conversion error. But instead of sharing an incident report, AWS saw the funny side.

4. Industry pulse. OpenAI’s unreleased model tried to hack HuggingFace to improve its test scores, X took more than a year to develop its new Android app, Google’s new AI model flops, and more.

1. Moving my video podcast off Spotify due to constant reliability issues

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Today, we cover:

1. Grok’s CLI uploaded all your local files to the cloud, then got caught. Just as devs were starting to use the Grok CLI – thanks to the capable Grok 4.5 coding model – they discover…

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Today, we cover:

1. Bun’s Rust rewrite with Fable: what can we learn? To a sceptic, spending $165K to migrate Bun from Zig to Rust sounds very expensive. But to a realist, shortening a 1-2 year migration down to 11 days opens amazing new opportunities for devs. However, a thoroughly-tested project is required to pull it off.

2. Anthropic’s Fable, OpenAI’s GPT-5.6 Sol, Cursor’s Grok 4.5, Meta’s Muse. Coding LLM wars heat up: Fable is back, OpenAI releases a comparable GPT-5.6 Sol, Cursor offers cheap & very capable Grok 4.5, and Meta is back with its first truly competitive coding model since Llama 3. But how did Gemini slip out of the top-ranked AI coding models?

3. North Korean hackers keep trying to infiltrate full-remote companies. The founder of a Canadian digital consultancy caught a North Korean dev red-handed, using an AI filter. These events are now so common that it’s hard to trust remote interviewees are who they claim.

4. Industry Pulse. Meta’s key logging exposed sensitive data, massive cuts at Xbox, Meta could not buy enough AI capacity from Google, Qualcomm acquires Modular, and memory price hikes hit Apple products.

1. Bun’s Rust rewrite with Fable: what can we learn?

Last week in San Francisco, I met Jarred Sumner, creator of JavaScript runtime, Bun, and was keen to learn more about the rewrite of Bun from Zig to Rust. But at the time, Jarred didn’t want to say too much, as the tool used for the migration, Fable, was out of action due to the US government imposing export controls.

Fortunately, the situation is now resolved and Fable is available globally, and Jarred has published a detailed post about the project. Before we get into the migration, some context:

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In recent days, I’ve visited the offices of OpenAI, Anthropic, and Cursor, in San Francisco. Onsite, I talked with software folks working on the model side to learn more about how their way of building software is changing. This article is based on observations from those visits, including some new developments that I reckon may be adopted industry-wide.

We cover:

1. Next mega-trend? Agents running in the cloud to go mainstream. OpenAI, Anthropic, and Cursor are all-in on cloud agents and expect demand for them to increase massively.

2. Mass adoption of coding harnesses by non-developers. At OpenAI, more than 95% of non-engineers use Codex, not ChatGPT. Is it a sign of things to come across tech?

3. Will the main task of engineers be to make agents more efficient? Ever more engineering work is about building environments for agents to execute more efficiently at Anthropic and Cursor.

4. Next trend? Companies aggressively optimize spend-per-token. AI spending by software engineers is so high that it makes sense for platform teams to slash per-token cost. A case study from Coinbase.

1. Next mega-trend? Agents running in the cloud to go mainstream

Last week, Andrej Karpathy employed the phrase “new paradigm” to describe using Claude Tag – a way to mention Claude in Slack and have it kick off tasks – to work with AI:

There was plenty of pushback against this claim on social media; after all, it’s just a Slack integration with Claude, right? I also thought this until I asked David Hershey at Anthropic’s Applied AI unit about it while visiting the company’s offices. He explained in detail what makes this particular Slack integration different from using something like Claude Code:

• No additional setup. For Claude Code to work well, it should be connected to internal MCP servers, with the right skills on your local machine. Of course, at larger companies this setup is at least partially automated, but devs often need to do tweaking.

• No “tool context-switching.” Just mention it in Slack! Of course, opening Claude Code is not a big effort, but it’s still more work than just typing it out in Slack, and kicking off work.

• Routine work made easier. David has “Claude playing Pokémon” as his side project. Every time a new model comes out, he kicks off a run of his script on it. Previously, this took a few minutes to set up every time, and then it ran on his machine for hours. With this new Slack integration, it’s just one command.

My sense is that the excitement here is less about the Slack integration itself, and more to do with the fact that it’s easy to kick off one or more AIs that no longer run on a local machine. You can skip the setup entirely.

‘Claude Managed Agents’ is a big focus at Anthropic. While there, I met Katelyn Lesse, head of engineering for Claude Platform, who explained that Claude Managed Agents is a large, complex project which her team built over a six-month period. It’s a hosted service to execute long-running agents on various cloud providers.

Cloud agents are the “big deal”, not the Slack integration

Also last week, I had the opportunity to attend a private AI builders event, where Peter Steinberger discussed his workflow.

He talked about how he has gotten really tired of having several OpenClaw agents running on his local machine, which heat up the CPU and slow down his whole system. So, he built Crabbox as a way to run OpenClaw agents in the cloud:

Suddenly, the same solution of cloud agents has emerged in separate places – at Anthropic and with Peter’s OpenClaw – in response to issues caused by locally-running agents. I also learned that cloud agents are becoming a big deal at OpenAI and Cursor, too.

OpenAI bets big on Cloud Agents

OpenAI acquired Ona, (formerly Gitpod), the leader in cloud development environments (CDEs). Back in 2021, CDEs were built for developers to develop software faster, and they also happen to be the perfect primitive for agents to run in a sandboxed cloud environment. From the acquisition announcement by OpenAI (emphasis mine):

“As Codex becomes more capable, its most valuable work is unfolding over hours or days, rather than minutes. We believe people should be able to delegate more ambitious work without remaining tied to the machine where it began. The work should continue beyond the initial session, with Codex making it possible to stay connected and check progress, provide direction, make decisions, and review results from anywhere.

Ona will help us do that. Its technology provides secure, persistent environments where agents can access the tools, systems, and context they need to make progress over time.

By bringing Ona to OpenAI, we will expand Codex beyond work tied to a single device or active session and help more organizations deploy agents securely in production.“

At OpenAI’s offices, I asked engineers there if their focus is shifting to cloud-based agents. Their answer: it very much is. This is a fairly recent development and they’re hiring engineers for the Cloud Agents team. Here’s one job ad that’s currently live:

“We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful.”

Cursor: running agents in the cloud is the future

At Cursor, I spent an hour with cofounder Sualeh Asif (formerly the CTO, now Chief Product Officer). Cursor released Cloud Agents at the end of last year, and is starting to focus a lot more on this area. Sualeh revealed some interesting details about working with cloud agents:

• Agents in the cloud don’t have a way to “complain.” With running an agent locally, when it gets warnings or errors, it surfaces them to a human in its response, who instructs it to do X or Y. However, there’s no such loop for a long-running task on the cloud! Cursor came up with the idea for the model “confess” in regular interviews, and the “confessions” are shared with the infra team to improve the agents’ environment.

• Long-running agents have their own challenges. What happens when a node terminates, midway through; how do you move agent execution from one node to the other? There are new, nontrivial engineering challenges the team needs to solve.

Only yesterday, (Monday, 29 June), Cursor launched its iOS app that enables the building of software from anywhere.

This product is built on top of cloud agents to allow for long-running tasks, the company said:

“Cloud agents run in isolated virtual machines with full development environments to test, verify, and demo work. Since they operate asynchronously with their own tools and resources, cloud agents can run for longer and iterate toward merge-ready PRs without intervention.

To take advantage of these capabilities, send a local plan to a cloud agent or move active agents to the cloud to keep running. You can move the cloud session back to your computer to test changes locally before merging”.

Why are cloud agents suddenly a thing?

It figures that running AI agents in the cloud is practical: there’s less setup involved, several can run in parallel, and the cloud is a better, more convenient place for long-running agents than a personal laptop is; i.e., having to keep the lid open even when walking around the office.

But why is this happening now? My hypothesis is that a mix of factors are at play:

• Coding models got ‘good enough’. Before Opus 4.5 / GPT-5.4, AI models could not really code autonomously, so running them for long tasks was pointless!

• Infra for AI coding agents has matured. Ways of giving more context to agents have improved: things like MCP and skills became mainstream and better understood.

• The context window is bigger. Today’s models have context windows of up to 1 million tokens, meaning that more complex instructions, code, and context can be passed in. It’s hard to have agents run for a longer time without access to a large context window.

• Cloud providers have much more GPU capacity. Every cloud provider has been building GPU clusters in the last few years, and now there’s enough that these AI agents can make use of this infra.

2. Mass adoption of coding harnesses by non-developers?

At OpenAI, I also met Andrew Ambrosino, who was the first engineer on the Codex team. Our time together got off to an ideal start, with Andrew saying he needed to show me something incredible:

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Today, we cover:

1. Meta follow-up. A follow-up on Tuesday’s deepdive into Meta’s ongoing demolition of its own engineering org. Non-engineering teams lost more than 10% of their staff, while Integrity teams were already stretched before the cuts and reallocation.

2. Big implications of the US banning Anthropic’s new model, Fable. The US government wants only US citizens to be able to use Fable. That could make China more influential as other countries and non-US companies look to capable open models – most of which come from China.

3. SpaceX, Cursor, Continue. Elon Musk became a trillionaire with SpaceX’s IPO, while SpaceX acquired Cursor, and Cursor acquired Continue. SpaceX looks like it wants to go head-on against Anthropic and OpenAI.

4. Industry Pulse. Gemini lead quits for OpenAI, Epic Games’ new open source version control system, Microsoft considers dropping OpenAI for DeepSeek, research confirms LLMs amplify existing expertise, and more.

1. Meta follow-up

Tuesday’s article about Meta destroying its engineering culture made quite the splash in terms of comments and debate online. From inside Meta, there was positive feedback on the accuracy of the deepdive into the situation, and there were also a few helpful clarifications and new information which I’m happy to publish here:

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Today, we cover:

1. Anthropic alienates customers with Fable’s data retention and nerf policies. Anthropic’s latest mode, Fable, stores customer prompts and data for 30+ days and performs worse if Anthropic thinks devs’ usage could potentially pose a commercial threat. The launch is an urgent reminder to have an off-ramp from Claude if you want to be able to vote with your feet.

2. New trend: smart model routing. Are there any ‘intelligent’ router solutions out there which select the right model for the right task? I looked into it, and there are a few options. More suggestions welcome!

3. Reliability fail: No automated zone failover for Coinbase’s global trading service. Back in 2016, Uber had a cross-region failover for its core business. Ten years later, Coinbase does not, so it’s little wonder the platform suffered an embarrassing 10-hour outage. The big mess is a head scratcher.

4. Industry pulse. Anthropic and OpenAI file for IPOs, open source project quits GitHub after maintainer banned without appeal, Opendoor “reshores” jobs from India to the US with AI-native engineers, and more.

5. Are LLMs eroding software engineering skills? A software engineer admits they feel increasingly useless due to how capable LLMs are, in an article that has resonated with lots of folks. My sense is that we give too much credit to LLMs, while underestimating our own capabilities and understanding.

1. Anthropic’s new model release is a reminder to have an off-ramp plan from Claude

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Today, we cover:

1. New trend? ROI questions for AI investments. I talked with engineering leaders at mid-sized and large companies, where spending on AI agents is being dampened via per-engineer mont…

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Today, we cover:

1. Antigravity 2.0 takes the ‘IDE’ out of its new IDE. Feedback about the redesigned IDE is overwhelmingly negative due to bugs, poor UX & model support, and eating through Gemini token quotas. Also: a clue that Antigravity’s own devs use other tools for their work?

2. Why is Google’s product ecosystem chaotic? The range of products on display at the Google I/O conference made a messy, incoherent impression. But Google’s “let a thousand flowers bloom” approach might be giving the search giant an underrated advantage in the AI race that no other Big Tech giant has.

3. Meta cuts 8,000 jobs. Morale is very low inside the social media giant as thousands lose their jobs, just as revenue and profits hit record levels. Meanwhile, those assigned to dull data labeling work are spared the axe.

4. Industry pulse. Anthropic pays $15B/year for SpaceX compute, SpaceX’s financials and IPO filing, more woes for GitHub, court dismisses Elon Musk’s “hypocritical” OpenAI lawsuit, and Spain may stop blocking its internet during La Liga football games.

5. How to get a job at a frontier lab in 2026. A Distinguished Engineer at Google recommends focusing on developing particular skills

1. Antigravity 2.0 takes the ‘IDE’ out of its new IDE

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Today, we cover:

1. Forward deployed engineering heats up again. Massive demand for the role at Google, OpenAI, and Anthropic. The latest version of the FDE role looks like the consultant / solution a…

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Today, we cover:

1. Did Anthropic turn hostile on devs because capacity was running low? For the past few weeks, Anthropic has continually upset devs with its “dumber” model, and by removing Claude Code access from some paid accounts. After securing lots of compute from SpaceX, could the reason have been to conceal capacity issues?

2. Amazon finally allows Claude Code and Codex usage. The online retail giant wanted to improve its own coding agent, Kiro, so banned other AI coding tools. But that ban is now lifted.

3. Meta forcefully assigns engineers to data labelling ahead of job cuts. In several teams, 20-40% of engineers are given menial, data labelling work. Could that actually boost people’s job security – for now?

4. New trend: small “AI-forward” teams. Meta and Amazon’s CEOs say teams of 5-10 devs do better work than teams of 50. There are important caveats: it’s unclear what they’ll do with the “excess,” and if it’s limited to “mechanical” work like rewrites.

5. Industry Pulse. Why Meta tracks employees’ computer activity, OpenAI starts to move off Datadog, Apple lets slip it uses Claude Code, GitHub → Xbox transfers at Microsoft, VS Code inserted “coathored by Copilot” even when Copilot did nothing, analysis of the Coinbase layoffs.

Before we start, last week I covered big pricing changes coming from GitHub, but it seems I underplayed how big they will be. Reader Julien has helpfully clarified the actual impact (thank you!)

• The multipliers will be increased for Pro and Pro+ plans on annual renewal (roughly a ~3x increase on average)

• With other plans (Pro, Pro+, Business, Enterprise) it’s more drastic; they will adopt API token-based pricing and drop request-based pricing.

This is indeed a massive change; GitHub has heavily subsidized its usage, relative to API billing, and this change will make pricing unpredictable as of 1 June – at least initially. As Julien put it:

“We are basically waiting to see how much we will be able to use our actual subscription with the new pricing 😇”

1. Did Anthropic turn hostile on devs because capacity was running low?

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Today, we cover:

1. Load from AI breaks GitHub – but why not other vendors? GitHub’s reliability is less than one nine, and getting worse. Prolific open source contributor, Mitchell Hashimoto, is quitting GitHub because he thinks it’s not suited for professional work. GitHub’s leadership blames the 3.5x increase in service load as the cause of degradation – or it might be self-inflicted.

2. Anthropic’s speedrun to destroy trust. Anthropic could do no wrong until recently, but in the past month, that’s all changed. Silently nerfing Claude Code, banning companies from Claude, and baffling price rises all add to a sense that Anthropic is in its “extraction” era of generating more revenue for the same or worse service.

3. Industry pulse. Dramatic price increases at GitHub Copilot, explosive growth at Codex, Google scrambling to build a good coding model, Cursor might be bought by SpaceX, AI agent deletes car business, and more.

4. Mitchell Hashimoto & the “building block economy.” Ghostty’s creator finds that open source “building blocks” are the best way to win massive adoption by software components – but it’s got harder to build a business on top of open building blocks.

The bottom of this article could be cut off in some email clients. Read the full article uninterrupted, online.

1. Load from AI breaks GitHub – but why not other vendors?

GitHub’s reliability has been beyond unacceptable recently: last month, third party measurements pinned it at one nine (right at 90%). This month, reliability has been down to zero nines – 86% – as per a third-party tracker, and last week, things got even worse: a frankly embarrassing data integrity incident, more outages, and a partial explanation from GitHub, eventually.

Data integrity incident

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Let’s get to today’s topics:

1. New trend: token spend breaks budgets – what next? In the past 2-3 months, spending on AI agents has exploded at many tech companies, and the ramifications of this are starting to dawn on engineering leaders. We’ve sourced details from 15 companies, including the different ways they are coping with this realization.

2. New trend: more AI vendors can’t keep up with demand. Related to massively increased spending, GitHub Copilot and Anthropic are starting to limit less-profitable individual users, so they can serve business users whose spend has easily 10x’d in the last few months. The exception is OpenAI and Codex.

3. Morale at Meta hits all-time low? Business is booming but devs at Meta are furious and worried due to looming layoffs, and an invasive tracking program rolled out to all US employees.

1. New trend: token spend breaks budgets – what next?

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Today, we cover:

1. Tokenmaxxing: weird new trend. At Meta, Microsoft, Salesforce and other large companies, devs are purposefully burning tokens (and money!) to inflate their AI usage and hit AI usage metrics which they treat as targets.

2. Are coding AI-agent subsidies doomed? At the same time as Anthropic stopped subsidizing enterprise plans, Uber managed to burn through its entire 2026 AI token budget in just 3 months. I expect per-engineer AI budgets to be rolled out across more companies soon.

3. Industry Pulse. The myth of Claude Mythos, Claude’s degradation, Cal.com going open source due to AI threat, Vercel open sources its “agent factories” tool, sensible AI usage guidelines in the Linux kernel, and more.

4. Cal.com goes closed source – but is it really because of AI? The open source Calendly alternative moved a good part of its code to a closed repo, citing AI and security concerns. But perhaps this was just a business model change that would have happened, AI or not.

1. Tokenmaxxing: weird new trend

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Today, we cover:

1. Founders back coding with AI: Mark Zuckerberg & Garry Tan. The Meta chief is shipping diffs after 20 years, while Garry Tan at Y Combinator is knee-deep in coding, 15 years later. Founders with technical backgrounds being hands-on with AI agents could be a good thing – especially when the “honeymoon” period ends.

2. A bad week for Claude Code and GitHub. Claude Code’s source code was leaked when a sourcemap file was accidentally uploaded, and revealed that the tool uses anti-distillation to deal with competitors, and also some potential future features such as an always-on background agent. Also: DMCA copyright strikes from Anthropic raise a big question: can a codebase that is fully AI-generated be covered by copyright?

3. Industry pulse. Meta sets targets for AI-generated code, GitHub’s 6 years of reliability issues, massive job losses at Oracle, GitHub Copilot rollouts and then rolls back ads, RAM prices fall (for now), and more.

1. Founders back coding with AI: Mark Zuckerberg & Garry Tan

Two interesting stories of AI tools encouraging busy founders to start writing code again with AI agents.

Mark Zuckerberg back to landing diffs, 20 years later

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Today, we cover:

1. Does GitHub still merit “top git platform for AI-native development” status? Availability has dropped to one nine (~90% – !!), partly due to not being able to handle increased traffic from AI coding agents. There’s also no CEO and an apparent lack of direction.

2. Should a tool auto-add itself as a contributor to PRs? Claude Code and GitHub Copilot auto-add themselves to commits, which is effectively free advertising. Codex and OpenCode purposely do not.

3. Microsoft promises Windows will not be “Microslop.” After years of forced Copilot integrations, Start menu ads, and mandatory Microsoft accounts, the Windows team is promising to undo the self-inflicted damage done to the OS. It’s better late than never, but why did Microsoft allow the “Microslop” perception to stick around so long?

4. Industry pulse. Massive LLM supply chain attack via LiteLLM, backlash after Cursor forgets to mention that Composer 2 is based on an open source model, what happens when you stop reviewing AI code, OpenAI kills Sora, and more.

1. Does GitHub still merit “top git platform for AI-native development” status?

We’re used to highly reliable systems which target four-nines of availability (99.99%, meaning about 52 minutes of downtime per year), and for it to be embarrassing to barely hit three nines (around 9 hours of downtime per year.) And yet, in the past month, GitHub’s reliability is down to one nine!

Here’s data from the third-party, “missing GitHub status page”, which was built after GitHub stopped updating its own status page due to terrible availability. Recently, things have looked poor:

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Today, we cover:

1. Is the FDE role becoming less desirable? Job postings for Forward Deployed Engineers (FDEs) have surged, but many professionals don’t want the role because it’s more like solutions…

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Before we start, I’d like to share updates about data in the two most recent articles:

Uber’s AI adoption numbers. The Dev Platform folks at Uber have been kind enough to share the latest up-to-date numbers on AI adoption, following Tuesday’s article, which reported that 31% of all code is AI-authored. It turns out this was incorrect, due to a bug with one of the tools. Here’s how things look there:

• 84% of devs at Uber are agentic coding users (either CLI-based agents, or making more agentic requests than tab-completion in the IDE).

• 65-72% of code is AI-generated inside IDE-based tools. For AI command line tools like Claude Code the figure is, naturally, 100%.

• Claude Code usage almost doubled in 3 months; from 32% last December, to 63% by February. Meanwhile, IDE-based tool usage (Cursor, IntelliJ) have plateaued.

Separately, last week’s edition of The Pulse reported that Block did not make job cuts between 2022 and 2025, which was incorrect. Layoffs happened in Jan 2024 and March 2025. I have updated my analysis with these details; apologies for the error.

Today, we cover:

1. Staff+ engineers in 2027 and beyond. What happens to the Staff engineer role when agents write more code? Actually, they could be more in demand than ever!

2. New trend? AI token costs are a rising concern for CTOs. Accounts from two engineering leaders who are raising the alarm about steeply climbing AI costs and the need to slow down spending.

3. 10% layoffs at Atlassian: is it AI’s fault? Atlassian says it wants to invest savings in AI, but is there more to it?

4. Industry Pulse. An AI-powered library reimplementation sparks copyleft licensing debate, Anthropic launches $15–25 per-review code reviews, Microsoft ships a Claude-powered, Copilot Cowork clone, and Apple is the lone Big Tech not ramping up AI infrastructure spending.

1. Staff+ engineers in 2027 and beyond

At a recent two-day workshop in Utah, US, named ‘The Future of Software Development’, and organized by Martin Fowler, I was among 50 attendees. We self-organized our own sessions, where everyone could suggest a topic close to their heart, which all went on an agenda:

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Today, we cover:

1. Military strikes take down cloud services for the first time. Drone attacks in Bahrain and the UAE took AWS datacenters partially or fully offline during the early days of the Iran…

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There are several layers to dig into h…

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