Credit to Dario who said pretty much exactly this would happen, and on this timeline, thanks to seeing what Mythos could do. In May, Dario said there's a 6-12 month window before Chinese models catch up was also correct. That was 5 months ago.

A middleware engineer in South Korea wrote to me, seeking help on what to do now that their manager is "blinded by GenAI hype" and set an "AI token usage" KPI. This eng is using v little AI, so manager is poking them to use more. My response: your manager is trying to help you

At Big Tech annual events like AWS Re:Invent, Microsoft BUILD, GitHub Universe etc these co’s sell sponsor booths for PARTNERS in their ecosystem. Cancelling a sponsor booth last minute is unheard of: and yes, it suggests AWS is shit scared of Cloudflare, as a COMPETITOR.

What do developer tools look like inside Uber, today? They are very different from what you would see at most places. We get a rare tour with one of Uber's longest-tenured engineers, Uday Kiran Medisetty (@udaykiran) - who was at Uber already when I joined in 2016! Timestamps: 00:00 Intro 02:48 Uday’s early days at Uber 05:40 Uber’s move to microservices 07:55 Uber’s engineering team, then and now 09:05 Developer tooling before AI 16:03 DevPods 19:28 Building for AI agents 29:27 MCP gateway 34:37 Agent Skills repo 38:46 The context graph and Cortana 47:54 PRD and ERD tool 50:45 Minion 54:46 Testing and code review with Bazel, Slate, and Capri 1:12:26 Edge Gateway, Shepherd, and Wisdom 1:21:33 The changing role of engineer and measuring productivity 1:30:40 Uday’s favorite new products Brought to you by: • @turbopuffer – The tpuf eng team is rebuilding their storage architecture from first principles to make search faster, cheaper, and more reliable at scale. Follow along at turbopuffer.com/v3 • @linear – the product development system for teams and agents. Check out Linear Diffs: a new feature to review PRs inside of Linear, with all the context in one place. linear.app/pragmatic • @WorkOS – how do you deal with agents and permissions? WorkOS built Airlock, the authorization layer for AI agents. Works with Claude Code, Codex and MCP gateways. workos.com/airlock Three things you probably did not know about Uber: 1. At Uber, cities are a first-class concept that go all the way down to physical infrastructure. One reason Uber had to build a lot of its custom tooling is how the concept of cities is a “basic primitive” that needs to be handled across systems like observability, feature flagging, deployments, and even service sharding. For example, in the early days, some services had their database sharded by cities. Even today, each city is pinned to a cloud region, and can fall over to another region at any time. 2. A single AI model gateway has paid lots of dividends. In 2023, Uber’s platform team made the decision that everything built with AI needs to be model- and harness-agnostic. They built Model Gateway to support switching between Anthropic, OpenAI, other vendor models, and now also supports open models they run. 3. Uber tags PRs by the type of work each of those PRs do. In the past, Uber measured “PR velocity:” how long it took for a PR (or, as Uber calls it: a “diff”) to get to production. With agents, doing so makes less sense, because it’s easy to create dozens or even hundreds of PRs, and many of those PRs might have no business impact on the product. ​So Uber now tags all PRs by type: feature, bugfix, maintenance, testing, or docs. ​They are seeing the percentage of “feature PRs” going up, and the percentage of “maintenance PRs” going down.​ I find this categorization to be a clever approach!

The AI-style interview fwiw is good and increasingly necessary just not as easy to “scale it” like DSA. DSA was always meant to be a filter for a mix of college education + willingness to learn something pointless Google will keep asking it in in-person settings / on sites for sure

My keynote at LDX3 New York, "The state of the tech industry in 2026". is out now. Timestamps: 00:00 Introduction 00:53 What changed 12:29 What's not changed 16:14 What broke 22:53 What’s next And for notes + slides, see: newsletter.pragmaticengineer… Hope it's useful!

FINALLY OpenAI has a response to Grok Bot, and it's called "dots" Grok Bot powered by Grok 4.6 (meh), this one by GPT-6 Astra (yay!) I will be trying it out. I'm surprised they gave SpaceX a 2-month headstart!