There was a stretch of time when writing code felt like holding a lottery ticket that kept winning. Companies couldn’t hire fast enough. Recruiters spammed your inbox like it was a contest. Compensation packages looked unreal, and nobody wanted to say out loud that it might not make sense for the long run.
If you were in the industry then, you remember what it felt like. You could jump teams, switch companies, negotiate without sweating. The whole thing ran on this belief that the future was obvious and we’d just ride it forever. Infinite growth. Infinite headcount. Infinite snacks. Even the office plants seemed optimistic.
That version of the industry is gone. Nobody issued a statement about it. It just faded out while everyone pretended not to notice. — Read More
Daily Archives: June 4, 2026
Running an AI-native engineering org
At Code w/ Claude SF 2026, Director of Engineering for Claude Code and Claude Cowork Fiona Fung walked through how the team’s processes and structure changed once agentic coding became the default way of working.
On the Claude Code team, writing code, writing tests, and refactoring rarely slows us down anymore. But the bottlenecks didn’t go away when agentic coding took away the actual need to type code. Verification, code review, and security took their place. … “How are humans keeping up with how you’re doing code reviews?” — Read More
A Functional Taxonomy of World Models
The world is not made of words.
In an earlier essay, we argued that spatial intelligence is AI’s next frontier and that world models are the path to it. Here, the World Labs team and I want to go one level deeper: of the many things now being built and called ‘world models,’ which functional pieces actually compose that capacity — and what is each one for?
… The ancient Greeks could never agree on what the world was made of, whether fire, water, or indivisible atoms, because “world” was never a single thing. It was always a stand-in for whatever totality a given thinker needed to reason about. AI has inherited the same problem, at exactly the moment when the field needs precision. — Read More
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