My fireside chat about agentic engineering at the Pragmatic Summit
Highlights
- ▸Five distinct AI-adoption stages for programmers — most of the industry is stuck between 'autocomplete user' and 'agent operator', and the gap matters
- ▸Debug the prompt before you debug the code — most 'the agent wrote buggy code' complaints trace back to an under-specified prompt, not a bad model
- ▸claude.md / skills files encode the conventions agents keep getting wrong — they're the lowest-effort fix for most recurring pain points
Original excerpt
Sponsored by: Honeycomb — AI agents behave unpredictably. Get the context you need to debug what actually happened. Read the blog
I was a speaker last month at the Pragmatic Summit in San Francisco, where I participated in a fireside chat session about Agentic Engineering hosted by Eric Lui from Statsig.
We started by talking about the different phases a software developer goes through in adopting AI coding tools.
I feel like there are different stages of AI adoption as a programmer. You start off with you’ve got ChatGPT and you ask it questions and occasionally it helps you out. And then the big step is when you move to the coding agents that are writing code for you—initially writing bits of…
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