Engineering Fundamentals in the Age of AI — Part 1: Organising for Flow
I've been spending a lot of time recently thinking about what an AI-native software engineering organisation should look like.
Firstly, some context. I'm all-in on AI engineering tooling. Claude Code, Codex, and the growing ecosystem of agentic development tools are incredible. The progress we've made in such a short space of time is very cool to see, and we're only scratching the surface of what's possible.
We've seen just how much these tools amplify great engineers. We're moving from engineers writing code, to engineers orchestrating multiple agents that are writing, testing, debugging and improving software autonomously. An engineer running 5-10 agents at once is happening regularly, and the amount of work that a capable engineer can get through is ridiculous.
I'm not going to spend this post convincing you of that. There are plenty of people writing about how to get the most out of Claude Code, how to structure your agents, how to optimise your harness, and which model is best at building GTA 6 this week.
What I want to talk about is something that unlocks a lot more value.
We're spending enormous amounts of time and energy making our engineers AI-native.
But are we making our organisations AI-native?