The processes that got you here will eventually constrain you. Like a lobster shedding its shell, scaling companies must periodically dismantle what worked intentionally, not in panic. Constraints aren’t a failure; they’re proof you’ve outgrown your current structure.
The fastest way to learn agentic development is to stop studying it: move in, extract repeatable patterns into skills, and reflect to compound.
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
LLMs are built for conversation, not incantations. The value isn't in your opening message, it's in the back-and-forth: clarifying, correcting, refining. Iteration is cheap. The conversation is the work.
Founders juggle endless demands, investors, sales, suppliers, and employees, all while building the plane mid-flight. But with engineering often being your biggest expense, there's one responsibility you can't delegate: ensuring your team builds the right thing.
AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.
Here's part one of a post I shared with our team on the radical change and evolution of our jobs. AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.
Reflecting on whether teaching traditional coding skills still makes sense in 2026. Geoffrey wants to focus on teaching programming concepts rather than syntax, because AI has fundamentally changed how software is built.
By 2030, nobody will write code anymore and here is why. The difference between agent-powered engineers and those who handcraft code is huge. Here's our prediction on software engineering.