AI didn't change the economics of software engineering
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
Ideas
110 posts
Stop obsessing over the perfect prompt
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.
A founder's commitment to their engineering team
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.
The unbundling of engineering value (Part 2)
AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.
The unbundling of engineering value (Part 1)
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.
A letter to my son: Growing up in the AI world
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.
On the imminent retirement of the keyboard - the future of software engineering
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.
The hidden cost of multiple repositories
Go for one codebase or multiple repositories? A question multiple CTOs and technical founders have asked. It can be a surprisingly expensive decision nobody warns you about.
How AI is quietly killing open source
LLMs generate code on demand, but they do not replace maintainers, communities, or years of shared learning. This piece explores how AI-assisted coding risks fragmenting logic, increasing technical debt, and slowly eroding the open source ecosystem.