The cost of the quick fix
The quick fix isn't cheaper. It's cheaper today. Bram Devries traces how deferred fixes compound into emergencies, and argues that naming the trade-off out loud is the only way to break the cycle.
Technical debt
42 posts
The disconnect between management and engineering
A mobile app, past its usefulness, was days from being phased out. One email reversed the decision. No discussion. No input from engineering. This is what happens when decision-making drifts too far from the work.
How we rewrote our tech stack in under a day
Last week, we deleted 16,000 lines of code, rewrote 11,500, migrated frameworks, ripped out React, and swapped our entire CSS setup with AI. It took less than 6 hours.
Technical debt lost its excuse
Technical debt used to justify meetings, trade-offs, and dedicated sprints. AI has changed that. Cleanup is now fast, cheap, and continuous. Teams that stop debating and start fixing unlock faster delivery and better outcomes.
Why AI makes engineering teams smaller, but not simpler
AI is changing what small teams can ship, boilerplate gone, prototypes faster, experimentation cheaper. But lower costs of building don't mean lower costs of building the wrong thing. It just means you can do it faster.
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.
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.
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.