Posts with tag developer-workflow

I ran one model for everything and blamed the plan when usage climbed. The fix was splitting the work, and the saving turned out to have nothing to do with token price.


The rules are written down. The agent reads them on every prompt. They still do not make it into the code, and nothing is broken enough for the bot to report. A rules file is not configuration. It is a suggestion with an unknown success rate.

AI adoption doubled our code output. Nobody budgeted for the reading. Telemetry from 22,000 developers shows the bill: 5x longer review, tripled incidents, and 31% more PRs merged with no review at all. This is what treating review as infrastructure actually means.


Every company brags about their model's stats. Nobody tells you what you have to set up, and what you have to prompt, to actually hit those numbers. The hardest part of working with AI is the part no benchmark measures.

AI equalized the part of the job that was never the hard part — writing the code. The hard part was always knowing what to ask. That part it can't hand you, and worse, it hides the fact that you don't have it.

I committed code I hadn't read, felt the guilt, and almost filed it as a discipline problem. It wasn't. The gap between not trusting AI's code and not reading it is the clearest signal we have that the valuable part of the job moved downstream — from writing to reading.

Speed without reading creates technical debt. Here is exactly what I check when reviewing frontend code at data scale — and what AI keeps getting wrong.

AI can make developers faster. But speed without reading is just a faster way to create technical debt.