Last night, while I was asleep, an AI agent spent the better part of eight hours writing code in one of my repositories. It pulled a task off a spec, wrote the code, ran the tests, and left a merge request with my name …
There’s a repair agent inside go-tool-base now. When you run gtb generate command, it doesn’t just spit out a file and wish you luck. An agent takes the generated code, builds it, runs the tests, and fixes whatever it …
I write a CLAUDE.md for every project I work on, and a small pile of other markdown files besides. They’re how I keep an AI agent on the rails: what the project is, what the conventions are, what it must never do. I lean …
Turn one, the player swings, the die comes up 20, and my AI dungeon master narrates the goblin falling silent, leaving the player alone in the corridor. Good. Turn two, another roll, a 6 this time, and the same dungeon …
Most AI code generation works on a charming little principle I’ll call generate-and-hope. The model writes the code, the model stops at the closing brace, and whether the thing actually compiles is left as an exercise …
An AI that can only produce text can describe your system. An AI that can call your Go functions can actually operate it. That gap, between describing and doing, is the difference between a chatbot and something …
