🤖 AI coding

Monitoring the situation

A good way to stay abreast of AI tooling: Rands Leadership Slack #ai-coding-tools

Document driven (need link)
An iterative approach that makes your genie less insane over time Stdlib from Ghuntley (Cursor). No longer available to nonsubscribers, but the basic idea is to pay attention to your workflow each time, instead of just banging your head against the wall.
A structured approach to coding by Ryan Carson. For Cursor but generally relevant.
Kent Beck described a TDD and tidy first approach he calls augmented coding.
Vibe engineering describes patterns for those who are building high quality code quickly with AI.
Why AI swarms can’t build architecture and what to do about that.
Consider using ast-grep for larger codebases (and also this tool looks amazing).
Potential tooling for reducing duplication in code: jscpd, pylint for Python, dupl for Go.

Humans ON the loop Articulates a lot of the direction my thinking has been going around where a lot of engineering focus will probably be. Must read.
Stripe’s Minions show a workflow for creating pull requests in a large codebase, triggered by Slack. Part 2 goes into some detail of how it works. Most interesting part is the orchestration and how it separates deterministic and LLM based approaches. It’s a mostly one-shot approach, and suffers a bit because of that. But very interesting!
How to kill code review from a biased source who founded Aviator, but an interesting take on using BDD and deterministic tooling to constraint coding agents.
Intercom on AI approval of PRs. 19% of PRs approved by AI. Note I think their metrics are bogus, since of course the easiest and safest PRs will be reviewed by AI. Some nice approaches to how they did it, however.
Harness engineering for coding agent users. Describes some useful concepts for understanding how to engineer more reliably with coding agents.
Dark factories this post is mostly alright but the point I found useful is the concept of “dark factories”, factories where you are not designing for people but machines.

The Gap Through Which We Praise the Machine on usability issues in agent coding, and why some people seem to be doing well and others aren’t.
Nobody codes here anymore A case study on adoption

Revenge of the Junior Developer - Steve Yegge (who has a vested interest in this) lays out his vision of where this is going: agents, agent fleets, etc. March 2025.

Should probably have its own page