Donald Bough

I'm now able to tell my agent “we are going to work on JIRA-1234” and it goes and pulls down the task, makes me a plan, I say yeah okay that looks good, and it generates the commit. I run an AI review from a different session, it finds 4 issues of varying priorities, I paste it to my original agent and say validate these findings and fix them if necessary, it creates a fix, I run another review, no more high priority issues found. I open up the code in an IDE to go over it before pushing it up for human review. Looks fine I guess, nothing crazy. I try to understand everything before I push it up for review because if this breaks, it's still my name on it. I say why did you make this one change, it gives me a reasonable explanation for why. It says something codebaity like "if you want I can suggest 2 more ways you could really tighten up this work to prevent some rare but possible regressions". I'm smart enough to not fall for it. Code pushed up, task moved to in-review. I didn't write any of it, this is not my accomplishment. Users won't care who wrote it if it works. A lot done in 20 mins but it felt soulless.

codex with 5.3 taught me something that won't leave my head. i had it take notes on itself. just a scratch pad in my repo. every session it logs what it got wrong, what i corrected, what worked and what didn't. you can even plan the scratch pad document with codex itself. tell it "build a file where you track your mistakes and what i like." it writes its own learning framework. then you just work. session one is normal. session two it's checking its own notes. session three it's fixing things before i catch them. by session five it's a different tool. not better autocomplete. it's something else. it's updating what it knows from experience. from fucking up and writing it down. baby continual learning in a markdown file on my laptop. the pattern works for anything. writing. research. legal. medical reasoning. give any ai a scratch pad of its own errors and watch what happens when that context stacks over days and weeks. the compounding gains are just hard to convey here tbh. right now coders are the only ones feeling this (mostly). everyone else is still on cold starts. but that window is closing. we keep waiting for agi like it's going to be a press conference. some lab coat walks out and says "we did it." it's not going to be that. it's going to be this. tools that remember where they failed and come back sharper. over and over and over. the ground is already moving. most people just haven't looked down yet.

AI coding agents produce syntactically correct code. However, they don’t produce useful layers of abstraction nor meaningful modularization. They don’t value conciseness or improving organization in a large code base. We have automated coding, but not software engineering. 10/

We are (not) forever young. 1 of 4

Hit Christmas gift this year: Stickerbox. Press button, describe something, AI generates an image and prints on a sticker. Great product design. We’ve printed hundreds of stickers so far. Made by one of my YC Summer 2009 batchmates!