Running the same codebase for 10+ years with a small team is what finally made me fully internalize these rules.
I've always been a KISS/DRY person but over a decade there are plenty of moments where you're tempted to reach for a fancier database or rewrite something in a trendier stack. What's actually kept things running well at scale is boring, known technologies and only optimizing in the places where it actually matters.
I'm working on Chief [1], a CLI that autonomously works through a PRD using AI coding agents like Claude Code.
You write user stories, start it up, and it loops through them one at a time. Fresh context per story, progress tracked in markdown between iterations. One clean commit per completed story. Has a TUI for watching it work and supports running multiple PRDs in parallel via git worktrees.
Built it because a lot of the "autonomous coding" tooling out there felt overly complex and opaque. Chief is intentionally lightweight and transparent. Everything is just markdown files and git. No magic.
We are mainly B2B so we don't really see signups using Apple's email relay. That said, it could be something we might have to consider blocking in the future if it becomes a problem.
For paying customers, it probably doesn't make a lot of sense to use an anonymous email address, since we ask for your name and billing address either way (have to stay compliant with sales taxes!)
Isn't it nice to have just a little bit of an illustration instead of just text? Obviously an AI-generated image is going to spit out some nonsense text as part of the graphic, but we're not really trying to hide that it's AI generated.
I think things that require high credibility and have a learned readerbase it'd be better to not give a careless image, even at the cost of a cool image. I wouldn't mind an almost right image on some advert for cleanex or intranet holiday reminder mail, but I would be very concerned if it was used as part of EU directive
I've always been a KISS/DRY person but over a decade there are plenty of moments where you're tempted to reach for a fancier database or rewrite something in a trendier stack. What's actually kept things running well at scale is boring, known technologies and only optimizing in the places where it actually matters.
We wrote our principles down recently and it basically just reads like Pike's rules in different words: https://www.geocod.io/code-and-coordinates/2025-09-30-develo...
reply