Good context leads to good code: How we built an AI-Native Eng Culture
In this technical retrospective (2025), @waleedk shares practical architectural lessons learned from running, scaling, or migrating production software under lean constraints.
HN engineers debated the tradeoffs between cloud convenience and raw server economics, database indexing strategies, and resisting premature architectural complexity.
Thanks for the article, very insightful! I’m researching dev + AI workflows to build something to improve them. In your view, what’s the right granularity for storing and reusing context: A long file with lots of context per project? A small file with small bits of context per task? something in-between? And what type of context is useful for most workflows: stylistic preferences, intent, tech stack? Curious to know where you think context boundaries should actually sit to maximize usefulness without noise.
Author here. Happy to answer any questions you have.
I know the HackerNews crowd is anti-AI in the workforce overall, but I wanted to share a different approach which is optimizing for collaboration between humans and AI. This maps into certain practical things you can do, including things like how you structure your repo.