Field notes from engineering.

Most AI projects don't fail in production — they fail in scoping. Here is the framework we use to turn a fuzzy 'add AI' request into a measurable, shippable plan.

The big rewrite is the most seductive and most dangerous decision in software. Here is how we decide between refactor, strangler-fig migration, and full rebuild — and why the answer is usually 'incremental.'

Postgres and Supabase are a fantastic default — until the table hits ten million rows and the connection pool melts. Here are the scaling realities the quickstarts skip.

Billing is where SaaS products quietly lose money — double charges, missed upgrades, silent failed renewals. Here are the architecture mistakes we see most, and how to build billing that doesn't leak.

Most MVPs ship in two phases: the demo, and the rebuild. The first wins the seed round; the second consumes the next twelve months. There's a better way — and it doesn't take longer.

AI-native isn't a chatbot. It's a way of working that uses LLMs across the entire SDLC — and treats that integration as a first-class engineering concern.

Every few months a new database promises 10x performance and infinite scale. Most teams should ignore them. Postgres, in 2026, is still the right default for 90% of products.