shipping product with ai isn't as easy as everyone is saying our eng team ships daily with cursor, claude code and codex. after months of integrating ai into every workflow, here's the honest breakdown: what ai is genuinely great at: - scaffolding + boilerplate - refactoring - tests - documentation what ai still can't touch: - performance bottleneck root causes - complex consensus behavior - long-tail state growth & mitigation - validator coordination - production incident debugging the hard part nobody talks about: workflows are evolving weekly. tooling is fragmented. each model has different strengths. what works today is obsolete in two weeks. our playbook right now: keep the team lean, give engineers more scope, increase output per person. claude .md files are becoming essential. code review starts with cursor, escalates to a human. curious to hear about experiences from other founders.