A practical guide to running AI coding agents safely and efficiently in a monorepo, including the wins, the configuration changes, and the common failure modes.
Why AI coding divides engineers less on capability than on trust, identity, incentives, and what they think the job really is.
Why many teams use agile tooling and ceremonies but still deliver in large, slow, phase-gated batches, and how to get back to real fast-feedback delivery.
Why fix-forward is usually safer than rolling back when deployments touch databases, background jobs, and other non-idempotent state.
A practical guide to structuring skills so AI coding agents produce faster, safer, and more reproducible software delivery.
How remote work made voice-first coding practical for me, where it breaks down in open offices, and why I still review every transcribed prompt before sending it.
A practical look at which AI tools I adopted from late 2021 to early 2026 and what changed my day-to-day coding.
Why pragmatic, non-blocking code reviews lead to better software, happier teams, and faster delivery than fanatical perfectionism.