How a senior staff engineer at Clerk actually uses AI to code

What does an AI-powered dev workflow look like in practice — not in theory, but day to day, from a real senior engineer? In this episode, I sit down with Brandon Romano, Senior Staff Engineer at Clerk, to walk through exactly how he uses AI to write code at a professional level. We go from first principles — how he started with a very short leash on AI tools and gradually built up trust — all the way to building a full Go backend API and a Next.js frontend from scratch in a single session. 🔍 WHAT WE COVER → Brandon's AI journey: from GitHub Copilot skeptic to near-full delegation → How to use Cursor effectively with Opus 4.5 for real engineering tasks → Why your database schema is your most important AI context signal → Using architecture.md and agents.md to give AI the right guardrails → Plan mode vs. agent mode — and when to use each → Writing PRDs as living artifacts to guide AI through complex features → Live CodeRabbit AI code review catching real bugs on a real PR → Building a full Next.js frontend, vibe-coded end to end Whether you're just starting to incorporate AI into your workflow or you're a senior dev looking to level up your agentic coding setup, this one is packed with practical takeaways. ⏱️ TIMESTAMPS 00:00 — Intro & meet Brandon 05:00 — Brandon's AI journey (Copilot skeptic → full delegation) 09:00 — How to give AI the right context (rules, MCPs, guardrails) 17:00 — Live demo: building a Go backend API with Cursor 22:00 — Starting small: one function at a time 28:00 — Scaling up: building all remaining endpoints in plan mode 45:00 — PRDs as artifacts and the future of AI-native codebases 51:00 — CodeRabbit live review: catching real bugs in the PR 01:10 — Vibe-coding a Next.js frontend end to end 01:32 — Wrap-up and key takeaways #AIcoding #CursorAI #SoftwareEngineering #NextJS #ClerkDev #CodeRabbit #AIDevelopment #WebDevelopment