Insights on product thinking and engineering excellence • 17 articles published
When AI generates code that breaks production, ownership doesn't transfer to the model — the post-mortem still names the human who clicked merge. Vibe engineering is the craftsmanship answer: you delegate the typing, but never the understanding, the design intent, or the accountability.
AI coding agents are multipliers. Multiply zero, get zero. Multiply a typical outsourced codebase, and you don't accelerate delivery — you accelerate rework. Here's the founder math on why your AI ROI is landing on the wrong substrate.
Most teams say they "do CI/CD" because they have a pipeline that builds, tests, and deploys. That pipeline is automation — Continuous Delivery is a discipline. Here are the practices that turn one into the other.
Most teams have heard of mutation testing. The reason 90% of them never run it: nobody told them how. This is the operating manual — pick the tool, read the report, kill the surviving mutants, run it fast enough to gate every pull request.
Every team with a legacy codebase hits the same wall: you cannot add tests without refactoring, and you cannot refactor without tests. Characterisation tests are the specific tool — invented by Michael Feathers, amplified by AI — that breaks the loop.
Every new model release prompts the same question — is this the one that finally makes AI coding agents reliable? It's the wrong question. What keeps single-agent workflows from scaling to production is architectural, not about the model. Here's the pattern the teams shipping real code keep converging on.
AI coding agents don't understand your architecture — they pattern-match from your codebase. One boundary violation becomes a template that AI replicates hundreds of times. Clean Architecture went from best practice to survival requirement.
Your team adopted GitHub Copilot, spent $180K on licenses, and expected faster delivery. Instead, lead times got longer, defect rates climbed, and your senior engineers are spending more time reviewing AI-generated code than writing their own. Here's why — and what the fix actually is.