9 articles in Code Quality
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.
Gene Kim and Steve Yegge argue that vibe coding works for production — if you have preventive, detective, and corrective controls. We agree. We built the platform that enforces those controls structurally. Here's what we've learned about why practices alone aren't enough.
Your dashboards show green. Your test coverage is stable. But three threats are compounding underneath — defects, debt, and non-determinism. AI is making each one worse, faster. Here is how to see them before they see you.
Vibe coding is productive, inevitable, and here to stay. But without guardrails — prevention, detection, and correction — it creates tech debt at warp speed. The teams that win will be the ones who vibe code with discipline, shipping fast AND shipping safely.
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.
Most teams treat DORA metrics like a dashboard decoration — check them quarterly, nod at the numbers, change nothing. Elite teams use them as a compass that connects delivery performance to engineering decisions. Here's the difference between observing DORA and using DORA.
DORA metrics tell you delivery is slow. Code coverage says tests are fine. But neither tells you why features take 3x longer than they should. Detection connects the dots — correlating process symptoms to code causes — so you fix what actually matters.
Most test suites look healthy — high coverage, all green. But run mutation testing and you'll discover that 80-90% of tests would still pass even if you deleted the code they claim to test. Here's what decorative tests are, why they're dangerous, and how to fix them.
AI coding agents don't create quality — they amplify whatever's already there. The 2025 DORA Report confirms it: AI adoption correlates with higher instability. Here's why your codebase determines whether AI accelerates delivery or accelerates chaos.