Reliability, Risks, Incident Analysis, and what we find while building.
6 min readInstall the Revelara CLI, point it at a codebase, and read your first ranked reliability risk register. About fifteen minutes end to end, walked on a real public repo you can clone and check.
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6 min readWe had an AI quality metric that was stable across model tiers, improved when we refined the system, and measured something tied to proprietary knowledge. Then we built a counterfeit with almost none of the relevant expertise and it scored 0.99. A metric is not trustworthy because the real system passes. It becomes trustworthy when the fake fails.
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12 min readGitHub's February availability report documents two incidents an hour apart with the same root cause. The first mitigation was correct for what the team could see, and it was not the fix. This is a reading of the public report through two lenses, one heuristic and one systems-theoretic.
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7 min readAcross nearly 3,000 public postmortems, medium-severity incidents consume roughly thirteen times more engineering time than critical ones. The implication is upstream.
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12 min readThe DORA 2026 ROI report names the productivity dip of AI adoption and prices it. The verification tax it names is the same cost vibe coding pushes onto a tired reviewer.
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13 min readI ran our STPA review tool on a PRD I was about to build myself. Seven findings, six loss scenarios, every one of them about interactions between components that individually worked fine.
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