Guardrails

Because mistakes scale faster. Infrastructure mistakes scale with traffic. AI mistakes scale with usage and trust. That is faster. AI Errors Feel Plausible AI failures are dangerous because they often look reasonable. The output is coherent. The tone is confident. The result is wrong. That combination spreads errors quietly. When infrastructure fails, it fails loudly. Services return 500 errors. Dashboards turn red. Alerts fire. The failure is obvious and immediate. ...

Guardrails over guesses. We are deliberate about how we use AI. We do not ask it to invent solutions. We ask it to follow patterns. Patterns Encode Experience Patterns exist because something worked. They represent lessons learned, mistakes avoided, and decisions made. AI is very good at following rules. It is less good at choosing them. Patterns are distilled experience. A retry pattern with exponential backoff exists because someone learned the hard way that constant retries overwhelm systems. A specific logging format exists because it makes debugging easier. A particular testing structure exists because it catches common mistakes. ...

Boundaries matter more with AI than with humans. Trust is contextual. We trust engineers with secrets because they are accountable. We do not trust AI with secrets because it is not. That distinction matters more than people admit. AI Has No Sense of Boundary AI does not understand intent. It does not understand sensitivity. It does not understand consequences. It only understands inputs and outputs. If a secret appears in a prompt, the model treats it as data, not as something to protect. ...