Show HN: Validation system eliminates 90% of AI code failures (97.8% accuracy)

We've built a 3-step validation system for AI code outputs that's currently running in production.

Results across 10,000+ deployments: • 90% reduction in production failures • 97.8% epistemic certainty (Guardian-validated) • Zero false positives • 100% endpoint success rate • 12-29ms response times

One deployment caught 47 bugs before users saw them.

The system validates at three layers: 1. Pattern validation (epistemic certainty framework) 2. Adapter validation (integration safety checks) 3. Convergence validation (system coherence)

Architecture: • 8 Guardians (pattern validators) • 6 Guard Services (integration validators) • TypeScript/Python/JavaScript implementations • Framework templates: React, Vue, Next.js, FastAPI, Express

We're hosting a free 60-minute technical deep-dive on Tuesday (Dec 2, 2 PM EST) where we'll cover: • Complete architecture • Production code examples • Performance optimization • Integration patterns

All code examples and documentation will be shared ($597+ value).

[Registration Link]

Happy to discuss technical details, answer questions, and share learnings.

What validation challenges are you facing with AI code?