Open Source Summit India 2026

AI systems handle complex reasoning tasks with fluency, yet consistently fail at simple logic — arithmetic, timezone conversions, unit mismatches — with confidence. The problem deepens when AI agents injest AI-generated code/text: the generator and verifier share the same training distribution, and often the same blind spots. A model that writes a wrong timezone conversion will just as confidently verify it as correct. The error is invisible to both.
This talk presents concrete examples and an empirical study of these shared failure modes. We show which categories of errors are most prone to this — where they silently pass both generation and verification — and show practical approaches to break the symmetry using deterministic validation layers that catch what models miss.