Production systems, not demos. Everyone ships the model. I build what holds it up — data pipelines, orchestration, reliability layers. The 90% that determines whether the 10% actually works. Infrastructure that compounds.
The model is the easy part. Infrastructure, orchestration, reliability. That's where production systems actually break.
Cross-provider multi-agent LLM output verification. Three critics — GPT-4o for accuracy, Claude for logic, Gemini for completeness — audit any output in parallel via asyncio.gather. An adjudicator synthesizes per-dimension verdicts, calibrated confidence scores, and dismissed-flag explanations. Different providers, different training data, no shared failure modes.
A production-grade multi-agent system with persistent memory, structured inter-agent communication, and a reliability layer built on the same 60/30/10 architecture.