Work · Client · the firm · 2026

AI operations for a foundation's assistant

Reliability, observability and cost work on a production AI assistant serving a large foundation.

What was built

  • Model-performance monitoring and cost optimisation — routing, caching, model choice
  • An embedding-model migration
  • A read-only benchmarking harness against production data
  • A source-cited cost and strategy brief for leadership

What happened

Brief delivered to leadership; a silent context-compaction defect diagnosed by reading the code, not the vendor's claims.

What it taught me

Verify what a system writes, not just what it reads back.