The AI Implementation Process I Use With Every Client

Short summary

Framework for shipping AI systems through five phases with exit criteria: scoping (narrow scope, measure ROI), POC (adversarial kill-cheap testing), integration (production stack with idempotency and approval queues), evaluation, and operations. Key insight: projects fail during pre-build planning and post-demo handoff, not model selection. Production stack: LangGraph/state machines for orchestration, Postgres+pgvector for retrieval, Lambda for compute, hybrid BM25+dense search with RRF.

• •Five-phase framework with exit criteria prevents AI project failures at planning and handoff stages
• •POC must use production models and real data; should answer four validation questions with measurable eval harness
• •Production stack: orchestration (LangGraph), Postgres+pgvector for hybrid search, Lambda for compute, with idempotency keys and approval queues for safety

Generated with AI, which can make mistakes.