Why AI Integration Fails at the Governance Layer
The model is rarely the failure. A missing prompt registry, evaluation gate and human approval path are where production AI integrations actually fall over.
Read the piece ↗ Production AI
after the demo
Governance layers, evaluation gates, retrieval design and operational scaffolding. The work that decides whether an AI integration holds up after launch, written by the engineers who ship it.
AI Engineering
Why AI Integration Fails at the Governance Layer
The model is rarely the failure. A missing prompt registry, evaluation gate and human approval path are where production AI integrations actually fall over.
AI Engineering
Evaluating LLMs Without a Research Team
A working evaluation gate that a small engineering team can build in a week, with the assertions, scoring and failure modes that make it production-credible.
AI Engineering
Prompt Registry: YAML File, Database Table, or Service?
Three working shapes for a production prompt registry, with the trade-offs that decide which one fits a team of three, thirty, or three hundred.
AI Engineering
System Prompts That Survive Three Model Upgrades
A system prompt tuned to one model's quirks breaks on the next model. The structural patterns that decouple intent from model-specific tuning.
AI Engineering
LLM Output Streaming: The Edge Cases That Bite
Token streaming is the default for chat UIs and the source of subtle bugs. Partial JSON, truncated outputs, retries and the patterns that handle them.