The demo worked.
Production didn't.

Practical engineering notes on building production-grade AI systems — written for engineers, not for the hype cycle.

Three series, one discipline: pattern over product.
The series

AI Agents in Practice

Publishing now

Building the loop that survives production: observe → decide → act → check → repeat, the patterns that extend it, and the boundaries that keep an agent inside its lane.

Read the series

RAG in Practice

Complete

Retrieval past the toy example: chunking that holds up, retrieval that returns the right thing, and the failure modes that only show up once real documents are involved.

Read the complete series

MCP in Practice

Complete

How tools actually connect to models: where the seams are, how authority and scope are decided, and what it takes to wire it up without surprises.

Read the complete series
Where to start

Not sure where to begin?

New here New to building AI systems? Start with MCP or RAG — they cover the foundations everything else builds on.
Architecture Interested in how agents are put together? Start with AI Agents from Part 1.
Production After production lessons specifically? Jump to the latest AI Agents article.
Across the series, TechNova is used as a fictional company so the examples stay concrete and the trade-offs stay honest.