Pinned
Day 60: From model demos to mission-ready AI systems
A practical map for moving from impressive AI demos to systems people can trust.
The Production Layer
The Production Layer is a practical publication for builders moving from AI demos to reliable production systems. Sixty posts in order, plus eight specialist tracks, covering the real engineering decisions behind LLM apps, RAG, agents, multi-agent workflows, evaluation, observability, safety and governance.
Latest articles
Autonomy is a runtime decision, not a model decision
Agents get more capable by default. They only get bounded on purpose.
When MCP earns its overhead, and when a direct API is better
One question settles most of these arguments: will more than one AI application need this capability?
A clean connector does not make a reliable agent
Connector correctness and agent behaviour are separate problems. Most teams only test the first one.
Tools, resources and prompts are not interchangeable
Choosing the wrong primitive hands the model authority a person was supposed to hold.
Where your MCP server runs is a production decision
Transport looks like a technical detail during the demo. It is really a choice about ownership, reachability and trust.
What the MCP protocol actually standardises
It settles how capabilities are described and discovered. Every decision about whether to trust them is still yours.
Day 59: Why production AI is coordinated infrastructure
Why production AI is the coordination of data, models, tools, controls, evaluation, and people.
Day 58: Why governance belongs in the architecture
Why governance belongs in the architecture, not in a document after launch.
