Learn how AI actually works inside a business.
Plain-language explainers on the agents, the plumbing that connects them to your tools, and the governance layer that makes them safe to run. Written for people who follow this space and want to understand it, not just people who write code.
Explainers
Evergreen pieces that define a term and stay true. Start here.
The Stack
- An LLM is an engine, not a car A model on its own is stateless, goalless, and blind. The harness around it is where the engineering lives, and a person still sets the destination. Read →
- Bring your own agent Why the AI agent you run is becoming a commodity, what MCP is, and where the real value sits: the governance layer above the tool. Read →
- Who can your AI actually reach? Every person who connects a tool to their own AI creates an access path nobody tracks. The four ways it goes wrong, and why onboarding and offboarding are the same problem. Read →
- Intent attribution Your logs say what your AI did. They do not say whether it mattered. Why agent observability instruments the engineering layer and misses the business question. Read →
Prefer to talk it through?
Book thirty minutes with Jaron. We will map where governed AI would take the most work off your plate, using the tools you already run.