Field notes from the AI stack
Less mystery.
Better decisions.
Clear explanations of the choices behind useful AI systems. For the people building them, buying them, and making them work.
Practical AI guides
RAG or fine-tuning? Start with the problem.
Understand when to use retrieval-augmented generation, when to fine-tune a model, and how to evaluate both against your business requirements.
Read the guideWhat is MCP, and does your business need it?
A practical introduction to Model Context Protocol, how it relates to APIs, and what to consider when giving AI agents access to business systems.
Read the guideLLM caching: what actually gets reused?
Understand KV caching, provider prompt caching, and semantic response caching, including where they operate and how to measure their real value.
Read the guideFrom ambition to action
Turn a better understanding
into a better system.
Let’s connect the concepts to your business, your data, and the way your team works.