Field notes on intelligence layers, AI in operations, and what we're learning from building. Not whitepapers — what we learned this month.
Before an intelligence layer can be designed, discovery has to uncover how the work actually happens: the systems people use, the context they carry, the exceptions they handle, and the interpretation they still assemble manually.
Applied intelligence does not start with agents or frameworks. It starts with understanding existing systems, finding the interpretation gap, building the smallest useful layer, and learning from how people actually use it.
A practical reflection on agentic AI, existing systems, and where LLMs actually create value: not by replacing workflows, but by interpreting what sits around them.