How this stuff actually works, explained in plain English.
Notes on how AI systems actually behave: what an agent does between the prompt and the answer, what to automate, how to tell whether the output was any good, and where a person still has to say yes. No jargon, no pitch.
·4 min readThe work you are not allowed to send anywhere
Every firm has a category of work it would automate tomorrow if the files were allowed to leave the building. The hardware constraint that made that a dead end has quietly lifted.
On-premise AILocal LLMData privacyDocument automationHuman in the loop
·6 min readThree signs your intake process needs a second look
A short diagnostic for professional services firms. Each sign is easy to spot, and each one costs more than it appears to.
Client intakeBusiness automationProfessional services
·6 min readFour oversight patterns, running in a real product
Alpine Velo is an AI cycling coach. The interesting part is not the coaching, it is the four mechanisms that keep the AI honest without a person watching it.
AI oversightHuman in the loopAI agents
·6 min readHow much time would AI actually give your team back?
Vendors quote multipliers they cannot possibly know. Here is the arithmetic for sizing the real number inside your own operation, before you spend anything.
Business automationOperationsProcess auditHuman in the loop
·6 min readWhat an automation project actually looks like
Four steps, in order, with the decisions that happen at each one. Including the two places where a project should be allowed to stop.
Business automationProfessional servicesAI strategy
·6 min readThe real cost of typing the same thing twice
Duplicate data entry looks like a small tax on everyone's week. It is actually three separate costs, and only one of them shows up as time.
Business automationClient intakeProfessional services
·6 min readAgent skills vs. agent tools
Two words that get used interchangeably, and shouldn't. The difference decides what your AI agent can do, what it's allowed to touch, and who has to say yes first.
AI agentsHuman in the loop