What we're thinking about.
Short, useful pieces on AI systems, context, and the work of making them run.
The Art of the Possible
Five builds worth doing this year: the wiring, the realistic targets, and what success looks like when done properly.
Your AI Strategy Comes Down to One (Big) Question
You can buy the same models your competitors buy. What your company knows is the part they can't get to. Most leaders are still spending on the wrong side of that line.
Why smart companies don't send every task to their best AI model
The smartest model is almost always the most expensive one, and most of what a business asks AI to do does not need genius. It needs a fast, reliable, good-enough answer, delivered thousands of times a day.
What actually goes into a context layer
Facts, language, rules, and history. Four kinds of knowledge, one governed place, and a feed to whatever AI you use. Here is the anatomy.
The part everyone skips is the part that pays
Five parts make up a working AI system. Four of them you can rent or build. The fifth is your own people, and it is the one most programs never fund.
Context debt: the cost you are already paying
Gartner has a name for why your AI output feels generic. Every prompt that starts from zero is an interest payment on a debt you have not funded.
If you have a hundred use cases for AI, you have zero
The fastest way to stall an AI program is to let every team bring its own use case. Build the context first, and the use cases take care of themselves.
From systems of record to systems of action
Your CRM remembers what happened and waits. The next layer acts on it, and then it learns from what the action produced. That loop is the whole game.