Getting more out of your agents

Everyone is trying to get more out of these tools by writing better prompts. I do not think the lever is the prompt at all. What decides whether an agent is useful to you is not how clearly you instruct it, it is whether it understood what you meant and held it the way you meant it. That is a posture problem, and it is the oldest one there is.

You already do half of this without naming it. When you tell a model to be a blunt senior engineer who hates fluff, it gets sharper, because you handed it a posture. You oriented it. But you only oriented one side. You set up who it should be and told it almost nothing about who you are: your posture, your beliefs, what you and it have already worked out. Orienting the model is the easy half. Orienting it to you is the half that decides whether anything lands.

With people, the move starts with listening, not talking. Calibrate, then synthesize, then communicate. Read where someone actually is, find the threads that matter to them, then speak from curiosity, not certainty. It works because a conversation is live: you say something, their posture shifts, and that shift hands you better information than you had a second ago. You re-calibrate, and the understanding gets built in the loop, not delivered in a message. I did this for companies for over a decade and called it brand. Everything is a probing exercise.

Underneath all of it is one idea I have held since the brand days. You give someone a compass, not a map. A map is fixed, and the terrain always moves. The terrain here is what I call texture: your posture, your beliefs, the understanding we already share. It is the orientation of you that the persona prompt leaves out. The words sit on top of it, and the same sentence means one thing in one texture and something else in another.

This is what AI keeps getting wrong, and you feel it as memory. What you remember of a conversation is mostly its texture, not the words. AI memory is flat: it keeps the words and drops the texture, so a long conversation just gets longer, not richer. A model gets your words and almost none of your texture, so it misses what they mean to you. Texture is the missing layer, what would let an agent read the terrain the way a person does.

The bet underneath the company of one is that the thing worth compounding is not the artifact. It is the thinking that made the artifact possible. If the conversation teaches the next conversation, the work gets easier to carry. If it only produces another finished page, the useful part evaporates and I have to re-explain myself again.

That is why the prompt on this site asks your agent to compare my public context with what it already knows about your work. The useful answer is not automatic resonance. It should tell you where the overlap is real, where the site may be leading it, and where your frame and mine diverge. Otherwise the system just becomes a flattering mirror with better formatting.

I do not have this finished. I am still working out what actually carries the bearing and what just adds noise, and whether you can hand a machine enough of it to matter. This is where that thinking lives, with the trail of how it got here.