Teaching It Once
An agent gets better not from cleverer prompts but from corrections that stick: turn every fix into configuration (memories, rules, small skills) so the same mistake never comes back.
The first time your agent makes a mistake, you fix it. The second time it makes the same one, that is on you.
If you work with an AI agent every day, you already know the honest texture of it: it is confident, and occasionally confidently wrong. More often it just makes a perfectly reasonable call that is not how you would have done it. Early on you will treat each of those as a one-off. Spot it, correct it, move on. Then you will hit the same thing a week later and correct it again, and you will be paying full price every time for something you could have bought once.
The change that matters is not a cleverer way of asking. It is deciding that every correction has to leave something behind. A preference becomes a saved memory the agent reads next time. A rule about how you want things done becomes a standing instruction in its configuration. A mistake worth never repeating becomes a guard sitting right next to the code that invited it. A chunk of recurring production, the same kind of document built the same way again and again, becomes a small skill, so you describe it once and reuse it instead of re-explaining. At some point even the daily work log stops being something you keep by hand and becomes a routine that runs when a session ends and writes itself.
So treat the agent’s configuration the way you treat your codebase: something you version and improve, not a black box you re-explain to every morning. Corrections are not interruptions to the work. They are how the tool gets sharpened.
The leverage, it turns out, was never in the prompt. It is that corrections compound. A generic assistant slowly becomes one shaped to how you actually work, and almost all of that shaping is just a refusal to solve the same problem twice.
So if you are using one of these and you catch yourself re-explaining the same preference, that is the signal. Do not just fix it in the moment. Write it down somewhere the agent will read it next time. A companion is not the model. It is the accumulated residue of every correction you bothered to make permanent.