When you customise an AI assistant — the standing instructions in ChatGPT, a Claude project prompt, a "rules" file for a coding agent — the natural instinct is to keep adding. Every time the assistant does something wrong, you write a rule against it. Cole Medin, who works on agent systems, warns this eventually backfires:

too many rules for an agent can actually become detrimental. You're just splitting its focus between so many processes and conventions.

The idea in plain terms: a language model reads all of its instructions every time it responds. A short, sharp set of rules gets weighed carefully. A long, sprawling one competes with itself for attention. The model has to satisfy forty conventions at once, so it satisfies each of them worse — and worse still, the rules start crowding out the actual task. The fix Medin points to is not "write better rules" but "move processes out of the prompt." Things that should happen every time — formatting checks, file conventions, pre- and post-actions — can be enforced mechanically by hooks, small pieces of code that run around the agent rather than instructions it has to remember to follow. A hook cannot be forgotten; a rule can.

Who this is for splits in two. If you write custom instructions for a general-purpose assistant, the core lesson applies directly: keep the instruction list short, prefer a few strong rules over a complete employee handbook, and resist adding a rule every time something goes wrong — sometimes the fix is correcting the output once, not legislating against it forever. The second half of the advice, hooks, is honestly a developer technique. It applies to people building or configuring coding agents and agent frameworks, where you can attach scripts that run before or after the model acts. If you are a non-developer using a chat assistant, there is no equivalent lever in most consumer products — your practical takeaway is only the first half: shorter prompts, fewer rules.

This is usable now, not a proposal. Hooks are a shipping feature in agent tooling, and the rule-bloat problem is an observed behaviour, not a prediction. That said, be honest about the limits. Medin does not quantify the effect — there is no number for how many rules is too many, no benchmark showing performance falling off at a particular threshold. You are working from practitioner experience, not a measured curve, so "too many" remains a judgment call you have to make by watching whether the assistant keeps ignoring instructions it clearly received. The other unresolved piece is that offloading to hooks requires you to know which processes are deterministic enough to automate; a rule written in prose can handle nuance a script cannot. Moving everything mechanical out of the prompt is good advice, but deciding what counts as mechanical is still on you.