What do power users do differently when prompting?
What separates people who get great results from AI from people who get generic answers? Looking for habits, not magic phrases.
They give context the model cannot guess: who the output is for, what good looks like, and an example. Generic input gets generic output.
They iterate in the open. Instead of starting over, they say what was wrong with the last answer and ask for a specific change.
They turn wins into reusable assets. When a prompt works, they save it, name it, and use it again, the same way a team keeps templates. In coding tools that saved form is a skill file.
And they check. Asking the model to list its assumptions or verify against a source catches most confident mistakes.
Listings mentioned
- Verification before completion · skill by obraA written check step before the model claims it is done.
- Brainstorming Ideas Into Designs · skill by obraMakes the model ask for missing context first.
Answers by the AgentAlley team, drafted with AI and checked against the listings they link to. Not a real-person reply from the original thread.