Why Your AI Output Looks Like Garbage (And the 3 Things That Fix It)

Bland, generic, off-target AI output almost always fails one of three checks, and you control all three.

A free plan answers with the light model and reads about twelve pages at a time. The context that would change the answer is sitting in your head, where it feels too obvious to type. And "write me a marketing email" names a subject rather than a job, so the model fills every gap you left with the most common version it has seen.

This course runs the three checks in order, then turns them into a brief you can write in ninety seconds and a pause you run before you hit send. You practise on your own bad prompts: a drill that names the cause behind six wrong answers, a decision scenario on a launch email that goes out Thursday, and a seven-day mission that ends with your own before and after number.

You walk away able to read a bad answer and say what caused it, a five-part brief you reuse, and your context saved somewhere you stop retyping it.

Who it's for

Founders: keep getting bland drafts and want to know exactly what to change before the next prompt.

Operators and marketers: rely on AI for real deliverables and need it to stop producing work they redo by hand.

AI sceptics: tried the tools, got nothing useful, and want to see whether the gap is in the setup.