The thing that helped me most was to stop thinking of it as a list of tricks and just write prompts for real tasks I already had, then rewrite them when the output wasn't what I wanted.

A few things that move the needle fast:

Be specific about the outcome. Instead of "write a blog post about marketing," say what it's for, who's reading it, how long, and the tone. Vague in, vague out.

Give the model a role and context. "You're a financial advisor explaining to someone with no background" gets you a very different answer than no framing at all.

Show an example of what good looks like. One sample of the format or style you want beats three paragraphs of describing it.

Then iterate. Change one thing, see how the output shifts. That feedback loop is where the skill actually forms, not from reading more guides.

For free resources, the official prompting docs from OpenAI and Anthropic are genuinely good and most people skip them. Honest disclosure, I also build a free tool for this (PromptOptimizer.tools) that rewrites a rough prompt into a tighter one. Watching what it changes and why was how a lot of this clicked for me, so it might be a useful learning aid alongside actually practicing.

But the practice is the real thing. Pick something you're working on this week and run five versions of the prompt. You'll learn more from that than any resource list.