I’ve tried writing prompts for AI tools, but I’m not getting the results I want. Can anyone share strategies or resources to create more effective AI prompts? I’d love tips from people with real experience in prompt engineering, since everything I’ve found so far hasn’t really helped.
Alright, straight shooter here: most prompt engineering advice tries to make it all mysterious, but honestly? Just say exactly what you want, and don’t expect the AI to read your mind. Be specific. If you want a list, say ‘give me a bulleted list.’ If you want a certain style, say ‘write in a snarky tone,’ etc. It’s not magic, it’s just wording. Don’t ramble; use clear details. When you don’t get what you want, literally copy your own prompt, annotate what went wrong, and rephrase it so your grandma would get it. That’s basically it, unless you’re doing highly technical API stuff—then, read the docs and play with parameters. Otherwise, practice and iteration beats everything else.
Not to knock what @sognonotturno said—specificity is def clutch—but sometimes you ALSO want to leave a bit of wiggle room so the AI can “think” creatively. Too many instructions and it’ll just cough up a rigid, boring response. I’ve wasted hours trying to over-explain myself, only to realize a more open-ended approach sometimes gets way more impressive ideas. So yeah: balance! If you’re doing, say, story writing prompts or brainstorming, try “give me three out-of-the-box ideas for a horror novel set in Antarctica” instead of a whole paragraph of strict guidance.
Also, don’t underestimate the power of giving examples. Even a simple “E.g.: X, Y, Z” in your prompt can steer results. Or, try giving it a bad answer and say “Don’t do this.” LOL, seriously, it learns weirdly well from that.
Some nerdy people talk about few-shot prompting—basically you give several inputs-outputs right in your prompt so the AI gets what you mean. It’s clunky sometimes, but works in complicated cases (like code, data parsing, format-heavy stuff).
For resources, yeah, reading docs helps when you REALLY need to (snooze fest tho). Some practical stuff: Threads on Reddit’s r/PromptEngineering, newsletters like Latent Space, and lots of prompt template repos on GitHub. Honestly, just lurking and copying others’ prompts has given me 80% of my best ideas, not even kidding.
Summary: find your own balance between detailed and open, toss in examples, see what other people are hacking together, and don’t be afraid to ask dumb questions. AI isn’t judging, it’s just word-vomiting.
If you want a more data-driven approach than just “be clear” or “add examples,” track your prompt iterations. Literally make a spreadsheet: Prompt, AI Response, What Worked, What Didn’t. Over time, you’ll see patterns in phrasing, structure, and context that consistently give you better output. Think of it as A/B testing your prompts—especially useful for recurring tasks or if you’re training workflows for a team.
One trick that’s barely been touched on: chunking. If you need something complex, break it up into logical chunks and walk the AI through them step by step—don’t just toss a giant wall of instructions at it. For instance, first prompt for an outline, then flesh it out section by section. More work, but much more reliable quality.
On disagreeing with earlier advice: while specificity helps, sometimes “playing dumb” and intentionally leaving out a piece of context forces AI to get creative, surprising you. Extreme specificity can dampen unique outputs, but too much ambiguity = AI hand-waving or hallucinations. Finding that sweet spot changes by domain, and IMO, tinkering is half the value. You’re learning how the tool “thinks.”
And on resources: If you’re stuck, don’t just lurk—actually post failures and successes on those prompt forums. Feedback loops dramatically speed up your learning curve. People are weirdly helpful, and memes aside, crowd-sourced prompt hacks are gold.
Here’s a quick pro/con scan for using techniques discussed:
- Pros: Higher consistency, transferable tactics for new tools (not just the current '!), easier troubleshooting, perfect for workflow documentation.
- Cons: More up-front work, can be overkill for casual users, spreadsheeting your life isn’t super fun.
Competitors like @viajantedoceu and @sognonotturno both offer excellent angles—straightforward clarity and creative looseness—but if you want to step up your AI prompt engineering game, systematize and analyze your own experiments. Eventually, you’ll find out exactly what works for you, and that beats one-size-fits-all advice every time.