A guy on r/PromptEngineering did something ballsy. He built a tool that takes your rough prompt and rewrites it like a pro engineer would, then he told the internet the honest truth: if enough people don’t find it useful, he’s shutting it down.
That’s the hook. Not the tool. The stakes.
Here’s the twist: most builders hide the “we might kill this” part. They spin. They talk roadmap. This guy just said it out loud, on Reddit, to strangers. And weirdly, that’s what made people actually click and test it instead of scrolling past another “check out my SaaS” post.
The tool itself, thepromptoptimzer.com, does one job: paste in a prompt, get back a tighter version stripped of the fluff you didn’t know was dragging it down. One early tester said exactly that, the optimization caught bloat he didn’t even notice was there.
Step-by-step mini-workflow if you want to actually test it right:
- Grab a prompt you use often, something you run more than once a week 🧠
- Paste it into the optimizer as-is, don’t pre-clean it
- Compare the output side by side with your original
- Manually strip any leftover constraints the tool left in ✂️
- Run both versions on the same task and see which one actually performs better
Pro tip: the founder flagged this himself, the tool works best when you go back in after and cut extra constraints from the optimized version. Optimizers love to over-explain. Your job is to trim what it left behind, not just accept the first pass.
Second pro tip: if you’re testing any early-stage tool like this, leave feedback that’s specific. “Add a loading state” is more useful to a builder than “cool tool.” Specific feedback is basically free equity in whether the thing survives.
This is a live experiment with a real deadline attached to it. Go poke it, break it, tell the guy what’s broken. Worst case you wasted five minutes. Best case you helped decide whether this tool lives or dies 🚀
Frequently Asked Questions
Q: Does this work for all types of prompts?
Creative prompts get noticeably sharper results, but technical ones sometimes lose specific instructions you need. Testers found it’s clever at removing unnecessary fluff, so it’s worth testing with your prompts to see how it performs for your use case.
Q: Is the interface responsive, or does it feel frozen?
It processes in the background, but there’s no loading indicator yet, so it might feel stuck. Just wait a moment before refreshing; the creator’s aware of this and might add a visual indicator based on feedback.
Q: Can I control how aggressive the optimization is?
Not currently, but users have requested a toggle to keep more constraints intact. This would help when precision matters more than brevity, especially for technical prompts.
Q: Will this actually improve my results?
Early testers found it genuinely clever at spotting fluff they didn’t realize was dragging things down, and said they’d use it regularly. The impact varies by prompt type, but the consensus is it has real potential.
Need feedback for web app
by u/Talley-Ho in PromptEngineering