Hey makers!
I've been deep in prompt engineering lately while building an AI tool, and I'm genuinely curious about how others approach this.
A few questions:
1. Do you save your best prompts somewhere? Notion, text files, dedicated app, or just copy-paste from chat history?
2. How do you iterate? Do you have a systematic approach or just tweak until it works?
3. Different prompts for different models? Or do you use the same prompt for ChatGPT, Claude, Gemini?
4. Text vs image prompts do you treat them completely differently?
I've noticed I was doing the same optimizations over and over (adding role, being more specific, structuring output format), which made me wonder if everyone has their own "prompt formula."
Would love to hear your workflows!

This community helped turn a scrappy weekend project into something used by 25,000+ people from all around the world. So it felt right to share this here first:

On Jan 31, we are launching Pretty Prompt 1.0 right here on Product Hunt.

I am so excited about this one!

You can now use Pretty Prompt right inside @Lovable (in beta)

We ve been working super hard to take Pretty Prompt beyond the generic ChatGPT world, and stepping into Vibe Coding.

I recently found a dataset on @Hugging Face that has a huge list of prompts. It's called awesome-chatgpt-prompts, but they point out that it's applicable to other models as well. There are some really useful ones in it along with some funny ones like Magician and Lunatic

I've found persona prompts like this to be really helpful, and I want to start trying out some of these now. I've even gotten my wife to start using some persona prompts in @ChatGPT by OpenAI and she's getting better results.

I recently found a dataset on @Hugging Face that has a huge list of prompts. It's called awesome-chatgpt-prompts, but they point out that it's applicable to other models as well. There are some really useful ones in it along with some funny ones like Magician and Lunatic

I've found persona prompts like this to be really helpful, and I want to start trying out some of these now. I've even gotten my wife to start using some persona prompts in @ChatGPT by OpenAI and she's getting better results.

AI coding is pretty mindblowing but sometimes it's a headache built on a mountain of bugs. Usually that comes down to issues with how you prompt. So, with that in mind, I'm starting a crowdsourcing discussion so we can all improve our prompts and in turn our apps.

Share the exact prompts that turn blank AI requests into real world code. Show us how you go from generate a REST API to a deployable service in just a few steps.

What to post:

AI coding is pretty mindblowing but sometimes it's a headache built on a mountain of bugs. Usually that comes down to issues with how you prompt. So, with that in mind, I'm starting a crowdsourcing discussion so we can all improve our prompts and in turn our apps.

Share the exact prompts that turn blank AI requests into real world code. Show us how you go from generate a REST API to a deployable service in just a few steps.

What to post:

Prompting is everything in the age of vibe coding. Knowing how to guide AI precisely and efficiently is the key to getting the results you want. Today, I m sharing some of my favorite prompting tips, plus a handy cheatsheet I put together.

Prompting Tips That Actually Work

• Be spatially specific. Use keywords like "left", "right", "centered", "aligned to bottom", "spaced evenly" to help the model place elements correctly.

• Mention device behavior. If it should behave differently on mobile vs desktop, say so. Ex: "stacks on mobile, grid on desktop".

• Use visual vocabulary. Mention familiar UI terms like "modal", "toast", "card", "hero section", or "split view" to tap into known design structures.

• Give UX intent. Add the why: "Add white space for readability", "Add a hover effect for feedback", "Use a progress bar to show completion".

• Sequence your ideas. For complex prompts, list in steps: "First, add a header. Below that, place a form with two inputs...". AI loves structure.

• Say what not to do. If you want to avoid scrollbars, animations, shadows, etc., say so.

• Don t forget empty states. Great design considers what happens when nothing is there say "show a placeholder when list is empty".

• Test prompt variants. Swap words like "tile" vs "card", "modal" vs "popup" to see which gives cleaner structure.

• Use active voice. Start with a verb: "Add", "Place", "Make", "Create", "Animate", "Style". It helps guide generation.

A short one today, but packed with milestones:

We just hit 350,000 prompts improved, 25,000 users, and launched 5 new Quality-of-Life updates:

5/5. We made it. One new feature per day this week.

Introducing today: Prompt Library

Full demo and announcement here.

When I first started using AI tools to code, I ran into this wall:

Wait I thought I could just describe what I wanted? Why do I need to learn how to prompt like a pro?

If I have to study how to talk to the AI, something s broken.

Meow world, welcome back to The Breakpoint, a weekly thread on all things dev tools on Product Hunt.

The latest

Recent dev-first products launched on the site

When integrating internal knowledge into AI applications, three main approaches stand out:

1. Prompt Context  Load all relevant information into the context window and leverage prompt caching.
2. Retrieval-Augmented Generation (RAG)  Use text embeddings to fetch only the most relevant information for each query.
3. Fine-Tuning  Train a foundation model to better align with specific needs.

Each approach has its own strengths and trade-offs:

The last 14 days have been mental. Here s why
Pretty Prompt has grown faster in two weeks than our previous product did in 14 months . Crazy.
Highlights:
- 36 new reviews. More than the last 3 months combined.
- 1,000+ new paying users signed up. Still can t believe I m typing that.
- We gave a talk at Stripe about our story and using LLMs in production.
- And on our side, we have been shipping like crazy.
This week is Launch Week.
Major updates. New integrations. Small but powerful tweaks. Super excited
What people are saying:
- My productivity has skyrocketed. It just makes sense the second you use it."
- Honestly, it's one of those tools that instantly becomes part of your everyday stack.
- No friction, no learning curve. Just genuinely better outputs..."
- "The time savings compound quickly."
- "The output I'm getting from Pretty Prompt is a million billion times better than what I was getting before.
Biggest focus:
- Refine v2 better refinement, multiple options, context.
- Team Plans shared libraries, multi-user support.
- Lovable Integration site-specific prompts for Vibe coding
Obsessed with making every day better than the last.

And it all started right here in Product Hunt. The best place to launch new products.

At least it was for us.

Your feedback drives what we're building. Try Pretty Prompt and let me know your thoughts!

Hello Product Hunt!

Following our launch earlier this week, we re back with the most requested feature so far: multiple custom prompts.

I am attempting to observe what you use for coding. I have come across many tools on Product Hunt + Web, but I am fairly certain I have missed quite a bit.
I divided them into "traditional" and "specialised".

Traditional AI models:

DeepSeek

With so many AI tools popping up every week, I m curious:

Which ones have actually stuck around in your workflow?

• Are you using anything for image/video generation?

• Got an underrated writing or code assistant?

• Something that helps automate tedious stuff?

Would love to hear what s been useful (or surprising)!