Launched this week
PingPrompt
Organize prompts, track changes, and iterate faster.
112 followers
Organize prompts, track changes, and iterate faster.
112 followers
Most people still manage important prompts in chat history, docs, and text files. PingPrompt keeps everything in one place, tracks every change, and helps you iterate without losing what already works. Refine prompts faster with a built-in copilot, compare versions with visual diffs, and test improvements with confidence. Built for agencies, creators, no-code/low-code builders, and marketers who depend on prompts every day.
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Launch Team / Built With
PingPrompt
Hey, Hunters 👋
I’m Gabriel, the founder of PingPrompt.
PingPrompt exists because prompts became critical to my work, but the way I was managing them didn’t scale.
They were scattered across ChatGPT history, Notion docs, Slack messages, and text files. Small changes happened constantly, but there was no clear history, no safe way to test improvements, and no real confidence in what was actually working. When I needed to improve something, I’d ask an AI to adjust the prompt. It would often rewrite the entire prompt, hallucinate, or alter the logic, even when I only needed a small tweak.
Since I was already using agentic IDEs for development, I tried to bring that workflow to prompts. I set up GitHub repos, used copilots for edits, and relied on diffs to track changes. But they were too complex for working with prompts, where adjustments are frequent, and the friction was too high for non-developers.
I then looked for dedicated prompt tools, but most focused on just storage, generation, or observability. None of them supported the full prompt lifecycle: editing, versioning, testing, and long-term maintenance.
So I built PingPrompt as the workspace I needed.
It combines fast, text-level editing, full version history with visual diffs, an inline copilot for precise edits, and a multi-LLM playground, all in one place.
You can track every change, compare versions side by side, connect your own API Keys and test prompt versions, parameters, and different AI models simultaneously, without breaking what already works.
This is the first version of PingPrompt. There’s still a lot to evolve, and I’m actively working on improving the app and releasing new features like team collaboration and APIs that integrate directly into real production workflows and applications.
I’m confident this tool helps people work with prompts in a more reliable and confident way.
Happy to answer questions and hear feedback.
@gabrielnsmnto This is a game-changer for "Prompt Ops," Gabriel! Huge congrats on the launch! Upvoted!
In prompt engineering, even a single word change can drastically alter the output, so having a "Git-like" audit trail is essential for reliability. I also love that you’re focusing on precise edits via the inline copilot—standard LLMs are notorious for "over-fixing" a prompt and losing the subtle logic you spent hours perfecting.
PingPrompt
Thanks for the feedback, @nicole_h94! 🙏
The copilot was my biggest bet. Anyone who works with prompts daily knows how frustrating it is when an AI makes edits you didn’t ask for. Sometimes you just want to fix a small ambiguity. It was inspired by agentic IDEs for code, and honestly, I’ve been using it every day with very solid results.
The Git-like versioning exists to preserve that edit history and help you understand how a prompt evolved. If a change doesn’t behave as expected, you can roll back, recover previous versions, or continue iterating safely.
As you noticed, it’s inspired by developer tools, but designed with a cleaner and simpler approach for people who aren’t developers or don’t want to deal with that level of complexity.
StreamAlive - Interactive PPT slides
Congrats on the launch, Gabriel! What makes PingPrompt different from the many other prompt tools (free, open source, and paid)?
I'm curious who the audience would be for this? What's the use case? I ask because I use AI every day in my work (marketing) and for hobbies (vibe coding) and I haven't really found the need to save my prompts. My chats tend to be conversations with refinements over time rather than repeatable work.
PingPrompt
Thanks, @peterclaridge. That’s a totally fair question.
I’m very similar to you in how I use AI day to day. For exploratory work, refinements, or one-off conversations, I don’t save prompts either (there’s no real value there).
Where PingPrompt starts to matter is when prompts stop being casual and start becoming infrastructure.
As soon as you’re building specialized assistants, custom GPTs, chatbots, automations, or reusable workflows, the prompt itself becomes an asset. You need to improve it over time.
That’s exactly how I ended up building PingPrompt. Personally, I built my entire copywriting library inside it. One single hub where I keep specialized copy assistants for different tasks: landing pages, hooks, ads, emails, etc. Each one evolving over time.
What makes PingPrompt different from most prompt tools is that it’s not just storage. It’s a fast iteration workspace. Most tools go to extremes: either they’re simple prompt libraries, or they’re heavy observability/testing platforms. PingPrompt sits in the middle and integrates writing, testing, versioning, and comparison in one simple workflow.
So the audience is people who need to optimize prompts frequently and reuse them across projects and automations like marketing and AI agencies, no-code builders, freelancers, content creators with defined processes. Especially people who already use AI operationally, not just conversationally.
StreamAlive - Interactive PPT slides
@gabrielnsmnto I love this reply, thanks so much for sharing!
PingPrompt
@peterclaridge Thanks a lot. Since this is my first launch, I’m genuinely trying to learn. From your perspective, what would need to exist for a tool like this to be worth using in your workflow? Or what problem around prompts would have to become painful enough for you to care about a dedicated tool?
StreamAlive - Interactive PPT slides
@gabrielnsmnto I was giving this a lot of thought overnight and spoke to a couple of our developers. The consensus was that prompt management and tracking for machine to machine prompts where the human is out of the loop might have a good use case.
For example at StreamAlive we help visualize the chat by using an API to send chat messages to an AI image generator. There's no human involved in the prompt, it's entirely machine to machine. We've refined and tweaked that prompt over the last 18 months so potentially it would be useful to know what prompt we started with and how it has evolved over time.
This is so timely! I’ve been using Notion pages to organize my prompts, but it’s a mess when it comes to tracking version changes or iterating quickly. Having a dedicated space to manage everything without losing 'what already works' is a huge upgrade. Great job on the launch!
PingPrompt
@yahaha66 Thanks, that’s exactly the problem I ran into as well.
Okay, gotta say. This is really cool. Because I do save prompts in chats, whatsapp or docs which is quite tiresome. Congrats on the launch. @gabrielnsmnto Can't wait to try this out.
PingPrompt
@rashiaroraofficial Totally get that, it’s exactly the pain that pushed me to build this. You can try it free for 14 days and see if it fits your workflow. Hope you enjoy it.
I've found when coding , that short prompts and then iterating is the best way... mostly because if i write a long perfected prompt... it neeeeeever becomes as my vision anyways. is it me that is bad at prompting or how do you think about that?
PingPrompt
@markus_kask You're absolutely right. For coding, short prompts + fast iteration is definitely the best approach.
But here's the thing: those coding agents themselves have system instructions that define how they work. Those instructions are what need to be constantly updated and optimized, which is different from the prompts users iterate on to get results.
That's exactly where PingPrompt fits: when managing automations, assistants, or recurring tasks. Even though the interaction with outputs stays iterative, the system instructions need to be consistent, optimized, and reusable.
Does that match how you're thinking about it, or do you see it differently?
Version control for prompts makes sense—does the diff view show semantic changes or just text diffs?
PingPrompt
@jacky0729 Great question! Right now it’s a text diff, similar to what you’d expect from a code editor. Semantic diffs are tricky with prompts because meaning and behavior change depending on the model, temperature, and surrounding context. There’s no single “ground truth” for how a prompt will behave.
That’s exactly why PingPrompt leans so much into fast testing instead of trying to over-abstract semantics. You can run two or more versions of the same prompt side by side in the playground and see how the outputs actually change, with the same inputs and settings.
In practice, comparing real outputs ends up being far more reliable than guessing intent from a semantic diff alone.
Hi Gabriel!
Wonderful setup! Congratulations for your launch.
I am assuming Pingprompt acts as a prompt repository for various channels of AI tools that we use.
Is this the primary use case for the same? If else, kindly provide appropriate use case any given scenario.
PingPrompt
@nikil_krishnan thank you, I really appreciate it.
At a high level, it can work as a prompt repository, but that’s not the main value.
PingPrompt is designed for recurring workflows where prompts need to be refined, tested, and reused over time. Things like assistants, automations, or repeatable tasks inside agencies or teams with defined processes.
A key differentiator is the in-line copilot. It works only with the prompt context and suggests targeted edits directly in the text, which you can accept or reject piece by piece, similar to code copilots. This makes iteration much faster without rewriting the whole prompt.
Everything runs on your own API keys, both in the playground and in the copilot, so you stay in control of cost and data.