Seppen – Turn prompts into shareable web UIs

Hacker News

"AI is currently in it's CLI era" is a take I saw somewhere that I couldn't get out of my head. So I built Seppen with the goal of bringing AI into it's GUI era to make AI's functionality accessible to an even wider range of people. You can paste any prompt into Seppen and you will get a nice looking web UI that serves the functionality of that prompt on a silver platter in a couple minutes. Seppen automatically detects which parts of the prompt need to be fixed to get a consistent output, and which parts can be customized and picks a fitting input component for those variable parts of the prompt. Then all you have to do is fill in the details as you want and press generate. It's much easier to share, save, and manage these UIs than having to store thousands of words worth of prompts in some notes app. Currently, Seppen supports prompts that produce text, images, and tables (that you can export to csv) and can access the internet to get up-to-date information for prompts that need it (e.g. for a stock comparison prompt or research prompt) You can paste any prompt you have saved on X or that you have somewhere in your notes and see how it works. There are a few ready made examples on the homepage, but if you want to see some more I would encourage you to go to my profile page (/egor) and check out the collections. I would greatly appreciate any feedback and would be very curious to discuss the take I put at the start of the post.

Visit product View on Hacker NewsNov 23, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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