Flow Charts from Text

Hacker News

I needed to make a simple flowchart for a .pptx displaying a connections between servers. So instead of actually finishing the .pptx I vibed a browser flow chart editor. That's cool and all, but I still need to finish the presentation now that I've been vibe-crastinating... The pitch is that you can edit the flowchart in text straight away. So you can just use any editor and paste it and press "Apply changes", if you don't like the built in one. Probably a few bugs left. There is no backend saving state, so remember to export the sqlite file when you're finished. I would love feedback if this is usable to anyone? In that case I might bother building a backend for user data and buying a domain name.

Visit product View on Hacker NewsAug 29, 2025

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3points

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

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

19%19% 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.

Correct prediction on native model

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