Yet Another Kanban – FOSS, local, private proj. mgmt

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I made a free local private kanban and published the source code. I also made a video with more details on usage, inspiration, why it exists, what to do with it, etc. https://www.youtube.com/watch?v=6qJYg3OuOx4 I made this to support me while working on another project, and I did the thing where I got all mad about paying $20 a month for a SaaS kanban, but actually got the thing done in 2 days as predicted because I have a sick component library. Cool different things about this: - Uses a popular Japanese mobile -> desktop progressive enhancement pattern not seen often in America - Uses gfm-md so you can dump ChatGPT/Claude/Gemini etc tickets - Uses sqlite for local storage - You can `bun dev --host` bc solid and use it on your phone while puttering around your office - It has prebuilt hooks (db schemas + routes) for adding auth so you can easily wire it up for deployment and use it wherever ($12 akamai box < $20 SaaS sub) Use bun as the runtime for this. Enjoy your extra $96 - $240 a year :3

Visit product View on Hacker NewsJul 28, 2025

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

83%83% 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: claude, chatgpt, gemini · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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