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Updating docs suck, so I'm building GitHub AI agent

Hacker News

Updating docs suck, so I'm building GitHub AI agent

As developers, we love coding but I am just frustrated that nobody takes updating docs seriously. Docs like README, API references, SDK guides, tutorials etc. constantly get outdated. So I am building an Github AI agent that updates your docs automatically whenever your repo changes. This will work as follows: 1. You open a PR 2. The agent reviews the changed files and updates the relevant doc files if needed 3. The PR includes the updated documentation I’d really appreciate any feedback on this idea and any insights on how you're maintaining docs.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, coding, open · Missing: mac, agents, macos
96%96% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
44%44% 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: reviews · Missing: plus, platform, intuitive
34%34% 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
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% 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
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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