Better Hub – A better GitHub experience

Hacker News

Hey HN, I’m Bereket, founder of Better Auth. Our team spends a huge amount of time on GitHub every day. Like anyone who’s spent enough time there, I’ve always wished for a much better GitHub experience. I’ve asked a lot of people to do something about it, but it seems like no one is really tackling GitHub directly. A couple of weeks ago, I saw a tweet from Mitchell (HashiCorp) complaining about the repo main page. That became the trigger. I decided to start hacking on a prototype to see how far I could push an alternative interface using GitHub’s APIs. Within a week, I genuinely started using it as my default, same with the rest of our team. After fixing a few rough edges, I decided to put it out there. A few things we’re trying to achieve: - UI/UX rethink* – A redesigned repo home, PR review flow, and overview pages focused on signal over noise. Faster navigation and clearer structure. - Keyboard-first workflow: ⌘K-driven command center, ⌘/ for global search, ⌘I opens “Ghost,” an AI assistant, and more. - Better AI integration: Context-aware AI that understands the repo, the PR you’re viewing, and the diff you’re looking at. - New concepts: Prompt Requests, self-healing CI, auto-merge with automatic conflict resolution, etc. It’s a simple Next.js server talking to the GitHub API, with heavy caching and local state management. We’re considering optional git hosting (in collaboration with teams building alternative backends), but for now, the experiment is: how much can we improve without replacing GitHub This is ambitious and very early. The goal is to explore what a more modern code collaboration experience could look like, and make it something we can all collaborate on. I’d love your feedback on what you think should be improved about GitHub overall.

Visit product View on Hacker NewsFeb 26, 2026

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

97%97% 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.

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

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

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: collaborate · 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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