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Branching – Continuous Version Control (real-time sync for Git)

Hacker News

Branching – Continuous Version Control (real-time sync for Git)

Hey HN, I'm Fedor (solo founder). After ~20 years of watching devs fight Git, I'm building Branching. Branching streams your local edits to teammates in real time - no manual push/pull. It's Git-compatible and works offline. Why you might care - Teams see each other's changes instantly instead of in PR-sized batches - Conflicts surface ASAP while context is fresh (LLM-assisted merge is experimental, off by default) - Same GitHub remote, so no migration Ships today - VSCode extension + desktop app (macOS / Windows / Linux) - 3 small product teams have been using it for 1–6 months in production - quick demo video - https://branching.app Looking for 5-10 more teams to join the closed beta - https://branching.app Solo dev? Free Jujutsu GUI: https://visualjj.com (stays free) AMA - does an "always-in-sync commit tree" fit your workflow?

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, context · Missing: agents, agent, cursor
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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
68%68% 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: video, month, way · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% 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
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting
15%15% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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