Ub

Uber for Coding — Build product with bounties

Hacker News

Uber for Coding — Build product with bounties

Hey HN! After lots of dogfooding, we are now releasing Algora.io to help developers share bounties & easily meet new collaborators. The problem: early-stage founders always have more work than people, tight budgets and no time. Hiring full-time engineers is often not an option, yet most founders would welcome contributions from new collaborators. Meanwhile, most developers welcome flexible work. However, today, all of this is hard. Our solution: we built a Git GUI where you can pay developers and start collaborating with new ones, in just a few clicks. On Algora you can share, reward and earn bounties right inside your code repositories. Algora also recommends developers/bounties that match your tech stack and makes it simple to start working together. We are excited to welcome you on Algora, answer your questions and further improve our product and documentation with your feedback! Thank you - Ioannis & Zaf

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Actual performance

66points
83comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, coding, code · Missing: mac, agents, macos
82%82% 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 · Missing: supports, reddit linkedin, podcasting
79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
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: way · Missing: mobile apps, ios, personal
21%21% 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
16%16% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: reward · 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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