humans fix ai

Product Hunt

Real developers help vibecoders with AI-built apps

AI tools like Lovable, Replit, and Cursor make it easy to build apps — but when something breaks, you're often stuck. HumansFix.ai connects non-technical builders with real developers who help with AI-built apps — whether it's bugs, improvements, reviews, or technical questions. Describe your problem in plain words and a developer takes care of it. Affordable — fixed pricing and you set the price. Fast — results within 3 days. Perfect for vibecoders and AI builders with no technical background.

Visit product View on Product HuntMar 10, 2026Software Engineering Vibe coding

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Actual performance

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18comments

Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, apps, lovable · Missing: mac, agents, macos

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, builder · 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 · Strong signals: apps · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, 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

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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