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BlinkFolio – AI-Powered Portfolio Builder for Developers

Hacker News

BlinkFolio – AI-Powered Portfolio Builder for Developers

Hey HN! We just launched BlinkFolio, an AI-powered portfolio builder for developers. It automatically pulls your GitHub projects and turns them into a professional-looking portfolio—no manual setup needed. We built this after winning Startup Weekend Zilina, where we saw that many developers struggle to showcase their work effectively. Our goal is to make it effortless for devs to create a portfolio that grabs recruiters' attention and highlights what really matters—your projects. What BlinkFolio does right now: Connect GitHub → Instantly import your projects AI-generated portfolio → Clean, structured, and ready to share Fast & simple → No need to manually build a portfolio from scratch This is our MVP, and we’re looking for feedback! If you're a developer, you can try it for free in exchange for your thoughts. Try it here: https://app.blinkfolio.com Would love to hear your feedback! What features would you like to see next?

Visit product View on Hacker NewsFeb 15, 2025

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, 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

34%34% 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 · Missing: mobile apps, ios, personal

23%23% 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

18%18% 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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