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I Help Startups Go from Idea to Revenue in 30-60 Days

Hacker News

I Help Startups Go from Idea to Revenue in 30-60 Days

Hey HN, I'm Syket, and I've noticed a pattern: most startup failures aren't due to bad ideas, but slow/expensive technical execution. Over 30+ projects, I've developed a framework for rapid MVP development: Week 1-2: Core features + authentication + payments Week 3-4: Mobile app + admin dashboard + analytics Week 5-6: AI features + optimization + launch prep Recent examples: - Taplab Agency: Now UK's largest edu creator platform ( https://taplab.agency ) - Unithrive: Mentorship platform serving thousands of UK students ( https://www.unithrive.net ) - Connect Jew: NGO management system scaling across multiple cities ( https://connect-jew.vercel.app ) What I've learned about startup tech: 1. *Start with revenue generation* - build payment processing first 2. *Mobile-first design* - 80% of users are on mobile 3. *AI integration* - users expect smart features now 4. *Performance = retention* - every 100ms delay costs users The key insight: Don't build everything. Build the minimum that generates revenue, then iterate based on real user data. I'm curious - what's been the biggest technical bottleneck in your startup journey? Happy to share specific solutions I've implemented. Portfolio: https://syket.io

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nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
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Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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