I built a SaaS without knowing how to code – am I an idiot?

Hacker News

It's called learnfrom.co, a platform for creating, hosting and selling online courses. I started building it because I wanted to solve a problem I had with existing course platforms. I kept running into things I wanted to change, so I started building them myself. The problem: I wasn't really a software engineer. Instead, I started using AI to build the product. I'd describe what I wanted, let it write the code, test it, fix things when they broke, and repeat. That somehow turned into a real product. LearnFrom is now used by 100+ creators and businesses, with real students and real payments going through it. And that's where I'm starting to get uncomfortable. "It works" and "it's well engineered" are obviously not the same thing. So I'm bringing it to HN to find out how much trouble I'm actually in. If you were reviewing this before I'd let more customers depend on it, what would you look for first? Security? Authentication? Authorization? Data isolation? Payments? Architecture? Performance? AI-generated code? Something I haven't even thought about? Please assume I'm guilty until proven innocent.

Visit product View on Hacker NewsAug 25, 2026

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

92%92% 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 · Strong signals: using, code · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released

57%57% 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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

27%27% 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.

Incorrect prediction on native model

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