Make fullstack web app bi AI Agent with structured requirements

Hacker News

Hi Hacker News, I know that you guys mostly technical person but I want to share my startup MVP to you if you can test it and give me your valuable feedback. I try to build Software Development AI Agents for Non-technical startup founders who want their MVP fast with affordable solutions. So I build Genesoft to allow user put their web application requirements and Genesoft AI Agent will working on fullstack web application for them. Genesoft different from similar product in the market, it focus on structured requiremnts to get input from customer because I think in the long running project structured requirments may help improvement better that conversation based AI Agent that can lead to AI Agent confusion and misunderstanding if context is too large. By the way, I'm still looking for technical co-founder who able to help me develop software development AI Agent system to automate software development tasks as much as possible for non-technical startup founder.

Visit product View on Hacker NewsFeb 15, 2025

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

80%80% 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: agents, agent, user · Missing: mac, macos, cursor

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, hacker news, io · Missing: https docs, excited, just released

36%36% 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

30%30% 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

29%29% 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

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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