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Trainy, an AI team that fires you

Hacker News

Trainy, an AI team that fires you

Hi - I'm Patrick. Did YC in S22 + Revolut, Nubank alum. Trainy is made for you to learn how to build AI products, without being fired in real life. It seems like every company in the world wants to use AI (for whatever reason). At the same time, 95% of their workforce has no clue how to do it. Plus, AI jobs are the hottest right now but talent is scarce. So basically, everyone needs to up-skill. I'm not an ML engineer so struggled to learn how to build an AI product. Took me months and a bunch of mistakes. So I decided to try to fix it. Trainy is a simulator to replicate the experience of building an AI product from within a large company. You interact with agents representing CEOs, CTOs, Compliance, etc who have their own expertise, way of looking at things and even personalities. If you screw up the CEO will actually fire you. The full simulator is still being built but on this link you can experience a few scenarios. Would love to hear what you think feels off about the interaction.

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3points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent · Missing: mac, macos, cursor
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes, ios · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
65%65% 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: ios, personal, month · Missing: mobile apps, entrepreneurs, apps
40%40% 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
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
17%17% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real life · 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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