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I'm betting everything on this. No plan B

Hacker News

I'm betting everything on this. No plan B

I’m 25, way too many exams still to take. My classmates graduated two years ago, and here I am…still stuck in the same place. Not long ago, through a friend, I received an offer for a regular 9-5 job, average salary, 30-minute drive to the office and all the usual perks. It seemed like a solid offer. Everyone told me to accept it: my friends, my family. The idea was simple—I could start working, save some money, keep studying in the meantime, and finally finish my degree as soon as possible. After that, I could move to a bigger city, get a better paying job, and follow the usual path everyone expects. But I said no. I turned it down to create Describify. Describify is a platform that uses AI to analyze an image of an item someone wants to sell and generates a complete, tailored listing for platforms like Vinted, eBay, or Wallapop. Alright, you’re probably thinking, “What an idiot!” And maybe you’re right. I know that Describify isn’t a rocket headed for Mars or the next groundbreaking innovation in AI, but it’s my first public project—the first one I’ve poured my time (and sometimes my sanity) into, coding almost every day in my bedroom (don’t believe me? Check out my GitHub) while the rest of the world judged me. It’s like the Macintosh for Jobs. (Okay, I know that’s an over-the-top comparison, but you get the idea.) The point is, I believe in my idea and in the future ones that will come. And if you believe in it too, sign up for the waitlist and be among the first to access the platform—as soon as I squash a few bugs! www.describify.it

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Actual performance

2points
11comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
90%90% 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.
AppSumoStrong fit for a featured deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
62%62% predicted probability of success on AppSumo, 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
56%56% 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
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, coding · Missing: agents, macos, agent
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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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