18 months after big tech layoff, my indie game is nearing release

Hacker News

Howdy, long time HN'er. Spent ~20 years in FAANG and startups, got the pink slip during a big layoff wave in spring 2023. That's ok, I was about to quit anyway :) Finally got back to a lifelong goal of mine, making an "indie" game. (Indie is subjective, but you get the drift.) So, here it is: Ballionaire, a "fast-paced pachinko roguelike where strategy meets physics to create outrageous wealth!" My influences were: Plinko(TM), Luck Be A Landlord, and Totally Accurate Battle Simulator. I was really fortunate because localthunk, the dev behind Balatro, noticed my game during its first month of development (October 2023) and boosted the game a bit amongst streamers, gaining me some traction/confidence, and enabling me to land a publisher. "AMA"?

Visit product View on Hacker NewsSep 24, 2024

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

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal

43%43% 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

38%38% 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

23%23% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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