I Put Snake in my Resume [pdf]

Hacker News

I'm sure you've seen the post about putting Tetris in a PDF ( https://news.ycombinator.com/item?id=42645218 ) and putting DOOM in a PDF ( https://news.ycombinator.com/item?id=42678754 ). Someone suggested using this technique in a resume to potentially demonstrate your engineering skills, and being chronically unemployed, I had the chance to try that out. The vision is that some recruiter out there will take a break from work, enjoy a game of snake, before inevitably pressing reject. Take a look if you like. Like the others, it requires chromium based browsers.

Visit product View on Hacker NewsJan 15, 2025

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

64%64% 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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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.

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

11%11% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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