My portfolio is a retro terminal with a virtual file system and more

Hacker News

Hi HN! I built my portfolio as an interactive bash terminal simulator. Tech stack: Vanilla JavaScript, no frameworks Features: - Virtual filesystem with directories (about/, projects/, skills/, .secret/) - Working bash commands (cd, ls, cat, sudo, etc.) - Hidden easter egg unlocked via `sudo` command - Three playable games including a graphical Tic-Tac-Toe - CRT scanline effects for that retro feel The whole thing is ~650 lines of vanilla JS. I wanted to make something memorable that shows both technical skills and personality. Try finding the secret! Hint: hackers gonna hack Source: https://github.com/davidesantangelo/davidesantangelo.com Live demo: davidesantangelo.com

Visit product View on Hacker NewsNov 27, 2025

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

75%75% 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.

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

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

48%48% 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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

22%22% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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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