SandBox – AI agents simulating possible futures

Hacker News

Hi HN, I’ve been working on SandBox, a project that lets you explore possible futures using autonomous AI agents. You can build scenarios (environmental, social, governance, etc.), make decisions, and see how things might unfold under different paths. Some of the things you can do: Generate speculative news and events under your scenario settings Visualize how small decisions ripple over time Run multiple agent-based simulations in parallel Built with Python, LangGraph + Azure OpenAI, plus a front-end for visualization. Still in active development; feedback, critiques, ideas & contributions are very welcome. Live demo: https://sandboxes.live/ Github: https://github.com/abozaralizadeh/SandBox If you like it, a helps me know this is worth pushing further. Thanks!

Visit product View on Hacker NewsSep 18, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, new · Missing: mac, macos, cursor

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, visualize, para · Missing: mobile apps, personal, entrepreneurs

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

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