Doxa – Open-source emergent simulator for geopolitical scenarios

Hacker News

Hi! We, Vincenzo and Riccardo, built Doxa as an agnostic engine for emergent simulations with agents for constrainted scenarios (like geopolitical, economics, ...) and work well with LLMs like Qwen2.5:7B, Llama but also cloud models such as Gemini. Doxa can be configured in minutes with YAML scenarios, where you can assign agents' persona, portfolios, constraints. Here a ready-to-use Colab: https://colab.research.google.com/github/VincenzoManto/Doxa/... Let us know your thoughts!

Visit product View on Hacker NewsApr 24, 2026

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

96%96% predicted probability of success on Product Hunt, 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: llama, io · Missing: https docs, excited, just released

63%63% 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 · Strong signals: ios, gemini · Missing: supports, reddit linkedin, podcasting

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

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

44%44% 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

41%41% 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

19%19% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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