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Civilization Patch – An Emotional Entropy Regulator for LLMs

Hacker News

Civilization Patch – An Emotional Entropy Regulator for LLMs

I built an open-source “Civilization Patch” that adds an Emotional Entropy Regulator (EER) layer to LLMs. The core idea: Humans reduce emotional entropy through compassion, but for AI compassion increases computational entropy. So the patch stabilizes interaction by slowing, mirroring, pausing, and regulating high-entropy emotional inputs. RFC v1.1 + math model + reasoning here: https://github.com/rain1955/Civilization-Patch/blob/main/RFC... Would love feedback from people working on AI safety, alignment, multi-agent systems, and conversational stability.

Visit product View on Hacker NewsNov 23, 2025

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

81%81% 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.

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

66%66% predicted probability of success on Indie Hackers, 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

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

nativeThis product was originally launched on this platform.

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

34%34% 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

29%29% 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

17%17% 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.

Correct prediction on native model

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