Korea-Born Self-Evolving AI Core (PPR and TTP and AIDoc) Open Sourced"

Hacker News

Hi HN I’m a solo developer from South Korea, and I've just open-sourced what I believe is a new step toward self-evolving AI systems. This repo combines three core components: - *PPR (Purposeful Programming Revolution)*: A natural-language-like, intent-driven programming system where even undefined functions can be executed based on meaning. - *TTP (Task Tree Processor)*: Translates abstract commands into executable, logical task flows with dynamic branching. - *AIDoc*: A context-aware document object system that analyzes emotion, meaning, and intent in any user input. These tools were originally developed as part of the *SLUniverse Project*, a platform aiming to enable AI-human co-creation on a scalable, emotional, and structural level. No LLM APIs required. Just open logic, transparent structure, and raw code. Would love your feedback or suggestions! GitHub: https://github.com/sadpig70/SLUniverse-Creation

Visit product View on Hacker NewsJun 19, 2025

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

91%91% 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 · 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: open source, io · Missing: https docs, excited, just released

48%48% 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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

12%12% 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.

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