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Extremis adds RL-powered memory and knowledge graph to AI agents

Developer Ashwani Jha has created Extremis, an open-source Python library designed to give AI agents persistent memory. Extremis automatically recalls relevant past conversation context before LLM calls and saves new context afterward, without requiring changes to application code. It differentiates itself from standard similarity-based memory systems by incorporating a reinforcement learning scoring mechanism that prioritizes useful memories and a knowledge graph for structured data retrieval. AI

IMPACT Enhances AI agent usability by providing persistent memory, reducing user frustration and improving context retention.

RANK_REASON Open-source library release that adds functionality to existing AI models.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Extremis adds RL-powered memory and knowledge graph to AI agents

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  1. dev.to — MCP tag TIER_1 English(EN) · Ashwani Jha ·

    I got tired of Agents forgetting everything, so I built a memory layer. No more re-building RAG pipelines everytime.

    <p>Every AI agent I built had the same problem: it forgot everything the moment the conversation ended.</p> <p>Not because the LLM is bad. Because there was no memory layer wiring things together. So I'd ship a chatbot, watch users re-explain their context every session, and quie…