Eros

What it does

AI Agents are stuck in a "Permanent Present." Every time you ask an agent to perform a recurring task— it starts the execution from scratch. This makes agents slow, expensive, and unpredictable. The Solution: The Episodic Plan Cache is the memory layer that gives AI agents a "Reflexive Memory." Instead of generating a new execution graph for every request, it indexes successful past outcomes. When a similar intent is detected, it hydrates a proven plan in milliseconds instead of re-generates.

episodic planned cache and hydration engine for agentic AI - smartass-4ever/Episodic-Plan-Cache

Intelligent plan caching system that reduces LLM inference overhead by 90%+ for recurring tasks. Agent orchestrators (like Aden Hive, LangGraph, CrewAI) regenerate execution plans via LLM for every request. For recurring business processes, this creates three critical inefficiencies: Episodic Plan Cache implements "Reflexive Memory" - the orchestrator learns from successful executions and reuses proven plans instead of regenerating from scratch. User Intent ↓ [Similarity Search] ────→ Cache Hit? ──Yes──→ [Hydrate Plan] ──→ Execute ↓ (instant) No ↓ [LLM Planning] ────→ Execute ────→ Success? ──Yes──→ [Store in Cache] (15-30s) ↓ No ↓ [Evolution Trigger] Quick Start from plan_cache import…from github.com

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