Agents
From LLMs to Agent Teams
Agents plan, act with tools, cooperate, and remember. GEORGE keeps them aligned and policy‑compliant.
Agent vs. LLM vs. RAG
LLM
Reasoning & generation from training data only.
RAG
Retrieval‑augmented: injects fresh, external knowledge.
Agent
Decides, plans, calls tools/APIs, and executes workflows.
Building Blocks
- Role‑playing: Explicit responsibilities per agent.
- Focus/Tasks: Narrow scope, high reliability.
- Tools: Custom tools & MCP servers for reuse.
- Cooperation: Multi‑agent collaboration patterns.
- Guardrails: Validation, limits, fallback/human‑in‑the‑loop.
- Memory: Short‑term, long‑term, entity memory.
GEORGE (Orchestrator) — Overview
GEORGE translates user intents into coordinated multi‑agent plans, governs tool access, enforces guardrails, and maintains memory across flows.
Task Orchestration
Breaks down intents, assigns to domain agents, tracks completion.
Policy & Guardrails
Constraints for cost/safety/data; human‑in‑the‑loop when needed.
Tool & Memory
Registers MCP tools, rate‑limits usage; shares scoped context.
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