Agents

LLMs that observe, plan, act, and loop autonomously

🔴 MUST

🧠 Understand👁️ Visualize💻 Code🔬 Experiment⚖️ Compare🗣️ Explain🔨 Build

10 subtopics — click to study

What is an Agent? 🔴 Observe 🔴 Plan 🔴 Act 🔴 Tool Use 🔴 Memory 🟡 Planning 🔴 Reflection 🟡 Multi-Agent Systems 🟡 Agent Evaluation 🟡

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RASL Pull · Sprint S-08 — Parallel Learning

You're reading this because RASL is blocked on: "how does the agent loop work — what does planner.py actually do on each step?"

Read observe→plan→act and reflection pages. Then build agent.py and wire it into reliable-agent-lab/agent/planner.py. Read only what unblocks you.

🔨 Lab: M-09 → agent.py + tool schemas 🔁 agent.py loop = RASL planner.py + executor.py 📋 View full parallel plan →

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