Phase 3: Scale, Failure & Evaluation · ~90 minutes · —
Case Studies and the 2026 State of the Art
Three production-grade references to study end-to-end, each illustrating a different slice of multi-agent engineering.
Hiring signal: Can operate case studies and the 2026 state of the art in production
Introduction
Anthropic's Research system (orchestrator-worker, 15x tokens, +90.2% over single-agent Opus 4, rainbow deployments) is the canonical supervisor case. MetaGPT / ChatDev (SOP-encoded role specialization for software engineering; ChatDev's "communicative dehallucination"; MacNet extension to >1000 agents via DAGs, arXiv:2406.07155) is the canonical role-decomposition case. OpenClaw / Moltbook (originally Clawdbot by Peter Steinberger, November 2025; renamed twice; 247k GitHub stars by March 2026; local ReAct-loop agents; Moltbook as an agent-only social network with ~2.3M agent accounts within days of launch, acquired by Meta 2026-03-10) illustrates what happens at population scale: emergent economic activity, prompt-injection risks, state-level regulation (China restricted OpenClaw on government computers, March 2026). Framework landscape April 2026: LangGraph and CrewAI lead production; AG2 is the community AutoGen continuation; Microsoft AutoGen is in maintenance mode (merged into Microsoft Agent Framework, RC Feb 2026); OpenAI Agents SDK is the production Swarm successor; Google ADK (April 2025) is the A2A-native entrant. Every major framework now ships MCP support; most ship A2A. This lesson reads each case end-to-end and distills the common patterns so you can pick the right reference for your next production system.
Type: Learn (capstone) Languages: — Prerequisites: all of Phase 16 (Lessons 01-24) Time: ~90 minutes
Objective
Learning objectives
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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.
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