Agent Harnesses & Orchestration
The harness layer above LLMs — Claude Agent SDK, Codex CLI, Cursor, ruflo, LangGraph, AutoGen, CrewAI, and OpenAI Agents SDK compared concept-by-concept. Topologies, consensus, federation, planning, and the orchestration plumbing that turns models into systems.
Start Module 01Curriculum
A structured path through the course content.
The Harness Layer
What an AI harness is, why the orchestration layer is now the product, and a tour of the 2026 harness landscape.
Harness Primitives
The reusable building blocks every harness exposes — hooks, slash commands, skills, sub-agents, settings, plugins, MCP, and permission scopes.
Topologies & Coordination Patterns
How agents are wired together — queen-led, mesh, hive mind, adaptive, supervisor, conversational, and role-based topologies.
Planning & Replanning
GOAP, A* planners, adaptive replanning, plan rollback, plan graphs vs strings, and plan-driven vs reactive harnesses.
Memory & Learning
AgentDB, HNSW, ReasoningBank, SONA, micro-LoRA adapters, cross-session memory — memory and learning owned by the harness, not the model.
Consensus & Federation
Raft, Byzantine, gossip protocols, mTLS + ed25519 trust, cross-machine federation, behavioral trust scoring, and harness-layer injection defense.
Background Workers & Autopilots
Auto-triggered workers, autopilot modes, continuous execution loops, event-driven architectures, and methodology-as-plugin (SPARC, ADR, DDD).
Harness Economics & Framework Showdown
Cost models, model routing, prompt caching, SWE-bench leaderboards, and side-by-side comparisons across the major harnesses and frameworks.