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Agentic Systems

Building production AI agents in 2026: reasoning loops, MCP tool use, multi-agent orchestration, memory, planning, error recovery, human-in-the-loop, and evaluation.

Agents are not a single technology. They are a composition of reasoning loop, tool layer, memory, planner, error handler, and evaluator. The 12 chapters in this folder cover each layer in depth, ordered so that earlier chapters establish vocabulary used in later ones.

Chapter Order

flowchart TD
    A[01 Agent fundamentals] --> B[02 Reasoning loops ReAct]
    B --> C[03 Tool use and MCP]
    C --> D[04 Multi-agent orchestration]
    D --> E[05 Memory and state]
    E --> F[06 Planning and decomposition]
    F --> G[07 Error handling and recovery]
    G --> H[08 Human in the loop]
    H --> I[09 Security and sandboxing]
    I --> J[10 Evaluating agentic systems]
    J --> K[11 Durable execution]
    K --> L[12 Loop engineering]

Reference Architecture

Each chapter's concepts map to one component of a deployed agent. The diagram below shows where each chapter's material lives in a production system:

flowchart LR
    U[User goal] --> P[Planner ch 06]
    P --> R[Reasoning loop ch 02]
    R --> T[Tool execution ch 03]
    T --> S[Sandbox ch 09]
    S --> M[Memory ch 05]
    M --> R
    R --> E[Error handler ch 07]
    E --> R
    R --> H[Human gate ch 08]
    H --> R
    R --> EV[Evaluator ch 10]
    EV -.feedback.-> R

Files in This Folder

File What it covers
01-agent-fundamentals.md What makes a system an "agent"; the agent vs workflow distinction; when to choose each.
02-reasoning-loops-react-and-beyond.md ReAct, Plan-and-Execute, Reflexion, Tree-of-Thought; loop design patterns.
03-tool-use-and-mcp.md Function calling, Model Context Protocol (MCP), the 2026-07-28 stateless rewrite, A2A v1.0, MCP production hardening.
04-multi-agent-orchestration.md When multi-agent helps and when it hurts; orchestration vs choreography.
05-agent-memory-and-state.md The L1-L4 memory hierarchy (Working, Episodic, Semantic, Procedural) with tradeoffs.
06-planning-and-decomposition.md Task decomposition, plan revision, long-horizon planning.
07-error-handling-and-recovery.md Tool failures, retries, loop guards, the "100th tool call" problem.
08-human-in-the-loop-patterns.md Confirmation gates, escalation, supervised autonomy.
09-agentic-security-and-sandboxing.md Code execution sandboxes, capability gating, prompt injection in agents.
10-evaluating-agentic-systems.md Trajectory evals, Agent-as-judge, Process Reward Models, agent benchmarks.
11-durable-execution.md Surviving crashes in long-running agents: event history, replay, exactly-once side effects, Temporal.
12-loop-engineering.md Engineering the loops around an agent: the four loop levels, termination and budget control, context rot, verification, anti-patterns like loopmaxxing, and the maturity ladder.

Companion Chapters

Key Takeaways

  • Agents are not a single technology; they are a composition of reasoning loop, tool layer, memory, planner, and evaluator. Read chapter 01 first.
  • MCP is the standard tool-interop protocol in 2026; do not build custom tool protocols unless you have a strong reason.
  • Multi-agent orchestration (ch 04) is over-applied; single-agent with good tooling beats multi-agent for most use cases.
  • Memory (ch 05) and error recovery (ch 07) are where most production agent bugs live; budget evaluation effort there.
  • Human-in-the-loop (ch 08) is not a fallback; design gates intentionally for high-stakes actions.
  • Loop engineering (ch 12) is its own discipline now: a strong model in a weak harness loses to a decent model in a great one. Enforce termination and budgets in the harness, and keep the verifier separate from the producer.