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11 ยท Agent Building Blocks

Overview

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11 - Agent Building Blocks

Every agent is assembled from the same parts. This module covers the three that decide whether an agent works: tools (how the model acts on the world, and how to design schemas and errors it uses reliably), memory (what the agent keeps in context, in task state and across sessions) and planning (how it decides what to do next, and when reflection helps). Agent Protocols: MCP & A2A then standardizes how tools and other agents are connected, and Agentic Workflows & Multi-Agent Systems composes these blocks into patterns.

Learning objectives 3-4 hours
By the end of this module you will be able to:
  • Design tools, schemas and error messages a model uses reliably, and scale to large tool sets with tool search
  • Design working memory, task state and long-term memory (semantic, episodic, procedural), and name their risks
  • Choose a planning strategy - native reasoning, ReAct, plan-and-execute, ReWOO - and know when reflection helps
Prerequisites

Where This Module Fits

flowchart LR
    LOOP["๐Ÿ” The agent loop"] --> T["๐Ÿ”ง 01 Tools"]
    LOOP --> M["๐Ÿ’พ 02 Memory"]
    LOOP --> P["๐Ÿ“‹ 03 Planning"]
    T --> MCP["Next: MCP & A2A"]
    T & M & P --> WF["Then: Agentic Workflows"]

    style T fill:#e8e0d4,stroke:#c8b89a
    style M fill:#dde4dc,stroke:#b0c4b0
    style P fill:#d8dfe8,stroke:#b0bac8

Chapter Map

#ChapterYou will learnTime
1Tool Use & Function CallingStrict schemas, tool_choice, tool design, errors, idempotency, tool search60 min
2Agent MemoryOne taxonomy; context management; checkpoints; Letta, Mem0, Zep, LangMem; poisoning60 min
3Planning & ReasoningReasoning models, ReAct, plan-and-execute, ReWOO, LLMCompiler, reflection, todo lists50 min

Practice with the Agent Loop from Scratch lab: its tool descriptions and validation are the tool-design ideas of chapter 1 under measurement.

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