A Practical Guide to Building Agents - Summary

A_Practical_Guide_to_Building_Agents/
│
├── 01_What_is_an_Agent/
│   ├── Definition: Systems that independently accomplish tasks
│   ├── Core_Characteristics/
│   │   ├── Uses LLM to manage workflow execution
│   │   └── Has access to tools with defined guardrails
│   └── Not_Agents: Simple chatbots, single-turn LLMs, classifiers
│
├── 02_When_to_Build_an_Agent/
│   ├── Use_Cases/
│   │   ├── Complex decision-making (refund approvals)
│   │   ├── Difficult-to-maintain rules (vendor reviews)
│   │   └── Heavy unstructured data (insurance claims)
│   └── Validation: Must resist traditional automation
│
├── 03_Agent_Design_Foundations/
│   ├── Core_Components/
│   │   ├── Model: LLM for reasoning and decisions
│   │   ├── Tools: External functions/APIs
│   │   └── Instructions: Explicit guidelines and guardrails
│   │
│   ├── Model_Selection/
│   │   ├── Start with most capable model
│   │   ├── Establish performance baseline with evals
│   │   └── Optimize: Replace with smaller models where possible
│   │
│   ├── Tool_Types/
│   │   ├── Data: Retrieve context (query DBs, read PDFs, search web)
│   │   ├── Action: Take actions (send emails, update CRM)
│   │   └── Orchestration: Agents as tools for other agents
│   │
│   └── Instructions_Best_Practices/
│       ├── Use existing documents (SOPs, policies)
│       ├── Break down tasks into clear steps
│       ├── Define clear actions for each step
│       └── Capture edge cases
│
├── 04_Orchestration/
│   ├── Single_Agent_Systems/
│   │   ├── One agent with multiple tools
│   │   ├── Loop until exit condition (tool call, output, error, max turns)
│   │   ├── Use prompt templates with variables
│   │   └── When_to_Split: Complex logic or tool overload
│   │
│   └── Multi_Agent_Systems/
│       ├── Manager_Pattern/
│       │   ├── Central manager orchestrates specialized agents
│       │   ├── Agents as tools (tool calls)
│       │   ├── Manager maintains control and context
│       │   └── Use_Case: Single agent controls workflow and user access
│       │
│       └── Decentralized_Pattern/
│           ├── Agents hand off to each other (peers)
│           ├── One-way transfer with conversation state
│           ├── No central controller needed
│           └── Use_Case: Specialized agents fully take over tasks
│
├── 05_Guardrails/
│   ├── Philosophy: Layered defense mechanism
│   │
│   ├── Types/
│   │   ├── Relevance_Classifier: Keep responses on-topic
│   │   ├── Safety_Classifier: Detect jailbreaks/prompt injections
│   │   ├── PII_Filter: Prevent exposure of personal data
│   │   ├── Moderation: Flag harmful content
│   │   ├── Tool_Safeguards: Risk ratings (low/medium/high)
│   │   ├── Rules_Based: Blocklists, input limits, regex
│   │   └── Output_Validation: Brand alignment checks
│   │
│   ├── Building_Strategy/
│   │   ├── 1. Focus on data privacy and content safety
│   │   ├── 2. Add guardrails based on real failures
│   │   └── 3. Optimize for security AND user experience
│   │
│   └── Human_Intervention/
│       ├── Trigger_1: Exceeding failure thresholds
│       └── Trigger_2: High-risk actions (refunds, payments)
│
└── 06_Key_Principles/
    ├── Start simple: Single agent first
    ├── Iterate: Add complexity only when needed
    ├── Validate: Test with real users
    ├── Monitor: Track failures and edge cases
    └── Evolve: Grow capabilities over time

Key Takeaways

Agent = Model + Tools + Instructions + Guardrails

• Start simple: Begin with a single agent and well-defined tools
• Orchestration patterns: Choose based on complexity (single → manager → decentralized)
• Guardrails are critical: Layer multiple types for robust protection
• Human-in-the-loop: Essential for high-risk actions and early deployment
• Incremental approach: Small deployments → validation → scaling