Agents

AI agents are autonomous assistants that handle tasks requiring decision-making and judgment. Give them a goal and the tools, and they figure out the best path to get there.

What

AI Agent = Your Decision-Making Assistant

What makes something an agent:

• You describe the outcome you want, not the exact steps
• AI decides which actions to take and in what order
• Different situations may need different approaches
• Requires judgment and problem-solving

Common agent scenarios:

• Customer service (every inquiry is different)
• Research and analysis (exploratory, not linear)
• Content review and moderation (requires judgment)
• Complex scheduling with multiple constraints
• Troubleshooting and problem diagnosis

Not agents? If you can write down exact steps that happen every time, that’s a workflow, not an agent.

When to Use Agents

Agents excel at tasks requiring judgment:

Customer Service

The Challenge: Every customer inquiry is unique - some need order lookups, refunds, technical help, or escalation.

Agent Approach: Give the agent tools (order lookup, refund processor, knowledge base) and it decides which to use based on the inquiry.

Why agent works: Can’t predict exact steps ahead of time.

Research & Analysis

The Challenge: Research requires following different paths based on what you find.

Agent Approach: Give the agent research tools (search, document reader, summarizer) and a topic, it explores and synthesizes findings.

Why agent works: Exploratory, not linear.

Content Moderation

The Challenge: Requires understanding context and intent to determine appropriateness.

Agent Approach: Give the agent moderation guidelines and it makes judgment calls based on context.

Why agent works: Judgment calls, not simple rules.

Not sure if you need an agent?

• Can you write exact steps? → Workflow
• Do you need AI to figure out what to do? → Agent
• Is it a mix? → Custom solution

Examples

Customer Service Agent

What you give the agent:

• Goal: “Handle customer inquiries professionally”
• Tools: Order lookup, refund processor, knowledge base, escalation system
• Guidelines: Company policies and tone

What the agent decides:

• Is this an order issue, refund request, or technical question?
• Which tools should I use?
• In what order?
• Do I have enough info or should I ask follow-up questions?
• Should this be escalated?

Why agent works: Customer inquiries are unpredictable. Fixed workflows break.

Real-world use: Customer emails “This product doesn’t work!” - Agent must decide: Is this user error? Defective product? Wrong product ordered? Each path requires different tools and responses.

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Document Review Agent

What you give the agent:

• Goal: “Review contracts for risks and key terms”
• Tools: Document reader, clause library, risk assessment framework
• Guidelines: Company risk tolerance

What the agent decides:

• Which sections are most important in this specific contract?
• What constitutes a risk in this context?
• Should I flag this clause?
• What additional information is needed?
• How urgent is this for review?

Why agent works: Every contract is different. Requires judgment and context understanding.

Real-world use: Service agreement vs purchase contract vs NDA - each requires different focus areas. Agent adapts its analysis approach based on contract type.

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Research Agent

What you give the agent:

• Goal: “Research [topic] and provide comprehensive summary”
• Tools: Web search, document reader, summarizer, fact checker
• Guidelines: Quality standards, source credibility requirements

What the agent decides:

• What are the best initial search queries?
• Which sources should I investigate deeper?
• What information is still missing?
• When do I have enough to provide a complete answer?
• How should I organize the findings?

Why agent works: Research is exploratory - you can’t predict the exact search path ahead of time.

Real-world use: Researching “competitive landscape for SaaS company” requires the agent to determine which competitors matter, what metrics to compare, and how deep to investigate each one.

Agents vs Workflows

Understanding when to use which approach:

Use Agents when:

• ✅ Each situation requires different actions
• ✅ You need judgment calls, not just execution
• ✅ Can’t predict all possible paths ahead of time
• ✅ Task is exploratory or requires problem-solving

Use Workflows when:

• ✅ Steps always happen in same order
• ✅ Process is predictable and consistent
• ✅ You can write it as a checklist
• ✅ Compliance requires documented procedures

Example comparison:

Agent task: “Handle this customer complaint”

• Agent decides: What’s the real issue? What tools do I need? What’s the resolution path?

Workflow task: “Process this invoice”

• Workflow follows: Extract data → Validate → Route for approval → Update accounting → Schedule payment

Many businesses use both: Agents for unpredictable tasks, workflows for repeatable processes.

Getting Started

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See Real Examples

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Custom Agent

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Understand Workflows

Learn About Workflows

Discover when predictable workflows fit better than autonomous agents.

Next

Explore related concepts:

• Prompting - Learn how to give agents clear instructions
• Models - Understand how agents produce results
• Workflows - See how agents automate complete processes

Understand the building blocks at your own pace.