What Are AI Agents?
A practical introduction to AI agents, how they work, what they can do, and why they are different from chatbots.
10 MIN
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Build AI
AI Agents & Autonomous Systems: Build systems that can plan, act, use tools, and complete multi-step tasks
Learn how AI agents work, what autonomous systems can and cannot do, how to design agent workflows, connect tools, define guardrails, evaluate behavior, and build systems that do more than politely generate text.
Agents · Tools · Actions · Planning · Workflows · Guardrails · Evaluation · Autonomous systems
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Agent guides
Plan
Map agent behavior
Act
Connect tools
Test
Evaluate reliability
What you’ll learn
Agents are where AI starts doing chores. Naturally, that is where things get interesting.
This section breaks down how to build AI agents and autonomous systems: goals, memory, tools, actions, task planning, orchestration, permissions, fallback behavior, monitoring, human approval, and the guardrails needed before your agent enthusiastically automates the wrong thing at scale.
Agent basics
Understand what AI agents are, how they differ from chatbots, and what makes them useful for multi-step work.
Agent workflows
Design systems that can break work into steps, use tools, call APIs, retrieve information, and produce useful outputs.
Guardrails and safety
Learn how to set permissions, approval checkpoints, failure handling, privacy boundaries, and human review.
Testing and reliability
Evaluate agent performance, monitor outputs, test edge cases, and improve workflows before scaling them.
AI Agents & Autonomous Systems Articles
Build agents that do more than cosplay productivity.
Practical guides for understanding, designing, building, testing, and improving AI agents and autonomous workflows.
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Agent Design
How to Design an AI Agent Workflow
Map the agent’s goal, steps, tools, inputs, outputs, permissions, failure paths, and human checkpoints.
12 MIN
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Tools
How AI Agents Use Tools, APIs, and Apps
Learn how agents connect to external systems, retrieve data, call APIs, trigger actions, and complete workflow steps.
11 MIN
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Planning
AI Agent Planning: How Agents Break Work Into Steps
Understand task decomposition, planning loops, tool selection, intermediate steps, and where agent planning can fail.
11 MIN
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Memory
AI Agent Memory: What Agents Need to Remember
Learn the difference between short-term context, long-term memory, retrieval, user preferences, and persistent knowledge.
10 MIN
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Autonomy
How Autonomous Should an AI Agent Be?
Decide when agents should act independently, ask for approval, escalate decisions, or stay safely on a short leash.
11 MIN
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Guardrails
AI Agent Guardrails: How to Keep Autonomous Systems Safer
Build permissions, approvals, policy rules, output checks, private data boundaries, and fallback paths into agent systems.
12 MIN
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Testing
How to Test an AI Agent Before You Trust It
Test agent behavior with scenarios, edge cases, task completion checks, failure modes, and quality review loops.
11 MIN
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Agent Platforms
The Best Ways to Build AI Agents Without Starting From Scratch
Compare no-code tools, agent builders, automation platforms, frameworks, APIs, and custom builds for agent creation.
12 MIN
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Multi-Agent Systems
What Are Multi-Agent AI Systems?
Explore systems where multiple agents collaborate, divide tasks, review each other’s work, and coordinate complex workflows.
11 MIN
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Use Cases
Real AI Agent Use Cases Worth Building
Explore useful agent ideas for research, support, operations, scheduling, sales, recruiting, content, admin, and knowledge work.
12 MIN
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Failure Modes
Why AI Agents Fail and How to Fix Them
Understand common failures around bad goals, weak tools, missing context, poor evaluation, unsafe autonomy, and brittle workflows.
11 MIN
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Recommended Reading Path
Start with the agent, then design the system.
Begin with the basics, then move into workflows, tools, guardrails, and testing.
Keep Building
Where to go next.
After agent systems, explore no-code building, APIs, engineering practices, or AI product development.
Ready?
Build agents that are useful, not just dramatic.
The goal is not to make an AI system look autonomous. The goal is to make it complete the right task, in the right way, with the right guardrails.