THE AI CHRONICLE FIELD GUIDE
AI agents
AI agents plan, use tools and take actions toward a goal. These guides explain how they work, why they fail, who is accountable when they act, and how to build your first one with sensible limits.
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THE ESSENTIAL READ
What are AI agents? How they plan and use tools
How agents choose steps, use tools and where their limits lie.
Read the storyExplore AI agents
13 stories
What are AI agents? How they plan and use tools
How agents choose steps, use tools and where their limits lie.
Why AI agents fail, and how to diagnose the failure
Trace a bad answer back through the run before you fix it.
Build your first AI agent without code
Design one small, supervised agent, step by step.
AI agent vs. AI workflow: how to choose
The real difference is who decides the next step.
Build an ecommerce product-question agent
A supervised agent that answers shoppers from your own catalogue.
Build a research agent with source verification
An agent that drafts briefs in which every claim is sourced.
Build a SaaS onboarding investigation agent
A read-only agent that finds why new accounts stall.
Build a growth reporting agent
A weekly reporting agent whose every number traces to a query.
Build an invoice-exception investigation agent
An agent that investigates failed invoice matches, with people approving.
What AI agent demos leave out
The questions to ask before you buy or build from a demo.
LangChain's role in AI agent development
From open-source library to platform company: what LangChain sells.
Vapi's approach to voice agents
How Vapi wires AI phone agents together, and charges for them.
What AI agent platforms disclose about permissions
Ten agent platforms' permission documentation, read against ten criteria.