AI Agents for Developers: Learning Hub

AI agents are changing how developers build software, automate workflows, and interact with AI. Whether you're learning the fundamentals, exploring agent architectures, or building production-ready systems, this hub brings together practical guides covering every stage of the journey.

Start with the basics, then explore how AI agents work, how to build them, and how to deploy them securely in real-world applications.

"On average, developers report that approximately 46% of the code they produce is fully generated by AI agents, 39% is written with AI assistance, and 27% is written entirely manually."

Source: Preliminary findings from the JetBrains Developer Ecosystem Survey 2026 • 15,000+ developers worldwide

Foundations

New to AI agents? Start here. These articles explain the core concepts, terminology, and differences between AI agents, LLMs, assistants, and other related technologies before you dive into implementation.

What Is Agentic AI?

Learn what agentic AI is and how it differs from traditional AI systems.

What Are AI Agents?

Understand how AI agents work and where developers use them.

What Are Autonomous AI Agents?

Learn how autonomous AI agents execute workflows within defined boundaries.

AI Agents vs AI Assistants

Compare AI agents and AI assistants to choose the right approach.

LLMs vs AI Agents

Compare LLMs and AI agents across memory, tools, and workflow execution.

Agentic AI vs AI Agents

Learn how agentic AI and AI agents relate and where they differ.

Agentic AI vs Generative AI

Compare agentic AI and generative AI across capabilities, workflows, use cases.

Types of AI Agents

Explore the main AI agent types and when to use each.

Single vs Multi-Agent Systems

Compare single-agent and multi-agent architectures for different workloads.

Architecture and core concepts

Understand how modern AI agents work under the hood. Learn about planning, memory, orchestration, tool use, context management, and the building blocks that enable autonomous behavior.

AI Agent Orchestration

Learn how orchestration coordinates agents, tools, and workflow execution.

Multi-Agent Systems

Learn how multiple AI agents coordinate to solve complex development workflows.

AI Agent Architecture Explained

Explores AI agent architecture, including core components.

Agentic Workflows Explained

Explains agentic workflows, how AI agents plan and execute multistep tasks.

AI Agent Context Windows

Learn how to manage AI agent context windows, reduce context loss.

What Is Model Context Protocol?

Learn what Model Context Protocol (MCP) is how it connects AI agents with tools.

What Is an AI Agent Loop?

Explains how AI agent loops work, why infinite loops occur.

Memory in AI Agents

Learn how memory enables AI agents to retain context.

What Are Agent Skills?

Learn how reusable skills extend AI agent capabilities.

Building agents

Ready to build? These practical guides cover frameworks, architectures, implementation patterns, testing, optimization, and production considerations for AI agents.

How to Build an AI Agent?

Build your first AI agent from architecture to deployment.

Building Autonomous Agents

Learn how to build autonomous coding agents that understand codebases.

AI for Engineering Teams

A new hub covering AI governance, observability, secure operations, and agentic workflows for engineering teams.

Explore the hub

Use AI agents in your development workflow

Explore JetBrains AI solutions that help you build, use, and scale AI agents across the software development lifecycle.

Air Gateway

Run terminal agents through one JetBrains account, with access, models, and usage governed centrally.

Explore Air Gateway

Junie

Plan, code, debug, and automate tasks with a coding agent that works across your terminal, IDE, GitHub, and GitLab.

Air in IDEs

Orchestrate AI agents and verify their output directly in JetBrains IDEs, with full control over how changes are reviewed.

Try Air in IDEs

Air Teams

Automate software delivery workflows, coordinate agentic work across teams, identify bottlenecks affecting delivery.

Explore Air Teams

Air Governance

Govern AI usage, models, policies, and costs across your organization, including JetBrains and third-party tools.

Explore Air Governance

Air Context

Give agents shared organizational memory and context that carries across tools, workflows, and execution environments.

Explore Air Context

JetBrains Air

An open system of AI products for developers, teams, and organizations – from coding with agents to automating workflows and governing AI at scale.