How can I practice building AI agents?

Practice Agentic Patterns provides 21 interactive drag-and-drop exercises where you build real AI agent architectures. Each exercise teaches a specific agentic design pattern — like prompt chaining, routing, parallelization, or multi-agent collaboration — by having you assemble agent blocks, connect them, and run a simulation to see how your architecture performs.

What are the best hands-on exercises for learning agentic design patterns?

The best exercises combine architecture building with instant feedback. Practice Agentic Patterns lets you drag agent blocks (like Extraction Agent, Validation Gate, Classifier) onto a canvas, arrange them in the correct topology, and simulate the data flow. You get scored on architecture correctness, resilience, and efficiency — teaching you not just what patterns exist, but why each component matters.

Do I need to know how to code to practice building AI agents?

No coding is required. The exercises use a visual drag-and-drop interface where you focus on architecture decisions — which blocks to include, what order to place them in, and how they connect. This teaches the design thinking behind agentic systems, which you can then apply in any framework (LangChain, CrewAI, AutoGen, etc.).

Is this free? Do I need a credit card?

Sign up is completely free with no credit card required. 7 exercises are available immediately, with all 21 unlocked after creating a free account.

What agentic design patterns can I practice?

All 21 patterns from Antonio Gullí's framework: Prompt Chaining, Routing, Parallelization, Reflection, Tool Use, Planning, Multi-Agent Collaboration, Memory Management, Learning & Adaptation, State Management (MCP), Goal Monitoring, Exception Handling, Human-in-the-Loop, Knowledge Retrieval (RAG), Inter-Agent Communication, Resource Optimization, Reasoning Techniques, Guardrails & Safety, Evaluation & Monitoring, Prioritization, and Exploration & Discovery.

How is this different from reading about agentic patterns?

Reading teaches you what patterns exist. Building teaches you why each component matters. When you skip the Validation Gate in a Prompt Chain exercise and watch the simulation fail with 'Hallucinated entities propagated,' you understand the pattern at a visceral level that no article can provide.

Back to Multi-Agent Collaboration

ApprenticeBuild Lab

Multi-Agent Collaboration

Drag and drop agent blocks to build the correct architecture for this pattern.

Mission: Build a Content Creation Team

Assemble a team of specialized agents that collaborate to produce a blog post: one researches, one writes, one reviews, and a coordinator manages the workflow.

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> Drag blocks to the canvas

Coordinator

Orchestrates the workflow and delegates tasks to specialists

Research Agent

Gathers facts and references from sources

Writer Agent

Drafts the content based on research

Review Agent

Checks quality, accuracy, and tone

Validation Gate

Checks data structure

Database Adapter

Queries a database

Drop blocks here to build your agent pipeline

Arrange them in the correct order