
Deployment & Scaling
How to Deploy AI Agents with FastAPI and Redis Queue for Background Tasks
Run AI agent tool calls in the background using FastAPI and Redis so long-running jobs never block your API clients or timeout mid-execution.
How to Build Agents
How to Build Agents is a practical resource for developers and AI engineers. It delivers tutorials, architecture guides, and deployment advice for building reliable AI agents, focusing on real-world implementation rather than theoretical concepts.

Deployment & Scaling
Run AI agent tool calls in the background using FastAPI and Redis so long-running jobs never block your API clients or timeout mid-execution.

LLM Integration & APIs
Learn to abstract provider-specific endpoints, schemas, and streaming formats into a single client interface to reduce vendor lock-in and manage model failures.

Multi-Agent Systems
Learn how to structure a supervisor agent to delegate subtasks to specialized workers, aggregate results, and manage the overall execution flow.

Multi-Agent Systems
Set up a multi-agent workflow where one agent gathers sources and another drafts, with a defined handoff condition.

Tool Use & Function Calling
Set up schema validation for agent tool calls to prevent malformed arguments and unsafe API requests.

Tool Use & Function Calling
Explore Model Context Protocol servers that provide standardized, secure tools for agents to interact with files, databases, and external APIs, including GitHub, Notion, Supabase, and local filesystems.

Agent Design Patterns
Compare five agent design patterns for breaking down complex tasks, with trade-offs for latency, cost, and reliability.

Agent Design Patterns
Explore different architectural patterns for combining LLMs with retrieval tools, focusing on when to self-correct queries or use graph-based context.

Evaluation & Testing
Compare agent evaluation tools for measuring tool-use accuracy, trajectory correctness, and task completion rates.