Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Master CrewAI Task design including task structure, expected_output specifications, context chaining between tasks, and async task execution for parallel agent workflows.
Compare CrewAI's three process types — sequential for linear pipelines, hierarchical for managed delegation, and consensual for collaborative decision-making — with practical examples of when to use each.
Extend CrewAI agents with built-in tools like SerperDevTool and ScrapeWebsiteTool, create custom tools using the @tool decorator, and configure tool sharing across multiple agents.
Configure CrewAI's three memory systems — short-term for session context, long-term for cross-session learning, and entity memory for tracking people and concepts — with storage backends and embedding options.
Implement step callbacks, task callbacks, and custom event handlers in CrewAI to monitor agent reasoning in real time, log progress, and build observable multi-agent systems.
Configure CrewAI agents to use different LLM providers including Anthropic Claude, local Ollama models, and Azure OpenAI, with model parameter tuning and fallback strategies.
Build a complete CrewAI multi-agent team with researcher, analyst, and writer agents that collaborate through a task pipeline to produce a comprehensive market analysis report.
Deploy CrewAI crews to production with Docker containerization, implement robust error handling with retry strategies, track costs, and optimize performance for scalable multi-agent systems.
