CrewAI Mastery focuses on the lifecycle and operational challenges of agentic systems how to create, register, version, and manage agents at scale. This hands-on guide covers agent factories, orchestration layers, resource scheduling, service discovery, and dynamic load balancing for heterogeneous agents. The book dives into advanced integrations: blockchain-based agent coordination and auditability, smart contracts for decentralized task markets, and hybrid cloud architectures for latency-sensitive workflows. It also addresses model governance, MLOps for agent models, CI/CD pipelines, testing frameworks for emergent behaviors, and governance patterns for safety, fairness, and compliance. Every chapter contains production checklists, code snippets (Python and orchestration templates), and case studies AI customer support fleets, automated task pipelines, decentralized marketplaces, and smart-city applications. Key topics: agent lifecycle & registry, resource & task schedulers, blockchain + smart contracts for coordination, MLOps & CI/CD for agents, testing & simulation, security, monitoring & SLAs, enterprise deployment patterns.
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