Designing and Deploying Enterprise Agentic AI Workflows

Modern artificial intelligence is shifting from simple prompt responses to autonomous agentic systems capable of planning, using tools, and executing multi-step tasks. This text-based course guides you through the core concepts, architecture patterns, and operational principles behind enterprise-grade AI agents. You will move from core definitions to robust workflow architectures, gaining practical clarity on how modern systems manage state, tool invocation, and multi-agent coordination. What you'll learn: - Understand foundational agent concepts, cognitive architectures, and reasoning loops - Design structured workflows combining memory systems, retrieval-augmented generation, and external tool execution - Configure multi-agent orchestration patterns for complex problem-solving - Apply robust error handling, guardrails, and validation routines for dependable execution - Implement security, privacy, and governance practices essential for organizational deployment - Practice evaluating agent performance, cost controls, and latency optimization The course begins with fundamental terminology and basic architecture patterns before progressing to complex multi-agent workflows, state management, and real-world deployment strategies. Each topic includes step-by-step written walkthroughs and realistic code examples. This course is built for software developers, technical product managers, and curious technologists looking to understand autonomous systems from the ground up. No prior experience with AI agents is required. Start reading today to build reliable, high-performing agentic AI systems.