Overview

Build autonomous AI systems that think, learn, and act-end to end. The next wave of artificial intelligence is agentic AI: LLM-powered agents with reasoning, memory, planning, and tool use. This hands-on guide shows developers, data scientists, founders, and AI strategists how to design, implement, and scale production-ready autonomous agents for real-world automation. What you'll master: Agent architectures-planning loops, reflection, long-term memory, retrieval-augmented generation (RAG) LLM integration-OpenAI/Anthropic APIs, LangChain, function calling, tool orchestration Multi-agent systems-coordination, messaging, role design, teamwork patterns Deployment & MLOps-evaluations, guardrails, monitoring, scaling, cost control Prompt engineering & alignment-policies, feedback, human-in-the-loop safety Real use cases-business automation, research agents, data ops, customer experience Why this guide: Move from theory to execution with actionable frameworks, code-first workflows, and scalable system patterns that turn LLMs into reliable, goal-driven agents. Essential for anyone building generative AI applications, exploring multi-agent frameworks, or deploying foundation-model solutions at scale.

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