AI systems no longer just answer — they decide and act.
Agentic AI Systems: Foundations of Architecture and Core Design gives engineers and technical leaders the system-level playbook for building reliable, production-ready AI agents. This is an architecture manual: it covers agent loops, planning and decision-making, state and memory models, tool contracts, guardrails and permissions, observability, and error-handling patterns that keep autonomous systems predictable under real-world pressure.

You’ll get practical patterns (proposal/executor separation, idempotent tool design, staged autonomy), checklists for safe deployment, and operational tactics proven in early production experiments. If you’re designing LLM-driven agents, orchestration layers, or multi-agent coordinators — and you need them to work at scale — this book replaces hype with engineering discipline. Not about prompts; about structure.

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