Agentic AI Systems Engineering: Planning, Tool Use, Memory, Verification, and Reliable Autonomous Workflows (Paperback) (ISBN-13: 9798175707923)

Agentic AI Systems Engineering is a guide to building systems where a language model plans, calls tools, maintains state, and acts over many steps without a human approving each one.

An agent is a control system with a model inside it. The model supplies judgment; the surrounding system supplies bounds, verification, permissions, and the ability to stop. Most production agent failures trace to that surrounding system rather than to the model's reasoning - which is why this book spends far more time on execution loops, tool schemas, and permission scoping than on prompting.

Fourteen chapters cover the full agentic stack:

- Agentic systems as software architectures: goals, state, policies, and loop design
- Planning and task decomposition: explicit task graphs, verifiable subgoals, bounded replanning
- Tool use and external actions: call boundaries, strict schemas, scoped permissions, untrusted results
- Memory and persistent state: working memory, durable facts, measured retrieval, bounded summarization
- Verification and self-checking: output validation, genuinely independent cross-checks, domain constraints
- Workflow reliability: classified retries, measured timeouts, idempotent writes, designed recovery
- Human oversight and escalation: meaningful approval gates, checkable exception criteria, informative handoffs
- Security and permission boundaries: phase-scoped privilege, tool-layer credentials, sandboxing, audit logs
- Observability and evaluation: decision-level traces, outcome-based success, actionable failure taxonomies
- Cost and latency management: per-run attribution, per-step model selection, caching, latency budgets
- Multi-agent coordination: justified decomposition, message contracts, partitioned state, global termination
- Testing agentic systems: deterministic harnesses, adversarial inputs, failure-mode coverage
- Production agentic platforms: bundled deployment, model version pinning, layered cost limits
- Interaction and progress design: plan-derived progress, streaming, interruption, scope communication

Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and a short set of practical checks. Each chapter closes with a worked scenario showing how these decisions interact under real pressure.

Five appendices cover architectural comparisons, a four-level agent maturity model, a failure-mode reference organized by symptom, adoption sequencing, and common questions.

Written for engineers building AI agents, copilots, and autonomous workflows in production.

Author: Yousf Alrukh
ISBN-13: 9798175707923
Publisher: Independently Published
Language: English
Published: 09/20/2026
Pages: 88
Format: Paperback
Weight: 0.28lbs
Size: 9.00h x 6.00w x 0.18d