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Harness Patterns for Agentic AI with Claude Code and Hermes Agent. ⁠Master 15 proven patterns for engineering secure, observable, and production-ready AI agents Ken Huang, Grace Huang

Książka w języku angielskim angielski
Harness Patterns for Agentic AI with Claude Code and Hermes Agent. ⁠Master 15 proven patterns for engineering secure, observable, and production-ready AI agents Ken Huang, Grace Huang - okladka książki

Harness Patterns for Agentic AI with Claude Code and Hermes Agent. ⁠Master 15 proven patterns for engineering secure, observable, and production-ready AI agents Ken Huang, Grace Huang - okladka książki

Harness Patterns for Agentic AI with Claude Code and Hermes Agent. ⁠Master 15 proven patterns for engineering secure, observable, and production-ready AI agents Ken Huang, Grace Huang - audiobook MP3

Harness Patterns for Agentic AI with Claude Code and Hermes Agent. ⁠Master 15 proven patterns for engineering secure, observable, and production-ready AI agents Ken Huang, Grace Huang - audiobook CD

Autorzy:
Ken Huang, Grace Huang
Ocena:
Stron:
374
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Building an AI agent is easy. Building one that can operate reliably in production is a much harder engineering problem.
Harness Patterns for Agentic AI with Claude Code and Hermes Agent goes beyond prompts and agent frameworks to reveal the architectural patterns that make production agentic systems work. By examining Claude Code and Hermes Agent side by side, you'll discover 15 reusable harness patterns for controlling how agents use tools, manage context, coordinate tasks, enforce permissions, retain memory, recover from failures, and interact with external systems.
Each pattern is explored through real TypeScript and Python implementations, followed by a practical comparison that explains the trade-offs and when to use each approach. You'll then apply the pattern to a defensive cybersecurity agent, seeing how these architectural decisions behave under real operational pressure.
From agent loops and tool contracts to permissions, context management, multi-agent coordination, observability, MCP, model routing, and structured outputs, you'll develop a framework-independent mental model for engineering AI agents that are reliable, auditable, and ready for production.

O autorze książki

Ken Huang is a renowned AI expert, serving as co-chair of AI Safety Working Groups at Cloud Security Alliance and the AI STR Working Group at World Digital Technology Academy under the UN Framework. As CEO of DistributedApps, he provides specialized GenAI consulting.
A key contributor to OWASP's Top 10 Risks for LLM Applications and NIST's Generative AI Working Group, Huang has authored influential books including Beyond AI (Springer, 2023), Generative AI Security (Springer, 2024), and Agentic AI: Theories and Practice (Springer, 2025)
He's a global speaker at prestigious events such as Davos WEF, ACM, IEEE, and RSAC. Huang is also a member of the OpenAI Forum and project leader for the OWASP AI Vulnerability Scoring System project.

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