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Harness Engineering. Design Patterns for Securing Long-Horizon Multi-Agent AI Systems Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu

Książka w języku angielskim angielski
Harness Engineering. Design Patterns for Securing Long-Horizon Multi-Agent AI Systems Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu - okladka książki

Harness Engineering. Design Patterns for Securing Long-Horizon Multi-Agent AI Systems Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu - okladka książki

Harness Engineering. Design Patterns for Securing Long-Horizon Multi-Agent AI Systems Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu - audiobook MP3

Harness Engineering. Design Patterns for Securing Long-Horizon Multi-Agent AI Systems Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu - audiobook CD

Autorzy:
Ken Huang, Prof. Yale Li, Iftach Orr, Matthew Versaggi, Dr. Melan Xu
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
326
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Long-running AI agents need controls that hold across tool calls, delegated tasks, and persistent memory. Harness Engineering presents design patterns for securing long-horizon multi-agent AI systems through a control plane that governs autonomy, identity, intent, context, and memory. Learn to scope agent permissions, contain prompt injection, detect goal drift, and place human oversight where consequential actions require it.
Through architectural diagrams and HarnessLab scenarios, explore decision tracing, evaluation gates, runtime intervention, recovery, fleet coordination, and data governance. Build the engineering judgment to make agent behavior observable, authority accountable, and improvement measurable, so you can move from promising prototypes to controlled production operations.

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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