EVALUATING AGENTIC ENTERPRISES (Frameworks, Metrics, and Strategies for the AI-Native Organization) | Metrics for AI Enterprises | AGPH Books
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Book title: EVALUATING AGENTIC ENTERPRISES (Frameworks, Metrics, and Strategies for the AI-Native Organization) | Metrics for AI Enterprises | AGPH Books
Evaluating Agentic Enterprises by Prasad Maderamitla is a foundational guide for organizations navigating the transition from passive AI tools to autonomous, goal-pursuing agents. The book addresses a critical gap: while agentic technology has advanced rapidly, the frameworks required to assess their performance, safety, and business value have lagged behind. The text is structured into five comprehensive parts, beginning with the evolution of "Agentic AI" and its core capabilities: perception, reasoning, action, and learning. Maderamitla introduces several original frameworks, most notably the TRACE Model, which evaluates agents across five dimensions: Task completion, Reasonableness, Action efficiency, Compliance, and Escalation quality. Additionally, the Agentic Enterprise Maturity Model (AEMM) provides a five-level roadmap for assessing organizational readiness across technical, organizational, and governance dimensions. Written for practitioners—including CTOs, architects, and product managers the book provides actionable guidance on the "Evaluation Imperative". It covers the entire lifecycle from pre-deployment red teaming to real-time production monitoring. Key themes include managing "non-deterministic" behavior, mitigating compounding errors in multi-step workflows, and establishing "Progressive Autonomy" to build human trust. By grounding its insights in real-world benchmarks like SWE-bench and case studies from leaders like Klarna and Salesforce, the book serves as a strategic manual for building reliable, AI-native organizations. It concludes by exploring research frontiers, such as world models and self-evolving agents, preparing leaders for the future of enterprise autonomy.
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AGPH Books is a Professional Self Book Publishing House based in Central India, specializing in academic, professional, fiction, and non-fiction books in both print, digital and audio formats. The publishing house produces textbooks, research and reference works, biographies, self-help titles, children’s books, literary fiction, poetry, and general interest publications. With a transparent publishing process and strong digital distribution, AGPH Books ensures global availability through Google Books, Amazon, Flipkart, and its official website store, supporting authors and institutions in reaching a wide and diverse readership.
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About the Author
Prasad Naidu Maderamitla is a distinguished technology leader and Principal Engineer at Salesforce with more than 20 years of experience spanning software engineering, automation, machine learning, enterprise AI systems, and agentic technologies. He has built enterprise-scale language model applications, prompt engineering and evaluation, enterprise-grade AI agents, and scalable AI-driven systems. Throughout his career, Prasad has worked on designing and developing data-driven technology solutions that improve reliability, automation, intelligence, and operational efficiency across enterprise platforms. His work focuses on applying artificial intelligence to real-world business systems, with particular emphasis on evaluating and improving the factual accuracy, robustness, safety, and production readiness of AI-powered applications. Prasad has developed advanced frameworks and systems for prompt optimization and AI evaluation, including an enterprise-grade Prompt Optimization and Evaluation System that leverages sophisticated metrics and similarity models to systematically assess and refine AI prompts. His work reflects a strong commitment to building trustworthy AI systems that can operate reliably in complex enterprise environments. As the author of Evaluating Agentic Enterprises: Frameworks, Metrics, and Strategies for the AI-Native Organization, Prasad explores the emerging discipline of evaluating autonomous AI agents, multi-agent systems, enterprise AI maturity, benchmarking, governance, compliance, and production-readiness testing. His research and practitioner experience focus on helping organizations transition from AI experimentation to responsible, scalable, and fully integrated AI systems. A passionate advocate for innovation, continuous learning, and responsible AI adoption, Prasad is deeply interested in the future of enterprise intelligence, agentic workflows, AI benchmarking, and human-AI collaboration. Through his work, writing, and thought leadership, he aims to help engineering teams and business leaders understand how to evaluate, govern, and scale AI agents safely and effectively. With a strong blend of technical expertise, strategic insight, and practical enterprise experience, Prasad Maderamitla continues to contribute to the evolution of AI-native organizations and the responsible adoption of agentic technologies.
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