Tom Smith

Tom Smith

About the Author:

Tom Smith (C. Thomas Smith III) is a veteran digital analyst and content strategist who spent more than four years as a Research Analyst at DZone.com (part of Devada), where he conducted thousands of interviews with technology executives and authored roughly 1,500 articles that generated more than 10 million page views across topics including AI/ML, Agile, APIs, cloud computing, DevOps, IoT, Java, Kubernetes, microservices, and security. He holds an MBA in Marketing from Duke University's Fuqua School of Business and a B.A. in Political Science from Duke. Smith later worked as a content strategist and technical writer at Cognizant, including stints on Google's Bard (now Gemini) and Meta's AI Business Assistant (MAIBA) "seed" content teams, where he helped train and evaluate large language models. Over his career, he has interviewed more than 4,000 technology executives across AI, cloud, data, security, and storage sectors. He now writes independently through Insights From Analytics and is a contributing writer across multiple Techstrong Group properties, including DevOps.com, Digital CxO, Cloud Native Now, PlatformEngineering.com, and Techstrong.ai, where he covers AI agents, enterprise AI infrastructure, and emerging developer tools.

Articles by Tom Smith

Google Research Releases Harness² to Improve AI Agents Without Retraining Models

October 20, 2026

Google Research’s Harness² introduces a new approach to AI agent optimization by allowing agents to refine their own prompts, tools, memory and orchestration logic without modifying model weights. Early benchmarks show promising performance improvements, but the open-source framework also raises questions about security, API costs and governance as enterprises explore self-improving AI agents.

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