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

Anthropic Is Rethinking How Claude Remembers You

May 27, 2026

Anthropic is testing dual-mode AI memory, introducing structured “Memory Files” and an background consolidation feature called “Dreams” to give Claude a smarter, evolving understanding of users.

Hermes Agent is Gaining on OpenClaw — and It’s Not Just About Features

May 25, 2026

The open-source AI agent landscape is shifting from static executors to experience-accumulating assistants. While OpenClaw popularized always-on agents running through messaging platforms, Nous Research’s Hermes Agent has recently surpassed it in daily token consumption on OpenRouter by offering a radically different architecture.

Instead of relying solely on pre-configured tools, Hermes Agent builds and manages its own skill library using a background system called Curator, which automatically encodes successful problem-solving behaviors for future use. Combined with a sophisticated, self-merging memory model and a persistent goal-tracking loop that executes tasks autonomously over multiple turns, Hermes Agent signals a new baseline for general-purpose AI—one where tools continuously adapt, learn, and improve the more they are used.

Go to Top