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.
OpenAI's updated Agents SDK adds sandboxing and a model-native harness, giving enterprises a more controlled way to build and deploy long-horizon AI agents ...
Google’s internal Project Jitro marks the evolution of the Jules coding agent from a task-executor to an outcome-driven collaborator. By shifting from manual prompting to KPI-driven development, Jitro autonomously identifies and executes ...
Anthropic introduces Ultraplan, a research preview for Claude Code that shifts complex coding plans from the terminal to a collaborative cloud environment. This feature enables developers to review, comment on, and refine ...
Azure Global Black Belts Diego Casati and Ray Kao developed Project Nighthawk, a multi-agent system that automates deep technical research for AKS and ARO with 100% source-grounding ...
Meta's semi-formal reasoning enables AI agents to verify code without executing it, achieving 93% accuracy. Implications for code review and RL training costs ...
GitHub's March 2026 updates introduce secret scanning for AI agents via MCP, 37 new detectors, and expanded push protection. Learn how to secure AI-generated code ...