Jason Ward, FinOps for AI lead at C.H. Robinson, shares insights on managing AI costs for enterprises and startups. He details a FinOps strategy centered on comprehensive tagging, leveraging AI for observability (e.g., detecting prompt bloat and context starvation), and pioneering advanced metrics like "cost per thought" and "reasoning ratio" to optimize complex AI workloads beyond simple discrete tasks.
Tanmai Gopal, co-founder of PromptQL and creator of Hasura GraphQL, shares insights on building secure and effective 'company brains' for AI agents. He highlights the surprising metric of a continuously rising edit count as a sign of health, dismisses common pitfalls like siloed knowledge, and proposes a human-in-the-loop, unified wiki approach with granular access control and dynamic credential injection to prevent leaks and foster collaborative knowledge creation.
Lenses.io experts Tun Shwe and Jeremy Frenay discuss the significant security and design hurdles in transitioning Model Context Protocol (MCP) servers from local development to enterprise production. They introduce five core principles for secure agentic design, including shrinking the attack surface and constraining inputs, and detail the necessity of remote MCP servers with robust authentication. The talk provides an in-depth comparison of OAuth 2.1's Dynamic Client Registration (DCR) and the more secure Client ID Metadata Document (CIMD) approaches for managing agent identities, offering a roadmap for building enterprise-grade agentic AI systems with MCP.
In this interview, Sarah Wells and Nick Selby discuss the significant business risks introduced by the current rush to adopt AI. They cover how AI vendors blur security terminology, how the insatiable need for data creates an enormous blast radius for breaches, and provide a framework for responsible AI adoption through threat modeling, cross-disciplinary governance, and a return to IT fundamentals.