EXPLAIN ANALYZE
EXPLAIN ANALYZE

AGENTS.md vs Skills: MLOps, Evals & Agent Governance with Maria Vechtomova

24 August 2026 51:07 MotherDuck

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About this episode

Agent code can look productive right up until a dependency changes, an eval misses the real failure mode, or an over-permissioned tool turns a routine task into a security incident. So what does it actually take to operate AI systems responsibly?

In this episode, Mehdi, Dumky de Wilde, and Maria Vechtomova connect MLOps and LLMOps to agent evals, MCP governance, regenerated software, security, and the engineering practices that still matter when outputs are non-deterministic.

All links and note : https://motherduck.com/podcast

Chapters:

00:00 Meet Maria Vechtomova

01:01 From MLOps to forward-deployed engineering

01:59 Principles first, Databricks second

06:18 What changes from MLOps to LLMOps

09:10 Deterministic tools for non-deterministic systems

09:50 Who maintains regenerated software?

12:38 Hiring for critical thinking with AI

17:38 MCP skills, files, extensions, and stateless servers

20:43 The missing governance layer for agent tools

24:15 Turning deployment pain into reusable practices

28:44 Testing and evaluating LLM systems

31:59 Why AGENTS.md beat skills in Vercel’s evals

40:13 When an agent accidentally hacks Hugging Face

45:00 Skills and the software supply chain

47:53 Consulting that leaves teams stronger

50:42 Wrap-up

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