EP 45: Why AI Agents Break in Production: The Missing Harness in Your Data Stack

About this episode

An independent evaluation of Snowflake's Cortex Analyst found 6 in 10 AI-generated queries were wrong — but they all compiled and ran without a single error. That's not a model problem. That's a missing harness problem.

Pradnesh Patil is the Co-Founder and CEO of Altimate AI — a platform bringing agentic AI to data engineering with tools trusted by Fortune 500s and downloaded more than 1 million times across 200+ countries. Before Altimate, he spent a decade in product leadership at Palo Alto Networks, Cisco, and VMware.

 

IN THIS EPISODE:

▪  The five components of an agentic data engineering harness: context, governance, MCP tools, shared skills, and agent infrastructure — and why missing any one of them causes silent failures

▪  Why a system prompt cannot substitute for a harness: a prompt tells the model what to do, a harness tells it what is actually true

▪  Where the 27–33% phantom table references and 78% silent wrong joins come from — and why it's not the LLM's fault

▪  How Altimate Code topped ADE-Bench using Sonnet while competitors used Opus — proof that the harness matters more than the model

▪  The deterministic vs LLM boundary: why validation, cost checks, and query correctness are deterministic jobs and should never go to an LLM

▪  Context compaction innovation: why standard LLM compaction destroys long-running data engineering tasks — and how Altimate fixed it

▪  The $5,000 Cortex AI query bill — and how permission-based governance controls prevent agents from going rogue on your cloud bill

▪  The future of data engineering: days of writing SQL by hand are ending — what the data engineer's role becomes in an agentic world

▪  Pradnesh's advice: build open source, build cross-platform — avoid siloed AI features that don't move the industry forward

 

FIND PRADNESH:

Website https://altimate.ai/ Github for altimate-code: https://github.com/AltimateAI/altimate-code Connect with Pradnesh on LinkedIn: https://www.linkedin.com/in/pradneshpatil/

 

DATASCIENCEWITHSAM:

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