An AI agent answering questions about your business needs to understand how that business works. How do you calculate churn? When does your fiscal year end? Who has the authority to change those definitions? Connecting a model to company data leaves those questions unresolved.

That’s the work of context engineering: giving agents the business definitions, instructions and examples they need to interpret your data. But that context changes as the business evolves, and someone has to keep it accurate.

In this episode of Chain of Thought, WisdomAI co-founder and CPO Kapil Chhabra joins Conor Bronsdon to explain how his team approaches that challenge. We explore how companies maintain shared context, why data teams are taking on the role of AI context engineers, and how a specialized harness plans queries, checks results and repairs errors before returning an answer.

Recorded at WisdomAI’s San Mateo office. This episode is sponsored by WisdomAI.

We cover:

Why the context layer is broader than a semantic layer or catalog, and how it differs from memory
How context drifts, and why a subject-matter expert has to approve changes to shared definitions
Why Kapil sees an AI context engineer role emerging, and why data teams are moving from providing insights to providing context
How WisdomAI's harness decomposes a question, federates queries across data sources and repairs errors, including a customer that replaced a $5M-a-year analytics pipeline
The four ingredients of a trustworthy AI answer: accuracy, consistency, governance and explainability
Live Apps: governed analytics apps built from a single prompt, and what keeps them live
Why your context is your IP and should stay portable

Chapters:
(0:00) Do your agents have the right context?
(1:56) The four ingredients of trust
(5:13) The criticality and impact 2x2
(8:12) Data, context, harness: the hospital analogy
(11:12) What the context layer actually means
(11:48) Specialized harnesses: legal, support, analytics
(13:17) Why only 7% of data leaders have scaled AI
(15:46) What models can't guess: ARR, churn, fiscal years
(16:45) The data stack collapses into the context layer
(20:55) Memory vs. context
(25:26) Are agents the new users of software?
(27:19) Where humans should spend their time
(28:14) Commissioning an AI agent, and who verifies it
(31:28) Context drift and the learning loop
(34:04) Context is a multiplayer game
(35:12) Decompose, query, verify, repair
(38:47) Replacing a $5M analytics pipeline with federation
(42:04) The context development life cycle
(43:29) The AI context engineer
(46:02) Jobs are changing, not disappearing
(46:59) Product, people and process
(51:20) Who decides? Why FDEs can't own your context
(52:22) Data context vs. business context
(54:11) The benchmark: specialized harness vs. general agent
(56:08) Meeting users in ChatGPT, Claude and Slack
(58:48) Static vs. runtime context
(1:00:08) Harness engineering as models change
(1:01:44) Right-sizing AI and Live Apps
(1:04:42) The boring parts: governance, security, caching
(1:06:18) 1,000 dashboards, 50 human-years
(1:08:08) What "live" means
(1:09:19) Are dashboards going away?
(1:12:08) A pipeline app built on a weekend walk
(1:15:53) Who owns the apps?
(1:17:27) Data teams now provide context, not insights
(1:18:56) Building with the WisdomAI MCP
(1:19:43) Your context is your IP
(1:20:48) Closing thoughts: none of that work goes to waste

Links from the episode:
Meet the Modern Data Team (WisdomAI CDO report)
AI Context Engineer (ACE) certification
Live Apps
WisdomAI in ChatGPT Work
Avoid AI Writing
ssot-check
I Paid an AI Agent $8 to Write About its 'Life'
Slack Wants to Be the Context Harness for Code | CPO Jaime DeLanghe
The AI Framework Era Is Over: Why Context Is the Moat | Jerry Liu

Connect with Kapil Chhabra:
LinkedIn
WisdomAI
WisdomAI on X

Connect with Chain of Thought host Conor Bronsdon:
Newsletter
Twitter/X
LinkedIn
YouTube

More episodes: https://chainofthought.show

Thanks to WisdomAI for sponsoring this episode. WisdomAI is the agentic analytics platform for trusted enterprise intelligence: governed context, an analytics harness that makes every answer consistent and verifiable, and Live Apps built from a single prompt. Try Live Apps: https://wisdom.ai/liveapps

Why Context Alone Isn't Enough for Enterprise AI Agents | WisdomAI CPO Kapil Chhabra

Chain of Thought | AI Agents, Infrastructure & Engineering

Why Context Alone Isn't Enough for Enterprise AI Agents | WisdomAI CPO Kapil Chhabra