What does an AI agent need to understand before it can act for a business? In this interview, Rohan Kumar, President & Chief Platform and Engineering Officer at Salesforce, explains why the answer goes beyond choosing a model. We discuss the enterprise AI harness: how to test and manage agents, give them limited permissions, protect sensitive data, and supply the right context without wasting tokens.
There are a lot of very interesting engineering problems to solve!
And one of them is capturing how a company actually makes decisions...
Part of **The Org Age of AI**: https://www.turingpost.com/t/the-org-age-of-ai
What happens on your team when an exception is approved: do your systems record *why*, or only that it happened?
*We talk about:*
- What belongs in an enterprise AI harness.
- Why an agent needs its own identity and limited permissions.
- How curated context could reduce cost and improve results.
- Choosing models by price and performance.
- Turning data across systems into knowledge an agent can use.
- Why coding models have examples of expert judgment to learn from, while business agents often don’t.
- Capturing the reasoning behind decisions.
- Building with customers to understand how work actually happens. - What junior engineers should learn as coding changes.
*Guest:* Rohan Kumar is President and Chief Platform and Engineering Officer at Salesforce. He previously spent more than two decades at Microsoft, including leading Azure Data.
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