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Turing Post · October 7 · 14 min

Salesforce’s Rohan Kumar on the Unsolved Problem Holding AI Agents Back

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. Follow along: https://www.turingpost.com/ Subscribe: https://www.turingpost.com/subscribe #AIagents #EnterpriseAI #salesforce

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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.


Follow along: https://www.turingpost.com/

Subscribe: https://www.turingpost.com/subscribe


#AIagents #EnterpriseAI #salesforce