Salesforce Says It Scaled Agentic Coding to 15,000 Engineers
Salesforce published Part 2 of its engineering agentic shift story on September 9, 2026, written by Muralidhar Krishnaprasad, President and CTO of Product Engineering and Research. It describes scaling agentic coding across 15,000 engineers while the company runs a $40 billion business serving hundreds of thousands of customers.
Transcript
Salesforce now uses agentic coding across fifteen thousand engineers. It published the numbers today.
Salesforce says the rollout covers a forty billion dollar business serving hundreds of thousands of customers.
Work items per developer are up ninety point five percent year over year and merged pull requests per developer are up eighty eight point one percent.
Salesforce treated token spend as an engineering discipline, with smart model defaults saving eight hundred sixty four thousand dollars in the first week.
These are Salesforce's own internal measurements, self reported with no independent audit and from a company that sells AI agent products.
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Sources
Every claim in this video comes from the top ranking coverage of this topic. The claims and where each one came from:
- Scaling agentic coding to 15,000 engineers, even as Salesforce runs a $40 billion business with hundreds of thousands of customers, tested the organization's ability to absorb change as much as it tested the technology itself.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- Work items completed per developer are up 90.5% in July year over year.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- Pull requests merged per developer are up 88.1%.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- Ultimately, we treated token optimization as an engineering discipline, and one insight in particular drove our thinking: Over-contexting degrades quality, not just budget.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- Smart model defaults saved $864,000 in the first week.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- In May, Srinivas Tallapragada shared what happened when Salesforce Engineering went agentic. This is the story of how we scaled that work across 15,000 engineers.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)
- Honesty caveat: every figure in this story is Salesforce measuring its own engineering organization. The productivity, adoption, and cost numbers are internal measurements self reported by Muralidhar Krishnaprasad, President and CTO of Product Engineering and Research, and published on Salesforce's own newsroom. No independent audit or third party verification of the figures is cited anywhere in the article, and Salesforce sells AI agent products, so it has a commercial interest in the results looking strong. The one partial exception noted in the article is the Effective Output score, described as a machine learning based productivity score developed with Stanford University, but the reported 200.3% increase in that score is still Salesforce's own measurement.(Salesforce's official announcement, "Pioneering Salesforce Engineering's Agentic Shift: Part 2", published September 9, 2026)