Pioneering the Agentic Shift Within Salesforce Engineering

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Key Takeaways

Autonomous tools are now writing code, reviewing pull requests (“PRs”), and driving deployments across the software development lifecycle.
Autonomous tools are now writing code, reviewing pull requests (“PRs”), and driving deployments across the software development lifecycle.
Standardizing on Claude Code and removing token limits improved output and quality simultaneously — more shipped, fewer incidents, and fewer bugs.
Standardizing on Claude Code and removing token limits improved output and quality simultaneously — more shipped, fewer incidents, and fewer bugs.
An agentic workflow allowed a product team to complete a 231-person-day migration in 13 days — 18 times faster.
An agentic workflow allowed a product team to complete a 231-person-day migration in 13 days — 18 times faster.
We’re still in the early stages of redefining how the roles across engineering, product, and design will change.
We’re still in the early stages of redefining how the roles across engineering, product, and design will change.

A few months ago, I wrote about the hard work of getting thousands of engineers to actually use AI — not just adopt it in name, but embed it meaningfully into how they work. We built the governance scaffolding, the measurement infrastructure, and the workflows to make it real. We crossed 90% adoption. That felt like a milestone.

It turns out, that was just the beginning.

Today, Salesforce Engineering is running on AI. We’ve moved from a world where AI was a helpful copilot to one where agentic tools are driving the software development lifecycle (SDLC) itself — writing code, reviewing pull requests (PRs), gene...