Srini Tallapragada (President & Chief Engineering Officer at Salesforce) published a progress report on May 27, 2026: after crossing 90% AI adoption, Salesforce Engineering moved from "copilot" usage to a genuinely agentic SDLC, where autonomous tools write code, review PRs, generate tests, update documentation, and manage deployments.

The inflection point: org-wide standardization on Claude Code and, above all, removing all token limits. The doctrine: the token limit is friction to eliminate, not a budget safeguard. The results (April 2026 vs 2025): +50.8% work items per developer, +79% PRs merged, and an Effective Output score (an ML measure of the code's real value, not volume) +151.3%.

Proof by example: a migration of 33 API endpoints to a cloud-native architecture, estimated at 231 person-days, completed in 13 days — 18× faster. The method: a rule-based framework built in Claude (markdown + reference implementations) whose rule set grows with every PR feedback, autonomous LLM loops (build, fix, validate) with no manual intervention, parallelized across isolated environments. Outcome: 5 PRs, the largest delivering 21 endpoints with 100% coverage.

Against the idea of a speed/quality tradeoff, the Engineering 360 platform shows incidents dropping by 5% despite the rise in PRs: "quality doesn't suffer from speed. It benefits from it" — thanks to security guardrails and quality standards structurally embedded in the workflow (Trust as the #1 value).

Beyond the numbers, Salesforce is overhauling the SDLC: which processes to eliminate, which handoffs to remove, what human work can an agent own? A new craft emerges: Claude Code skills become a shared engineering artifact; the AI Expert Suite and Salesforce Foundation Plugins institutionalize a skills library (more accuracy, less unnecessary cost); subagents and agent teams parallelize workstreams — the engineer describes the outcome, the agents find the steps.

The author acknowledges what remains hard: context management (variable CLAUDE.md file quality), agentic security (agents that act → increased blast radius), and evolving roles (becoming senior, the role of designer/PM, the execution unit shrinking to 1 or 3 people). Conclusion: the transformation "changed what was economically possible"; the ambition is to build "the most automated, agentic SDLC in the industry". A major empirical piece that validates, from the operator's side, the shift from token to outcome.