CI/CD has mastered deterministic checks—linting, tests, SAST, schema validation—but modern engineering risks increasingly live in the nuanced, contextual layer: “Does this change violate privacy expectations?”, “Did the UX drift from the spec?”, “Is this workflow introducing risky behavior?”

In this talk, we’ll explore non-deterministic CI gates: AI-assisted checks that evaluate context, intent, and policy, not just fixed rules. We’ll show how GitHub Agentic Workflows bring “Continuous AI” into your existing GitHub Actions pipelines by authoring automation in plain Markdown, executed by coding agents with security-first guardrails.

You’ll see practical SDLC examples—like policy/compliance analysis and UX alignment gates—where agents produce human-reviewable, structured findings and can safely trigger pre-approved operations via controlled outputs.

Walk away with a blueprint for augmenting deterministic CI/CD with agentic gates to drive faster delivery, reduced risk, improved developer experience, and smarter automation—without sacrificing governance.