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While AI coding assistants help developers write code faster than ever, the traditional manual workflows for delivery, security, governance, and production readiness often create a bottleneck. In this demo, see how Cursor and Harness bridge this gap by turning AI-generated code into a safe, governed, and production-ready software delivery lifecycle right from your IDE.

You're already using AI without even thinking about it. That's the realization that kicks off this ShipTalk moment: Apple Maps quietly using on-device machine learning to learn your routes and driving habits — complete trust, zero thought. Which raises the real question: why aren't we there yet with AI in software delivery? The answer comes down to one word: guardrails. Consumer AI earned invisible trust. Shipping software hasn't — not until the guardrails catch up.

How are you teaching your agents? Are they learning on their own? Does that lead to better results? Listen to @prathameshsonpatki7217 talk about our experience running agents in production for the last 8 months that self improve!

I gave myself five prompts each to build the same app in Claude using Opus 4.8, and Codex using GPT 5.5. The results were NOT what I was expecting! See which agent built the better app, which one stumbled massively, and look at the actual numbers behind these coding agents.

Give Codex access to CI feedback and it can diagnose failures, make a fix, and keep iterating until the pipeline is green. Here's the CircleCI plugin in action.