AI is generating more code while organizational delivery speed is not increasing, with industry reports showing a slight slowdown and more bugs. Engineering work must be made easier and guarded to prevent errors whether code comes from humans or AI. Proliferation of unique pipelines created thousands of hard-to-manage variations that slow teams. Template-driven, reusable pipelines with built-in policies surface failures early and enable rapid fixes. Modern CI/CD platforms need scalable, automatable pipelines instead of stitched-together tools, with AI assisting test generation, troubleshooting, and infrastructure management. The trend moves toward platform engineering emphasizing context and governance.
Durkin noted that while AI is generating more code, organizations are not necessarily moving faster. In fact, industry reports show a slight slowdown, along with an uptick in bugs. The challenge, he said, lies in making it easier for engineers to do the right thing while putting guardrails in place to prevent errors, regardless of whether the code was written by a developer or an AI.
One issue is the proliferation of pipelines. In the past, teams often created a separate pipeline for every application, leading to thousands of variations that were difficult to manage. Durkin argued for a template-driven approach, where reusable pipelines with built-in policies make failures visible early and allow fixes to be made quickly - more like a video game that encourages iteration than a static approval process.
Durkin also addressed the paradox that while AI can speed up some tasks, it may still extend delivery timelines. He sees this as part of a broader shift toward platform engineering, where context and governance matter more than raw speed. Increasingly, these conversations are moving beyond engineering leadership to CEOs, COOs and boards, as software delivery becomes central to business competitiveness.
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