AI can write more code. Can your engineering team safely ship it?
AI coding assistants and agents are accelerating software production, but code review, testing, security and operations still have to absorb the output. In this episode of The AI & Tech Society, we explore why the bottleneck is moving—and what CTOs, CIOs and engineering leaders need to change.
Drawing on the 2026 research discussed in the episode, we examine the gap between developer productivity and reliable software delivery. More generated code can mean more work downstream, from reviewing pull requests to finding vulnerabilities and handling incidents.
Inside the episode:
• Why faster code generation does not automatically mean faster delivery.
• How AI-generated code changes review workloads, testing and security.
• What adoption of tools such as Claude Code and GitHub Copilot means for engineering teams.
• Why specification, human judgment and operational readiness matter more as output grows.
• How leaders can build a safer, more effective AI-native software delivery system.
The leadership question is no longer just “Are our developers using AI?” It is “Can our delivery system handle the extra output without compromising quality, security or people?”
Listen for a practical perspective on leading developers in the AI era. Share this episode with your engineering team and follow The AI & Tech Society for more on AI, technology and leadership.
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