devopsy.kinsta.cloud

Author: Mike Vizard

  • The Next DevOps Frontier: Governing Models, Agents and Code

    The Next DevOps Frontier: Governing Models, Agents and Code

    Anaconda CEO David DeSanto explores what it takes to make AI-native development practical, secure and scalable for modern engineering teams. DeSanto reflects on his journey from leading product at GitLab to stepping into the CEO role at Anaconda, and why the next wave of software delivery will be shaped by the intersection of open source, DevOps practices and AI governance.

    Software is increasingly assembled rather than written. With dependencies pulled from countless repositories, the software supply chain has become one of the largest sources of risk—especially as attackers target packages and organizations push more workloads into production faster. DeSanto explains how trust, curation and reproducibility matter when teams are depending on thousands of third-party components to build and ship applications.

    From there, they turn to the evolving needs of AI development workflows. Beyond packages, teams now have to account for models, agents and new “AI supply chain” artifacts that also require security controls, policy enforcement and governance. DeSanto outlines how organizations are trying to move from experimentation to production with guardrails in place—tracking lineage, performance characteristics and vulnerabilities, and creating an “AI bill of materials” that extends the same discipline DevOps teams expect in traditional pipelines.

    A standout theme is developer enablement. As AI raises the cost and complexity of building and running models, the ability to test and iterate locally—then carry those changes forward into production—becomes a practical advantage. DeSanto emphasizes a hands-on approach: staying close to builders, listening to customers, and making it easier for teams to adopt new capabilities without sacrificing control.

    As AI becomes part of everyday software delivery, the winning platforms will be the ones that reduce friction for developers while strengthening security and governance across the full lifecycle.

  • 60% of Code Is AI-Generated—Are We in Trouble?

    60% of Code Is AI-Generated—Are We in Trouble?

    Jonathan Rende, chief product officer at Checkmarx, tackle’s one of the most urgent questions in AppSec right now: what happens when AI starts writing the majority of your software?

    With estimates that as much as 60% of code is being generated by AI in some environments—and that AI-authored code is already finding its way into production—the conversation quickly moves past novelty and into operational reality. The central theme is trust: should AI-generated code be treated differently than human-written code, and are organizations holding it to a higher standard simply because they’re less confident in how it was produced?

    Rende unpacks how developer behavior is changing as copilots and agents make it possible to generate thousands of lines of code quickly, often faster than teams can realistically review it. That shift increases pressure on DevSecOps “outer loop” controls—static analysis, dynamic testing, supply chain security, and governance—to catch defects and vulnerabilities before they become incidents. The issue isn’t only volume; it’s also context. Even as models improve, secure outcomes still depend on how developers prompt, validate, and integrate AI output into real systems.

    They also explore the evolving benchmark landscape for measuring model security performance and what those trends suggest: AI-generated code may be getting less vulnerable over time, but “less vulnerable” isn’t the same as “secure.” Rende argues that while common vulnerability patterns may decline, higher-order logic flaws and transitive issues will remain difficult—and may even become more prominent as applications and AI-driven supply chains grow more complex.

    Whether code is written by humans or machines, production software still demands rigorous, continuous security testing—because in the AI era, the attack surface is expanding as fast as delivery velocity.