AI coding tools have gone from novelty to core infrastructure in under three years. Today, many devs use AI daily, a substantial share of new code is AI-generated, and expectations for automation are rapidly increasing.
Sonar is a company specializing in analysis of code quality and security, and they recently released a new survey – the State of Code Developer Survey. The survey provides a deep examination of how developers are using AI in real production environments, and where the real-world gaps and risks still exist.
Chris Grams is the CVP of Corporate Marketing at Sonar, and Manish Kapur is the VP of Product Marketing and Developer Relations at Sonar. In this episode, they join Matt Merrill to discuss what the survey reveals about AI-assisted development, why 96% of developers still don’t fully trust AI-generated code, how deterministic verification layers fit into agent-driven workflows, and what engineering leaders should prioritize as AI shifts from experimentation to production infrastructure.
Matt Merrill is a software engineering leader with over 20 years of experience building and scaling software teams across enterprise and product-focused organizations. His background is in backend development, cloud architecture, and distributed systems design. He currently architects and delivers software products and leads a team of engineers at DEPT® Agency. You can learn more about his work at code.theothermattm.com.
Please click here to see the transcript of this episode.
Every AI team eventually hits the same wall. The models are solid, the infra is solid, but the data coming in is hours old because the pipeline is batch when it should be streaming and nobody’s had time to fix it.
That’s not a modeling problem. That’s a pipeline problem.
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