A transformative phase in software reliability is underway, as advancements in artificial intelligence (AI), particularly agentic AI, are urging development teams to go beyond traditional error detection methods. Organizations are increasingly leaning on systems that not only identify defects but also proactively anticipate potential failures before they occur. This evolution is revolutionizing standards for code quality and altering how teams approach monitoring and rapid remediation, shifting from reactive tasks to automated safeguards. Milin Desai, CEO of Sentry, formally known as Functional Software Inc., emphasizes this shift in expectations.
Desai noted, “The ability to take this deep context that Sentry has around what’s broken, to then apply it with AI, gives you 95% accuracy in root cause.” He highlighted that this represents the closed-loop solution that customers have long desired. In an exclusive interview with Christophe Bertrand on theCUBE, part of SiliconANGLE Media’s coverage of AWS re:Invent, Desai elaborated on how agentic AI is reshaping the workflow of developers. He described how Sentry is evolving from traditional observability to proactive bug prevention through the introduction of its reasoning layer.
This reasoning layer, dubbed Seer, enhances developers’ capabilities by converting production error data and traces into actionable root-cause insights. Desai explained that Seer integrates with more than just production data; it also leverages existing ecosystems to provide a comprehensive view of issues. Once a problem is identified, it can collaborate with internal coding agents to not only implement fixes but also prevent problematic code from reaching the production stage. “We are catching hundreds of thousands of bugs right now,” Desai stated. “Preventing them, not catching them, preventing them from getting shipped, which is a whole different value play.”
Sentry originally focused on error monitoring but has evolved into an extensive code monitoring platform that processes various telemetry data, including performance traces, logs, and session replays across web, mobile, and backend services. This vast reservoir of production context is utilized by Seer to recommend fixes and flag risky changes before they can impact production, exemplifying how agentic AI can be integrated directly into the developer workflow. Desai expressed a forward-looking vision: “I expect every developer to be AI-assisted. That’s going to result in great productivity and great experiences in terms of software that is built and products that are made.”
For those interested in gaining deeper insights, the full video interview is available as part of SiliconANGLE’s ongoing coverage of AWS re:Invent.
Sentry sponsored this segment of theCUBE, and it’s important to note that neither Sentry nor any other sponsors exert editorial control over the content produced by theCUBE or SiliconANGLE.
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Original Source: https://siliconangle.com/2025/12/05/agentic-ai-bug-prevention-awsreinvent/
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Publish Date: 2025-12-06 03:35:00
