A new phase of software reliability is taking shape as artificial intelligence and agentic AI push development teams past traditional error detection and into proactive, automated prevention.
Developers are beginning to rely on systems that not only spot defects but reason through potential failures before they materialize. It’s a shift that’s reshaping expectations for code quality, redefining how teams think about monitoring and accelerating remediation from a reactive chore into an automated safeguard, according to Milin Desai (pictured), chief executive officer of Sentry, legally known as Functional Software Inc.
“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,” Desai said. “That’s the closed-loop that our customers have wanted.”
Desai spoke with Christophe Bertrand as part of theCUBE’s coverage of AWS re:Invent, for an exclusive interview on theCUBE, News Media’s livestreaming studio. They discussed how agentic AI is reshaping the developer workflow and how Sentry is evolving from observability to proactive bug prevention through a reasoning layer. (* Disclosure below.)
Enhancing agentic AI for developers with reasoning
Seer, Sentry’s new reasoning layer that turns production error data and traces into root-cause insights, is integrated with more than just an enterprise’s production data. Instead, it also takes advantage of its existing ecosystems, Desai told theCUBE. Once the root cause for a problem has been found, it can engage with an in-house coding agent to write the fix — and, increasingly, to stop bad code before it ever reaches production.
“We are catching hundreds of thousands of bugs right now,” he said. “Preventing them, not catching them, preventing them from getting shipped, which is a whole different value play.”
Sentry started with error monitoring for developers and has expanded into a broader code monitoring platform that ingests telemetry such as performance traces, logs and session replays across web, mobile and backend services. That rich production context is what Seer taps into so it can recommend fixes and flag risky changes before they ever hit production — a concrete example of agentic AI for developers embedded directly into the workflow.
“I expect every developer to be AI-assisted,” Desai said. “That’s going to result in great productivity and great experiences in terms of software that is built and products that are built in general.”
Here’s the complete video interview, part of News’s and theCUBE’s coverage of AWS re:Invent:
(* Disclosure: Sentry sponsored this segment of theCUBE. Neither Sentry nor other sponsors have editorial control over content on theCUBE or News.)
Photo: News
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