AI predicts and fixes vulnerabilities... Sentry is revolutionizing the way developers work

Artificial intelligence is transforming the paradigm of software quality management. Going beyond simple error detection, agent-based AI technologies capable of proactively preventing pre-release defects are redefining how developers work. Currently, developers are becoming increasingly accustomed to automated features that not only identify errors but also implement preventive measures before problems occur.

According to Sentry CEO Milin Desai, Sentry is leading this trend, evolving from error tracking to a predictive defect prevention architecture. At the recent AWS re:Invent 2025 conference, Desai stated, “By combining Sentry’s debugging data with AI, we can identify root causes with 95% accuracy.” He called this “the complete closed-loop solution our customers have been waiting for.”

At the core of this shift is Sentry’s new feature, ‘Seer,’ which analyzes a wide range of telemetry data from enterprise environments and infers causal relationships. Seer goes beyond simple logs or error messages, integrating various analytical signals such as performance tracing and session replay with an AI layer, enabling the detection of code anomaly signs in early development stages and automatically suggesting fixes. Notably, once the root cause of an error is identified, it can invoke AI-based coding agents to automatically generate patches, preventing problematic code from reaching production environments.

Desai emphasized, “The key difference is that we’re now stopping hundreds of thousands of errors in real time, rather than just detecting them in real time.” He highlighted that developer tools are shifting from reactive aids to real-time control instruments. He predicts that developers who do not use AI in their work will soon become rare, and that all developers will naturally work in AI-assisted environments.

Sentry has evolved from a developer-centric error tracking platform to a comprehensive code monitoring system. With the full deployment of AI features like Seer, development teams are moving beyond simply observing data collected in production environments to building pipelines that proactively improve code quality.

Artificial intelligence and agent systems are no longer experimental technologies—they are redefining the reliability standards of the entire software industry. Sentry’s case is a representative example of how this technological transformation is producing tangible results. Desai made it clear: “The developer experience of the future will demand both high productivity and highly reliable system quality.” He emphasized that the integration of AI tools will become the new norm.