Operations | Monitoring | ITSM | DevOps | Cloud

In this video, Lightrun’s Dan Putman demonstrates what happens when Lightrun MCP is integrated within Claude Code. See how, once activated, Claude can ask specific questions about what services it can see and instrument in order to perform a deep investigation in production to get to a validated root cause analysis without the friction of redeploying or switching contexts.

Lightrun’s Dan Putman demonstrates the power of the latest Lightrun MCP skill. Watch how your AI code agent can now debug live applications directly in production. By connecting OpenAI's Codex to real-time runtime data via the Lightrun MCP, engineers can now generate and validate hypotheses using live telemetry and snapshots, without breaking flow. Ready to bring runtime context to your AI agents?

In this video, Dan Putman, Solution Architect at Lightrun, walks you through the power of Lightrun AI SRE. He shows how it transforms automated incident response and platform reliability by correlating signals from Monitoring tools and Incident management systems with live runtime code execution to identify and verify root causes in real time.

In this video, Lightrun's Moshe Sambol walks you through the power of Lightrun MCP and Runtime Context. A game-changer for AI-assisted development. This integration lets developers debug live issues, inspect real-world variables, and verify fixes across environments, all without leaving the IDE. With Lightrun MCP, you can: Capture live transaction state directly from Staging and Production. Identify root causes using real runtime values, not just static code. Verify fixes instantly without redeploying or context switching.

Lightrun R&D Team Lead Or Galon and Engineer Roy Chen demo how you the new Lightrun MCP allows AI coding assistants to access Runtime Context, and validate how software will behave in production.

Intermittent production bugs are hard to debug and rarely reproduce locally. Teams fall into a loop of adding logs, and every rollback slows them down. In this demo, R&D team leads Maor Yaffe and Or Golan show how an AI assistant can verify production issues using real runtime data, without redeploying. By connecting Cursor to Lightrun MCP, the agent inspects live production behavior, collects real variable values, and confirms the root cause with evidence instead of assumptions.

We’re entering a new era of AI-accelerated software development. Teams that successfully integrate AI coding assistants into their daily workflows are already seeing significant productivity gains, while those that don’t risk falling behind.

Introducing Runtime Context for AI agents The next evolution in autonomous software development. The Lightrun MCP connects IDEs and AI assistants to real runtime data, giving agents and developers the context they need to write, validate, and debug code with confidence. With Runtime Context, AI agents can: Reliable, AI-accelerated engineering starts here.

This video showcases how with Lightrun developer observability platform, developers can leverage the AI debugger within the platform plugin to swiftly identify critical code level issues through automated hypothesis and insertion of debugging actions at runtime (Lightrun dynamic logs, virtual breakpoints (Snapshots) and more. That helps reduce MTTR to mere minutes.