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Lightrun's Or Golan demos the Runtime Aware PR Verifier, a new Lightrun product that simulates pull requests against live runtime behavior before you merge. Watch use Lightrun to simulate an AI-generated PR, identify the affected production flows, and uncover a hidden risk that static review would miss. Instead of only asking whether the code looks correct, Runtime Aware PR Verifier checks whether the change matches how your system actually behaves in production.

Latency spikes are easy to detect. Understanding why they happened is the hard part. Gidi Freud explains how Lightrun helps engineers debug latency spikes by automatically capturing runtime context when a execution of code exceeds a defined threshold. Instead of only seeing that a method or code block was slow, you can capture local variables and source location from the exact execution that crossed the threshold.

Lightrun just launched the new AI-native PR verifier.

Lightrun's Gidi Freud demonstrates Ask Prod, the latest Lightrun AI Skill that teaches AI coding agents how to use Lightrun to answer production questions with live runtime evidence. Watch Codex use the skill to discover runtime sources, collect focused runtime data, adapt its investigation, and return an evidence-backed answer. Compatible with Claude Code, Cursor, GitHub Copilot, and other AI coding agents through the Lightrun MCP.

Lightrun's Gidi Freud demonstrates how your AI coding agent can now investigate and fix production errors, autonomously. Watch how Cursor, guided by Lightrun's Error Remediation skill, picks up a Sentry error, instruments the live service with a runtime snapshot, captures real evidence, and opens a validated PR for approval.

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.