Dev x AI: From Bug to Fix in Minutes: AI-Powered, Safe and Fast Production Debugging
From Bug to Fix in Minutes: AI-Powered, Safe and Fast Production Debugging
You know that feeling when production breaks at 2 AM in a service you've never worked on, and you're jumping between 5 different dashboards trying to piece together what's happening?
Logs in one tab. Database queries in another. Monitoring metrics in a third. Code in your editor. Documentation somewhere else.
And worse: you're guessing. Making assumptions. Hoping you're looking in the right place.
What if you could stay in one place and just ask:
"Why are payments failing for users in the EU region since 2 PM?"
"What changed in the authentication flow between yesterday and today?"
and AI jumps between all those systems for you, investigating logs, databases, and code to give you data-backed answers instead of hunches?
This session shows you how developers are debugging production systems with AI, turning hours-long investigations into minutes, guesswork into data-driven evidence.
What You'll See (Live):
Connecting the dots across systems, Watch us debug a real production issue by asking AI to investigate across multiple systems: application logs, database records, observability metrics, and code repositories, all in one conversation
See the correlation happen, AI doesn't just search one system at a time. Watch it find an error spike in your logs, then automatically check what queries were running in the database at that exact moment, correlate with performance metrics, and identify the code that triggered it
Evidence-based investigation, No more "I think it might be..." Watch AI present concrete findings: "Found 127 errors starting at 3:47 PM. Database was slow at the same time. This code change went out 10 minutes before the errors started."
One conversation, many systems, Instead of opening 5 dashboards and manually trying to connect what you see, ask questions and let AI jump between your logging platform, database, monitoring tools, and code to piece together what actually happened
Debug code you've never seen, Thrown into an unfamiliar service? AI reads the codebase, understands the architecture, and guides you through the investigation, even if you've never worked on that part of the system before
You'll Learn:
How to give AI safe, read-only access to your production data
What MCP (Model Context Protocol) is and why it matters for debugging
How to set this up for YOUR stack (works with any log system, any database, any monitoring tool)
Real debugging workflows: from "something's broken" to "here's the fix" in minutes
What to do (and what NOT to do) when connecting AI to sensitive systems
Who Should Come:
Any developer who's tired of:
Ctrl+F through endless log files hoping to find the right clue
Debugging based on intuition instead of evidence
Losing context while jumping between 10 different browser tabs
Spending more time gathering data than actually fixing the issue and then losing context half way
Making educated guesses instead of having hard data
What You'll Walk Away With:
A mental model for AI-assisted debugging (not just code generation)
Starter setup for connecting AI to your own tools
Real patterns that work in production (from teams already doing this)
Ideas you can try on Monday morning
Why This Matters:
Most developers are using AI to write code. Few are using it to debug code. But debugging is where the real time sink is.
No prior AI experience needed. If you can write code and you've debugged production issues, you're ready for this session.
Real demos. Real production systems. Real debugging workflows. No slides full of "imagine if..." just "here's how it works."