Nishil Patel

Debugging in the Dark

Stop debugging in the dark. This tool captures the complete story of a failure, using AI to pinpoint the root cause and suggest a fix.

Debugging in the Dark
#1about 1 minute

The hidden costs of traditional debugging processes

Vague bug reports lacking context and reproducibility steps lead to significant time waste and friction between developers and QA.

#2about 1 minute

Core requirements for effective bug resolution

Developers need complete context, clarity on the failure, and reliable reproducibility to move beyond "it works on my machine" arguments.

#3about 3 minutes

Capturing comprehensive bug reports with a tool

A demonstration shows how to record a user session to automatically capture video, system information, console logs, network requests, and user steps.

#4about 1 minute

A unified view for developers and QA

Bug reports are automatically created in tools like Jira, providing a shared screen with all captured data and integrations for backend logs.

#5about 2 minutes

Using AI for root cause analysis and fixes

An AI debugger analyzes logs to provide root cause analysis, suggest solutions, generate test cases to prevent regressions, and offer code fixes.

#6about 1 minute

Reducing bug resolution time by 75 percent

The tool aims to shorten the bug resolution lifecycle significantly, offering a free tier for small teams to get started immediately.

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