Some Failures and Lessons Learned Using AI in our AI company
Some Failures and Lessons Learned Using AI in our AI company

Abstract: 

We started on an exciting journey for AI-driven Engineering to apply AI in our own company. With enthusiastic developers, nearly limitless cloud resources, and a magical AI product, what could possibly go wrong?
Turns out, a lot.
Borys and Dustin, who lead the Engineering Productivity domain within DataRobot, will tell you some stories of how they use the DataRobot AI platform to improve R&D operations and efficiency.

Session Outline
The exciting promise of AI-driven engineering (10 mins)
Use case: Triaging JIRA tickets using AI (10 mins)
Use case: Optimizing cloud compute resource allocation by predicting container sizes (15 mins)
Lessons learned (20 mins)
Q&A (Last 15 mins of 75 mins slot)

Bio: 

Borys believes that the software development world could use an upgrade and that all engineers can boost their productivity beyond their current level if they start being scientific and pragmatic about their development processes.
Borys and his team are pioneering an emerging software development discipline to discover how engineering can make R&D more productive and developers happier.