Agentic property-based testing: finding bugs across the Python ecosystem

Registration Instructions
This is a paid event ($5 general admission, free for students & job seekers) with limited tickets - you must RSVP on Luma to secure your spot.

Event Description
​Testing software for bugs and vulnerabilities is typically difficult as it requires the developer to think through edge cases.

​In this talk, Muhammad Maaz will present work on using LLM-based agents and Hypothesis, a property-based testing framework, to automatically generate and test general properties of code.

Event Schedule
6:00 to 6:30 - Food & introductions
6:30 to 7:30 - Presentation & Q&A
7:30 to 9:00 - Open discussion

If you can't attend in person, join our live stream starting at 6:30 pm via this link.

​​This is part of our weekly AI Safety Thursdays series. Join us in examining questions like:

• ​​How do we ensure AI systems are aligned with human interests?
• ​​How do we measure and mitigate potential risks from advanced AI systems?
• ​​What does safer AI development look like?