The Art of Iterative AI System Development: A Practical Guide to Evaluation-Driven Improvement
Introduction: The Challenge of Improving AI Systems
Improving AI systems is hard. Unlike traditional software where you can often directly observe and fix bugs, AI systems present unique challenges:
Performance issues are often subtle and multi-faceted
The relationship between changes and improvements isn’t always clear
The development ...
Building AI Products That Actually Work: A Hard-Won Guide
“Let’s add AI to our product!”
If you’ve heard this recently (and who hasn’t?), you know the excitement - and anxiety - it can bring. After spending years building machine learning systems at companies like LinkedIn and Google, I’ve seen both spectacular successes and painful failures in AI product development.
Here’s what I’ve learned: the di...
The Real Secret to Landing Your Dream Tech Job: It's Not What You Think
After a decade in tech, including years at LinkedIn working on their job matching algorithms and now serving as VP of Engineering & Data Science, I’ve seen thousands of candidates navigate the tech hiring process. Here’s the truth that most won’t tell you: your network is worth more than all your technical skills combined.
The Uncomfortable...
Building an Automated Email Reply Agent with Pydantic AI: A Story of Simplification
After years of leading machine learning teams at companies like Google and LinkedIn, I’ve re-learned the same lesson over and over again: start simple and slowly add complexity and always prioritize observability. Recently, I embarked on an experiment with Pydantic AI to build an automated email reply agent. While the end goal was simple - autom...
15 post articles, 4 pages.