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You’ve spent thousands on an AI observability platform. You’ve set up dozens of dashboards. And somehow, you still find yourself struggling to answer any question the CEO asks: Why did this customer get a hallucinated response yesterday? Why is this feature slower than it used to be? Why does this cost so much? After leading ML teams a...

Your competitor just announced their “AI-powered revolution.” The board is demanding updates on AI strategy. Your team rushed to deploy an AI chatbot for customer support, but now users are posting screenshots of it giving nonsensical answers and leaking sensitive information. You’re lying awake at night, watching each new AI advancement with gr...

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 ...

“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...