The AI tooling ecosystem is exploding. Every week there seems to be a new platform promising: Better traces Better evaluations Better prompt debugging Better monitoring Better cost visibility The challenge isn’t finding an AI observability tool anymore. The challenge is choosing one. If you’re building AI applications today, chances are you’ve come across names like Langfuse, LangSmith, HoneyHive, Helicone, Arize, Braintrust, or Phoenix. After exploring these platforms, I noticed something interesting: Most tools overlap in functionality, but each one is optimized for a very different workflow. This article focuses on comparing the tools themselves—not explaining AI observability concepts. Let’s dive in.…