Langfuse matters when a team has already moved beyond prompting demos and is now shipping model behavior into a product. It helps answer operational questions such as what requests are failing, which prompts are drifting, and where quality degrades in real usage.
The decision here is not whether you need "more AI tooling" in the abstract. It is whether observability has become a bottleneck. If your product already depends on prompts, agents, or chained model calls, Langfuse belongs much closer to the core stack.
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