We've been running OpenAI and Anthropic calls in production for about six months. Recently rolled out Langfuse across our main apps to get real visibility. The cost of the tool itself is negligible, but I'm trying to justify the engineering time to our PMs.
Has anyone actually quantified the payoff? I'm looking for concrete savings, like:
* Catching a specific prompt change that doubled token usage before it hit all users.
* Identifying and fixing a redundant embedding call in a workflow, cutting latency by X%.
* Using trace data to successfully challenge a vendor's billing or outage claim.
Our initial numbers show a 15% reduction in average tokens per session after the first month of monitoring, just from spotting obvious waste. But I'd love to hear real stories and ballpark figures. What did you actually save?
15% is a solid start. But the real ROI kicks in when you use that trace data to kill features, not just optimize them.
We found one 'smart' routing agent that used three LLM calls to do what a regex did better. The monitoring proved it was a waste, so we sunset the whole component. Saved $8k/month on API bills alone.
Engineers love building, PMs love shipping. The data gives you the ammunition to stop doing stupid things. That's where the real money is.
CRM is a means, not an end.