The Single Best Way to Reduce LLM Costs (It Is Not What You Think)

Everyone says: use caching, use cheaper models, reduce token counts. Here is the one thing that actually cuts LLM costs by 40%. The Real Problem Most LLM cost optimization advice focuses on the wrong thing: the cost per call. But the real cost driver is: making calls you do not need to make. The 40% Solution Track which LLM calls are producing valuable outputs vs. which are being ignored. I added output engagement tracking to my monitoring. Here is what I found: 35% of LLM outputs were never read by the user Another 15% were read but immediately dismissed Only 50% drove actual user actions That is 50% of LLM costs producing zero value. The Fix Add a simple check: did the user act on the output? def track_output_value ( response , user_action ): log ({ " response_id " : response . id , " user_action " : user_action , # clicked, copied, dismissed, ignored " tokens " : response . usage . total_tokens , " cost " : calculate_cost ( response ) }) If user_action == "ignored", that call was wa