Estimation question

Estimate the LLM cost per Lindy agent run and its impact on pricing.

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What this question tests

Tests structured estimation of unit economics: tying LLM inference cost to a per run cost and its effect on pricing.

How to approach it

  1. Break down a typical agent run into its LLM calls: assume an average run uses 3 model calls, each with roughly 2,000 input tokens and 500 output tokens.
  2. Apply a blended token price: assume 3 dollars per million input tokens and 15 dollars per million output tokens for a mid tier model.
  3. Calculate cost per run: 3 calls times 2,000 input tokens is 6,000 input tokens, costing about 0.018 dollars, plus 1,500 output tokens costing about 0.0225 dollars, totaling roughly 0.04 dollars per run.
  4. Scale to a typical user: assume an active user runs agents 200 times a month, giving about 8 dollars a month in LLM cost per active user.
  5. Compare to pricing: if Lindy charges 30 to 50 dollars a month per user, LLM cost is roughly 16 to 27 percent of revenue, leaving room for infrastructure and margin.
  6. State clearly that token counts, model pricing, and run frequency are assumptions you would confirm against Lindy's actual usage data.

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