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Equation 11 · Part 1 · The Unit Economics of a Token

Symbol T_in

Tin(k)=∑j=1k(b+ja)=kb+a k(k+1)2T_{\mathrm{in}}(k) = \sum_{j=1}^{k} \left( b + j a \right) = k b + a \, \frac{k (k+1)}{2}
TinT_{\mathrm{in}}

What this part means

TiT_in is part of the quantity the equation computes from the expression on the right.

Its job in the formula

TiT_in is part of the quantity the equation computes from the expression on the right.

The passage around this formula

The nonlinearity that surprises people does not live in this equation, which is linear. It lives in agent loops. Suppose a loop runs for k steps, each step appends roughly a tokens of tool output and assistant text, and the context started at b tokens. The total input billed across the whole loop is then Tin(k)=∑j=1k(b+ja)=kb+a k(k+1)2T_{\mathrm{in}}(k) = \sum_{j=1}^{k} \left( b + j a \right) = k b + a \, \frac{k (k+1)}{2}. which is quadratic in the number of steps. Doubling the length of an agent trajectory roughly quadruples its input billing. This is why cache hit rate dominates agentic economics: prefix caching converts most of that quadratic term into reads at one tenth the price, and a workload that loses its cache to a time-to-live expiry or an effort change pays the full quadratic […

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Learn the underlying idea

A subscript is a label attached below a symbol. It often selects a time step, component, category, or member of a sequence.

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Sources cited in the article section

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