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Equation 17 · Part 1 · The Economics and Physical Limits of Running AI Agents at Scale

Symbol c_i

ci=pin(τ+δ+(i−1)σ)+pout oˉc_i = p_{\text{in}}\big(\tau + \delta + (i-1)\sigma\big) + p_{\text{out}}\,\bar{o}
cic_i

What this part means

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

Its job in the formula

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

The passage around this formula

Because the API is stateless between calls, step i in the loop must include, as ordinary input, everything that made it into the transcript through step i-1 : the tool results, the intermediate reasoning, the earlier outputs. Call the amount a single step permanently adds to that growing transcript σ\sigma — roughly δ\delta plus oˉ\bar{o} , since both the new material a step introduces and the output it produces become part of what every later step has to resend. Without caching, step i ’s input is not just τ\tau + δ\delta ; it is τ\tau + δ\delta plus the accumulated weight of every prior step, (i-1)σ\sigma : ci=pin(τ+δ+(i−1)σ)+pout oˉc_i = p_{\text{in}}\big(\tau + \delta + (i-1)\sigma\big) + p_{\text{out}}\,\bar{o}. Summed over an n -step trajectory, that gives

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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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