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Equation 10 · Comparing the Main Approaches to AI Agent Architecture

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h(j)h^{(j)}

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disjoint by construction, worker i ’s error cannot enter worker j ’s context directly — it can only reach the supervisor, and only in whatever compressed form the worker chooses to report. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

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h(j)h^{(j)}

Symbol h^(j)

disjoint by construction, worker i ’s error cannot enter worker j ’s context directly — it can only reach the supervisor, and only in whatever compressed form the worker chooses to report.

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superscript

superscript

A raised number can be a power. When it is a label or bound, it selects a case or the upper limit of a sum; the formula’s structure distinguishes these uses.

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Because h(i)h^{(i)} and h(j)h^{(j)} are disjoint by construction, worker i ’s error cannot enter worker j ’s context directly — it can only reach the supervisor, and only in whatever compressed form the worker chooses to report. That disjointness is the formal reason this pattern offers stronger containment than the single loop for genuinely independent subtasks, and it is also exactly why the pattern is documented to struggle when subtasks are not independent: the architecture has no channel for worker i to see worker j ’s intermediate state even when the task actually requires it. Cost rises with the documented multiplier, latency improves only to the extent that subtasks are truly parallelizable,…
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Because h(i)h^{(i)} and h(j)h^{(j)} are disjoint by construction, worker i ’s error cannot enter worker j ’s context directly — it can only reach the supervisor, and only in whatever compressed form the worker chooses to report. That disjointness is the formal reason this pattern offers stronger containment than the single loop for genuinely independent subtasks, and it is also exactly why the pattern is documented to struggle when subtasks are not independent: the architecture has no channel for worker i to see worker j ’s intermediate state even when the task actually requires it. Cost rises with the documented multiplier, latency improves only to the extent that subtasks are truly parallelizable, and debuggability gets harder in a specific way — failures are now spread across several separate transcripts that something has to reconcile after the fact, rather than sitting in one place.

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