The Organization of Inference: Information, Resource Constraints, and AI Production
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TL;DR - Controlled software-engineering experiments show that AI performance depends not only on token capacity but also on how task information and resources are allocated across planning and execution. Information-rich planning benefits substantially from larger budgets, while direct execution plateaus.
- Direct execution achieved 59.6% success at both 12,000- and 24,000-token ceilings.
- Information-constrained planning improved from 36.2% to 51.2%, narrowing its deficit by 15 percentage points.
- Giving a read-only planner access to the task issue increased success by about 16 percentage points at 12,000 tokens.
- Task-informed planning trailed direct execution by about 10 points at 12,000 tokens but led it by 29.6 points at 24,000 tokens.
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The Organization of Inference: Information, Resource Constraints, and AI Production
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Hugging Face upvotes 1
TL;DR - Controlled software-engineering experiments show that AI performance depends not only on token capacity but also on how task information and resources are allocated across planning and execution. Information-rich planning benefits substantially from larger budgets, while direct execution plateaus.
- Direct execution achieved 59.6% success at both 12,000- and 24,000-token ceilings.
- Information-constrained planning improved from 36.2% to 51.2%, narrowing its deficit by 15 percentage points.
- Giving a read-only planner access to the task issue increased success by about 16 percentage points at 12,000 tokens.
- Task-informed planning trailed direct execution by about 10 points at 12,000 tokens but led it by 29.6 points at 24,000 tokens.