Agent Loop Budget shadow
Agent Loop Budget shadow — AI retrieval, agent, evaluation, or production-reliability concept.
Definition
Agent Loop Budget is the hard cap on how far an AI agent may run its plan→act→observe loop: typically max steps, tokens, tool calls, wall-clock time, and dollar cost. Agent Loop Budget shadow is that budget object applied in a shadow context — the agent must stop or degrade gracefully when any limit is hit.
Why it matters
Without a loop budget, tool-using agents can recurse, re-retrieve, and burn spend while looking “busy.” Budgets turn agent autonomy into an operable production control: measurable, alertable, and comparable across canary/shadow/production.
Case
Shadow mode runs the agent beside production, records tool traces, and never shows the answer to users. You compare quality and cost before promoting the loop.
How to read it
Read the numeric limits (steps/tokens/tools/time/cost), the stop behavior, and which environment owns the budget. A canary budget that never trips is untested; a production budget that always trips means the workflow is mis-sized.