How to Build a Crawl Budget That Keeps AI Agents Fast and Predictable

Short summary

A crawl budget is the control system that keeps AI agent web-access loops predictable in production, preventing latency spikes and runaway costs. The article recommends defining a task contract (evidence needed, freshness, sources, latency, cost) before setting limits, then using a three-layer budget model: task-level, host-level, and page-level. Practical guidance covers URL prioritization scoring, escalation from simple fetch to JavaScript rendering, deduplication via content fingerprints, and politeness controls like per-host concurrency limits and backoff.

• •Define a task contract specifying required evidence, freshness, latency ceiling, and cost before crawling
• •Use three budget layers: task, host, and page — each with distinct limits on requests, renders, bytes, and retries
• •Prioritize URLs with a relevance×freshness×source-value/cost score; escalate fetch methods only when needed

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