Why building a workplace ChatGPT requires a great crawler

This post details the engineering challenges and solutions for building a quick, resilient, and scalable enterprise data crawler. Key technical contributions include: defining uniform transient error handling, implementing retry mechanisms with partial-completion tracking for idempotent execution, managing diverse work types (incremental, full, webhooks) to prevent staleness, prioritizing crawl tasks against API quotas with weighted workloads and dynamic rate limit policy accommodation, and employing regular full crawls with validation to purge stale data safely. The system is designed for horizontal scalability to handle varied datasources, complex permission schemas, and API gaps.