Research Agents
Iterative Retrieval Loops and Stopping Criteria
Deciding when AI agents should stop searching the web, not just how to search iteratively.
Everett Nadkarni
Features Editor · · 12 min read
Deciding when AI agents should stop searching the web, not just how to search iteratively.
Memory systems fail not because context windows are small, but because models lose signal in noise.
Research agents need to verify sources before trusting them, not after confidently citing them.
Research agents need loops, not one-shot retrieval, to handle ambiguous questions and live data.
Research agents dig deeper but cost more; answer engines are fast and cheap.
How agentic design patterns break down when your agent's tools hit live web data.
Prioritized queues, domain affinity, and deduplication keep crawlers fast and polite at scale.