Latency Budgeting for Search-Augmented Agents
Allocate latency to every pipeline stage, not just the LLM.
Allocate latency to every pipeline stage, not just the LLM.
Understanding rate-limit algorithms prevents retry logic from making outages worse.
Agents stumble when knowledge is stale, not when reasoning fails.
Live web data replaces hallucination with auditable facts.
Smaller, focused contexts produce more reliable outputs than enormous ones.
General-purpose scrapers fail AI pipelines by delivering boilerplate alongside content.
Research agents improve by refining queries across multiple retrieval steps instead of one.
Four modular agents decompose research tasks for independent optimization and scaling.
Optimize each RAG phase together, not in isolation, to avoid silent failures.
Search-driven agents outperform search-augmented ones on freshness-critical tasks.