18 minutesAWS re:Invent 2025 - Implementing Human-in-the-Loop Controls for Multi-Agent AI Systems (CNS428)
See how approval gates can be implemented as explicit workflow checkpoints rather than informal manual review after something goes wrong.
Matthew Berman. Walks through the LMSYS RouteLLM paper and code: a small classifier sits in front of a strong/weak model pair and decides which one to call, hitting roughly 95% of the strong model's quality at a fraction of the cost. The view count is under the usual 100k bar, but for the specific "show me real model routing, not just model comparisons" niche this is the cleanest explanation on YouTube and lines up directly with the article's quality/cost tradeoff section.
Model names, pricing and capabilities change quickly. Use this for the decision pattern, then verify current model behavior before adopting it.
Evaluate model-routing tradeoffs between quality, cost and reliability before adding orchestration complexity.
Comfort reading Python and calling model APIs; the primary pick's tier map helps.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
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