multi-model routing
AssessTechniques
Selecting among multiple models based on task, cost, latency, or quality requirements.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 6InfoQ·10/15/2026researchWhat 25 Trillion Tokens Reveal About AI Agent Adoption
Brendan O’Leary argues that real-world AI adoption depends more on trust and reliability than on model benchmark performance. Using large-scale usage data, he outlines an adoption ladder and highlights common failure points in context construction, multi-model routing, and feedback loops for scaling agentic workflows.