Introduction
North, Cohere's agentic AI workspace, can route each employee request to different Command models. Command A is fast and efficient. Command A Reasoning, released in 2025, "thinks" through a problem step by step before answering, which improves accuracy on complex, multi-step tasks but takes longer and uses more compute. Today North uses Command A by default and lets admins enable reasoning for specific agents.
The prompt: "Should North make Command A Reasoning the default model for all chat requests?" This is a classic quality versus speed and cost trade-off. The answer depends on which requests benefit from reasoning, how much latency users tolerate, and who pays for the extra compute.
I'll clarify the context, classify the trade-off, understand the product, form a hypothesis, choose metrics, design an experiment, plan the analysis, set a decision framework, and recommend next steps.
Step 1
Clarifying Questions (3 minutes)
Why it matters: If most requests are simple lookups, reasoning adds delay for little gain. Expected answer: Internal sampling suggests about 25% of requests involve multi-step analysis, comparison or calculation. Impact on approach: A blanket default may be wasteful; routing may be better.
Why it matters: In customer-hosted deployments, the customer pays for GPUs; in Cohere-managed deployments, Cohere absorbs cost within a fixed seat price. Expected answer: A mix; about half of seats are in Cohere-managed environments. Impact on approach: Cost matters directly to Cohere's margins and to customers' GPU budgets.
Why it matters: Habit formation suffers if answers are slow. Expected answer: Research suggests satisfaction drops sharply when chat answers take more than about 8 seconds. Impact on approach: Latency is a key guardrail.
Why it matters: Enables smart routing as an alternative. Expected answer: A lightweight classifier exists with roughly 85% accuracy. Impact on approach: Routing becomes a realistic third option.
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