Preferences > Benchmarks: Model Routing for How Teams Actually Build
Archana Kamath, Tyler Gillam
- When
- Thursday, July 212:05 PM – 12:25 PM · 20 min
- Where
- Leadership 2San Francisco, CA · imported from ai.engineer's public schedule feed
About this session
There is no best model. There's only the right model for a given task, and the right model depends on your team's preferences, not a benchmark score. This talk makes the case for preference-aligned routing: choosing models by the constraints that actually matter — cost, latency, task type, model preference — instead of a single leaderboard number. We'll demo a sub-200ms routing decision running on a purpose-built 30B MoE model with no application code changes, walk through real coding workflows routing most traffic to open models without losing accuracy, and show where this goes next: evals, caching, and personalization.
Speakers (2)
VP of Engineering, Digital Ocean
Archana Kamath is VP of Engineering at DigitalOcean, working across infrastructure, compute, networking, and AI infrastructure. Her DigitalOcean profile content emphasizes customer-centric infrastructure and product engineering for cloud and AI workloads.
Senior Software Engineer II - Agentic AI, Digital Ocean
Tyler Gillam is a Senior Software Engineer II working on Agentic AI at DigitalOcean and a core engineer on DigitalOcean's Inference Router, focused on intelligent model routing by cost, latency, task type, and model preference.
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