How to Evaluate Frontier AI and Prove Its ROI in Production
Thu, Oct 2211:00 AM PDT, 30 min
Frontier models keep improving, but a strong benchmark score doesn't show whether a model will hold up in your production environment, or whether it's worth the token spend. For many engineering leaders planning for 2027, the work has moved from just picking a model to evaluating it on real conditions and measuring its full cost and impact to ROI.
In this webinar, Sean Bell, who runs ResolveAI's Applied labs, will walk through his journey and learnings.
Decide when to go bespoke
Build evals that reflect reality
Avoid the DIY cost trap
Frame AI ROI accurately
Featuring
Sean Bell
ResolveAI Labs, previously Director of AI Research, Meta Superintelligence Labs
In this session, you will learn how to:
Decide when to go bespoke
Know when a domain-specific model beats a general one.
Build evals that reflect reality
Benchmark on live production incidents, not offline test sets.
Avoid the DIY cost trap
Spot early when a cheap in-house build is heading toward a large maintenance bill.
Frame AI ROI accurately
Budget for the full long-term cost of ownership, not just the one-time build.
