Dissecting the typed-decision hype: Jev, Laya, or your own classifier
The tables make Jev and Laya winners on different slices. The choice depends on where labels are defined and how much labelled data already exists.
Term
Evaluation
Laya has open weights. You own the operations
Laya is a non-autoregressive decision model under Apache 2.0. It trades the convenience of a hosted API for control over running, evaluating, and specializing the model.
Jev guarantees the shape, not the decision
Jev trades text generation for typed decisions with probabilities. The idea works when the answer space is closed, the question is narrow, and code stays in control.
The benchmark resets the repository. Your team does not
Coding agents look more capable when every task starts from a clean checkout. New benchmarks show the cost that appears when patches, decisions, and technical debt carry into the next job.
Evaluating AI Agents Beyond the "Vibes Check": How to Measure What Actually Matters
Your agent nailed the demo and everyone loved it. But how do you know it actually works? If the answer is 'we tested it and it seemed fine', you are operating in vibes mode. And vibes don't scale.