Quick summary Target bounded decisions: Jev returns typed answers rather than free-form prose. Separate interface from speculation: the article distinguishes public behaviour from unconfirmed internals. Validate correctness: typed output still needs evaluation and calibrated thresholds. Control consequential use: log outcomes and review uncertain cases. How Jev works starts with a simple observation: most software does […]
Quick summary Evaluate actions and answers: polished text can hide a failed workflow. Check three surfaces: the outcome, tool-use path and final external state. Combine suitable graders: deterministic checks, rubrics and human review. Learn from failures: turn traces into regression cases and measure cost and constraints. AI agent evaluation starts with a simple reality: an […]
The fastest way to get value from a personal AI agent is to stop imagining an AI employee. Start with one routine that is mildly annoying, happens often, and produces work you can easily review. In a couple of hours, you can prototype a useful workflow. You cannot reasonably expect a dependable, unattended assistant that […]
Trajectory evaluation shows how a final answer can look perfect while the agent behind it has already failed. Imagine an agent that tells a support team: “The customer record has been updated.” The sentence is clear and reassuring. However, the trace may show a different story. It may select a search tool instead of an […]