AI
Theo’s agent-driven UI experiment shows the power and limits of iterative evaluation
Theo describes using multiple coding agents as a reviewing “council” to iteratively improve T3 Code’s interface, then applying the same hill-climbing idea to tool-use evaluations. He reports better visual consistency and a large reduction in tool-description context, but also shows that model scores vary with prompts, comparison sets and non-determinism. The experiment required roughly 17.6 hours of parallel runtime and about $400 by his estimate, making the method more compelling for measurable engineering tasks than subjective design alone.
Editorial summary · Public video captions
What matters
- The UI process used repeated reviews from several models, screenshots and comparison against other developer tools.
- Reported improvements included typography, contrast, labels, borders, focus states and more consistent visual hierarchy.
- A tool-use evaluation improved from inconsistent results to a smaller context while preserving the tested score, according to Theo.
- Theo repeatedly notes that screenshot-based ratings are subjective and model outputs are non-deterministic.
Context & caveats
- The results are the speaker’s own account of an open-source project and are not independently validated in the supplied material.
- The captions contain occasional uncertain names and transcription errors; reported costs and scores should be treated as approximate.
Why this made the edition
The complete captions support a useful practitioner analysis of iterative agent evaluation, including concrete results, costs, limitations and the speaker’s own uncertainty about subjective scoring.
Source material