Section 084 · Chapter 10, Anti-Patterns That Create False Confidence

Anti-Patterns: Treating AI Bugs Like UI Bugs

Many AI failures do not have one screen, one selector, one line of code, or one obvious owner.

retrievaltreating bugs like ui bugs

What to do

  1. Define runnable checks that exercise retrieval and treating bugs like ui bugs.
  2. Set acceptable outcomes and blocker failures for retrieval and treating bugs like ui bugs before running the evaluation.
  3. Run representative cases for retrieval and treating bugs like ui bugs and preserve the failures that would change the decision.

Evidence to preserve

  • Preserve the inputs, versions, configurations, raw outcomes, and results for retrieval, treating bugs like ui bugs needed to reproduce work on Anti-Patterns: Treating AI Bugs Like UI Bugs.
  • Report results for retrieval, treating bugs like ui bugs by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.

Expert note

At scale, use AI incident templates with reproduction envelope, trace artifacts, affected slices, suspected contributors, severity, mitigation options, and post-mitigation eval results.

Continue the conversation

Apply this to your context.

Save your product context once, then open a focused conversation that combines it with this concept.

Cite this page

Jason Arbon. "Anti-Patterns: Treating AI Bugs Like UI Bugs." Testing AI Knowledge Edition, section 84.

https://jarbon.ai/testing-ai/knowledge/ch084-treating-bugs-like-ui-bugs.html

Shared across the Knowledge Edition

Adapt every concept to your world.

Describe your product, role, users, risks, constraints, or current quality problem. This stays in this browser until you choose to send it to ChatGPT.

Saved only in this browser.0 / 2400