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The Three Questions Every AI Eval Should Answer

Boundary · 0m · transcribed Aug 2026
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Section Insights

# 0:00

Model Deprecation Awareness

What should we know about the models in our workflows?

Every model currently in use will eventually be deprecated.

  • Models are temporary and will be replaced over time.
  • Awareness of model lifecycle is crucial for planning.
  • Users should anticipate changes in their workflows.
# 0:05

Evaluating New Models

Will new models enhance my workflow?

New models may improve workflows, and a specific harness can evaluate this.

  • New models can potentially enhance efficiency.
  • A systematic approach is needed to assess improvements.
  • Utilizing a harness can streamline evaluation of new models.
# 0:10

Compatibility of Models

Is Haiku compatible with Opus or Sonnet?

There are questions about compatibility between different models.

  • Compatibility between models is a key consideration.
  • Users need to verify if new models work with existing systems.
  • Understanding model interactions is essential for effective implementation.
# 0:15

Cost and Efficiency of New Models

How do new models compare in terms of cost and speed?

New models may be cheaper and faster, but their effectiveness needs to be assessed.

  • Cost and speed are critical factors in model selection.
  • Users should evaluate if new models meet performance standards.
  • A harness can help quantify improvements in cost and efficiency.
# 0:20

Harnessing Model Evaluation

What tools can help answer questions about models?

A harness is necessary to answer various questions about model performance and compatibility.

  • A comprehensive evaluation tool is essential for decision-making.
  • Harnesses can facilitate comparisons between models.
  • Effective model management requires systematic evaluation processes.

Transcript

0:00 Every model that we're using in all of our workflows now will be deprecated at some point in the future. There's still the other two pieces. Another is, "Hey, a new model came out. Will it improve my workflow?" The same harness can answer that question. And then the third question is, say you're running Opus or Sonnet, will Haiku work? >> >> It's cheaper, it's faster, is it good enough? How much cheaper? How much faster? So you need a harness that can answer all of these questions.

Summary

The discussion focuses on the inevitability of model deprecation in workflows and the need for a system to evaluate new models' effectiveness and compatibility. A harness is proposed as a solution to assess improvements, cost-effectiveness, and speed of new models.

- All models in current workflows will eventually be deprecated.
- New models may offer improvements, but their effectiveness needs evaluation.
- Compatibility of new models with existing systems (e.g., Opus, Sonnet) is crucial.
- A harness is necessary to answer questions about model performance, cost, and speed.
- Key considerations include how much cheaper and faster new models are compared to existing ones.
- The harness should facilitate informed decisions regarding model adoption.

Questions Answered

What should we know about the models in our workflows?

Every model currently in use will eventually be deprecated.

Will new models enhance my workflow?

New models may improve workflows, and a specific harness can evaluate this.

Is Haiku compatible with Opus or Sonnet?

There are questions about compatibility between different models.

How do new models compare in terms of cost and speed?

New models may be cheaper and faster, but their effectiveness needs to be assessed.

What tools can help answer questions about models?

A harness is necessary to answer various questions about model performance and compatibility.

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