Operations
Model Evaluation Sprint
Compare AI models on the work your team actually does before changing a production workflow.
- Outcome
- A documented model selection
- Time
- Half day
- Level
- Starter
BEFORE YOU BEGIN
Set up the work.
Suggested toolkit
- Test set
- Models
- Scorecard
- Review panel
You will make
- Representative test set
- Weighted scorecard
- Cost and latency notes
- Selection rationale
STEP BY STEP
Run the workflow.
Work in sequence and keep each intermediate artifact. Review the result at every stage before spending time on the next one.
- 01
Sample real work
Create a small test set from representative tasks, difficult edge cases and known past failures. Remove sensitive information.
- 02
Define the rubric
Weight accuracy, usefulness, style, speed, cost and safety according to the workflow. Decide pass criteria before seeing results.
- 03
Run blind comparisons
Use the same inputs and conditions for every model. Hide model names from reviewers where possible to reduce preference bias.
- 04
Choose with evidence
Document results, failure patterns and operating cost. Keep the test set so the decision can be repeated when models change.
QUALITY GATE
Before you call it finished
01The output matches the stated outcome.
02Sources, settings and intermediate files are saved.
03A person has reviewed the result and edge cases.
04The next person can repeat the process.