Lesson 260 of 2116
Regression Testing for Prompts
Prompts are code. Code needs tests. Here is how to stop silently breaking your system each time you tweak a prompt.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Every Prompt Edit Is a Release
- 2regression test
- 3prompt version control
- 4CI
Concept cluster
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Section 1
Every Prompt Edit Is a Release
Prompts live in files. Teams edit them and deploy without any automated check. Then a customer reports that the assistant now forgets to include the refund policy. Regression tests stop this loop.
A minimal regression suite
- 120-50 cases, each with expected properties (not necessarily exact output)
- 2A lightweight grader (keyword check, JSON schema, LLM-as-judge)
- 3A CI step that runs the suite on every pull request
- 4A diff report that shows which cases changed behavior
What to assert
Compare the options
| Assertion type | Example |
|---|---|
| Must contain | Response includes the word 'refund' when user asks for one |
| Must not contain | Response never contains 'Sorry, I am just an AI' |
| JSON schema | Response parses as JSON with required fields |
| Rubric score | LLM judge rates response at least 4/5 |
| Tone or format | First line is a greeting; sign-off is present |
Prompt regression tests look like unit tests — because they are
# A simple regression check
def test_refund_mention():
response = run_model("I want my money back.")
assert "refund" in response.lower()
assert "sorry" not in response.lower()
assert len(response) < 500Versioning the prompt
- Store prompts in version control (git)
- Tag each prompt change with a version string
- Log the prompt version with every production call
- Roll back by reverting the file
“Code that is not tested is code that is not trusted. The same is true of prompts.”
Key terms in this lesson
The big idea: treat prompts like code. Version them, test them, review them. You will sleep better.
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