Define regressions
Separate expected behavior from observed outputs.
Practical AI · EDITION 1.0.0
Build a Prompt Regression Test Suite
Create an offline comparison harness with explicit expectations, preserved fixtures, failure reasons and bounded release gates.
By Sanjaay Gowda T S · For python developers maintaining prompts and generated responses.
You need: Python dictionaries, lists and tests; Basic JSON and terminal use
Runtime and hardware details
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Python dictionaries, lists and tests; Basic JSON and terminal use.
Full setup and scope ↓$2.99USD · one-time purchase
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review remains pending. Automated checks and agent review are not certification.
PDF + EPUB + companion project. Any applicable tax is shown at checkout. Single-reader ebook terms; companion code is MIT licensed.
TRY THE FREE SAMPLE
See how the guide teaches.
Read 7 sample pages to explore the introduction, first chapter and teaching approach before you choose the complete edition.
Read free sample PDF · No checkout required
WHAT YOU WILL LEARN
Understand each part.
Inspect every boundary.
Build explainable checks
Track decision, phrase and citation failures by case.
Govern prompt changes
Preserve versions and block incomplete or misleading comparisons.
INSIDE THE BOOK
9 focused chapters.
- Define a regression contract
- Build cases with independent expectations
- Keep outputs and prompt versions
- Implement checks that explain failures
- Compare changes by case
- Handle variability and repeated runs
- Protect the test set from leakage
- Use gates without hiding old failures
- Maintain a useful regression suite
Your download includes
- 21-page tagged PDF with linked contents
- Reflowable EPUB for ebook readers
- Local Python project, fictional input, recorded expected JSON output and 12 companion tests
- 3 explanatory diagrams
- 9 chapters with exercises and worked answers
Before you begin
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Learning prerequisites: Python dictionaries, lists and tests; Basic JSON and terminal use.
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review is pending.
The included examples are synthetic teaching material. Model access, software subscriptions, hosting, ongoing updates and consulting are not included.
CLEAR EXPECTATIONS
Before you buy.
What will I build?
Create an offline comparison harness with explicit expectations, preserved fixtures, failure reasons and bounded release gates. The local companion uses fictional teaching fixtures. Project limits: Compares saved synthetic outputs; prompt texts are fingerprinted and never executed. Substring and citation-ID checks do not establish factual correctness.
What was tested?
The 12 companion tests passed on the packaged project. The supplied fictional fixture produced its recorded expected JSON output. EPUBCheck reported no errors or warnings; DAISY Ace and PDF/UA automated checks passed. These local teaching checks are not production accuracy claims or certification. Independent human technical, editorial and assistive-technology reader review remains pending.
How do I get the files?
Complete the secure Lemon Squeezy checkout to access the PDF, EPUB and companion ZIP. Keep your receipt and download access private. This is a one-time purchase of edition 1.0.0; ongoing updates and consulting are not included.
Can I share the book or the companion code?
The full ebook is licensed to one reader. The labelled free sample may be shared unchanged. The companion project is MIT licensed and may be adapted or shared with its licence notice. See the exact ebook terms.
Keep improvements, regressions and old failures visible.
One book. A complete learning project. Evidence you can inspect.
AI-assisted · Independent human review pending
$2.99USDBuy ebook