Record the creation process for code examples separately from the technical tests they pass. Keep each listing connected to its prompt or human source, revisions, expected behavior, and final location in the book. A successful test can support a claim about behavior, but it does not establish the example's origin, permission status, or suitability for teaching.
Give each example a clear editorial purpose
Identify what the listing is intended to demonstrate and what readers need to know before using it. A short fragment explaining one operation differs from a complete runnable project. Record that distinction so reviewers do not mistake an intentionally partial example for a failed program or a demonstration for a production-ready system.
Connect the listing to the surrounding explanation and any exercise that depends on it. Give it a stable identifier that survives chapter moves. This lets the project track one example through drafting, technical review, layout, and later corrections without relying on a filename or page number alone.
Preserve the creation path
Record whether the actual code was written by a person, generated by a tool, copied from an identified source, or assembled from several contributions. Keep those components distinguishable where the history is mixed. A later editor needs to understand what entered the book, not merely which application last saved the file.
For generated drafts, retain the relevant request context and accepted result with the revision record. Do not place private credentials, live customer data, or unrelated project secrets in that record. A compact, relevant account of the creation process is more useful than an indiscriminate dump of a developer's working environment.
Separate technical correction from origin
A reviewer may repair an error, replace a dependency, or simplify a generated example substantially. Record those changes without assuming that they erase the earlier generation step. KDP's current content guidance distinguishes generated material from human-created material improved with AI, and substantial editing does not by itself remove generated-content treatment.
Keep that classification question separate from whether the code now behaves correctly. The final publication record should explain both the creation path and the checks performed. Neither answer automatically supplies the other, even when a reviewer has rewritten large portions of the listing.
Test the example against its stated purpose
Use an appropriate isolated environment and record the relevant versions, inputs, and observed output. Check the specific behavior the chapter describes rather than treating the absence of an error message as sufficient evidence. Include a reviewer with suitable technical knowledge when the example's implications go beyond a simple demonstration.
Keep the test result attached to the exact version of the listing. A later editorial change can alter a command, quotation mark, indentation, or variable name. If the accepted code changes, review whether the earlier test still applies instead of leaving a passing status attached to a different example.
Review source use and teaching clarity independently
Identify external material and dependencies that need their own source or usage review. Generated code should not be assumed to have a fully established provenance simply because it arrived without a citation. Keep unresolved questions visible and replace or remove material when its use cannot be supported appropriately.
Read the example as a learner. Check whether the explanation identifies assumptions, limitations, and the result readers should expect. A technically correct listing can still teach poorly if it hides necessary setup or presents a narrow demonstration as a generally suitable solution.
Verify the code that appears in the publication file
Compare the final displayed listing with the technically reviewed source. Inspect line breaks, symbols, indentation where meaningful, and any omitted lines. If the book includes a downloadable companion, verify that its version matches the printed explanation or clearly documents the difference.
Retain the final listing, origin record, and test evidence with the release files. Answer applicable publication disclosure questions from that documented workflow. The book's technical credibility depends on accurate behavior and clear teaching, while its publication record must also preserve how the material was created.
Frequently asked questions
Clear answers for this publishing decision.
Does passing a test prove an example is ready to publish?
It supports only the behavior actually tested in the recorded environment. Teaching clarity, source use, creation history, and the fidelity of the final displayed code still need review.
What if a human fixes most of an AI-generated listing?
Keep the original generation step and later revisions in the record. Do not assume that the amount of editing alone changes how generated material should be treated under the current platform guidance.
Can I keep code only inside the layout file?
An editable source listing is usually more useful for review and testing. Keep it connected to the layout representation so corrections reach both versions and the final book can be compared with the tested code.
What must I check, disclose, and verify myself when AI helped produce the book?
Review facts, rights, and source material yourself, record which parts were AI-assisted or AI-generated so you can answer Amazon’s disclosure question accurately, and treat every automated check as a starting point rather than a verdict.
See what the compliance checks cover