When a team says “the AI copy is generic,” the missing piece is often a contract, not a better model. Define inputs, states, and review gates first; then evaluate the generated language like any other UI output.
Model the workflow at the interface level
An image-led ad writer can be described with four states: input, extracted, drafted, and approved. The public Nextify pages show an image upload, editable information, generation, preview, and download path. That is enough to design test cases without guessing the private stack.
type CopyJob = { image: 'missing'|'ready'; facts: 'empty'|'reviewed'; output: 'none'|'draft'|'approved' };
Separate copy contracts from slogan contracts
The AI Copy Generator is positioned for product descriptions, static-ad text, and UGC-style scripts. Test it for completeness, channel length, and factual alignment. A slogan has a different contract: memorability, one dominant benefit, and fit beside a visual. The AI Slogan Maker describes extracting product features and likely audiences from a photo before creating slogans and ad directions.
Write reusable test cases
| Case | Input | Expected review question |
|---|---|---|
| Clear product photo | Simple background | Are category and visible features correct? |
| Lifestyle photo | Product partly occluded | Which claims require manual confirmation? |
| Multiple audiences | One image, two markets | Does the draft declare whose problem it solves? |
| Short placement | Social card | Can the promise survive truncation? |
Instrument what you can observe
Do not invent latency or quality benchmarks. Instead, capture observable events: upload accepted, fields edited, draft generated, preview opened, download requested. A lightweight Playwright outline can remain illustrative:
// Illustrative selectors: confirm them in the current editor before automation.
await page.getByRole('button', {name:/generate/i}).click();
await expect(page.getByText(/preview/i)).toBeVisible();
Add a human approval gate
The highest-value test is semantic: does every claim appear in the supplied facts or visual? Reviewers should also check prohibited wording, localization, and whether the slogan still works without the logo. The tool can produce options; the release decision belongs to the team.
Make failures diagnosable
When a draft misses the mark, log the failure category instead of simply regenerating: wrong product fact, wrong audience, wrong channel length, or wrong tone. Each category suggests a different fix. A wrong fact calls for better input or manual correction; a wrong audience calls for a clearer brief; a length failure belongs in a placement rule; and a tone failure belongs in examples or editing guidance. This taxonomy keeps teams from treating every issue as a model-quality problem.
What this design cannot tell you
Public page behavior does not reveal model choice, data retention, or production reliability. Treat those as questions for documentation and security review. A clear interface contract keeps the workflow useful even while those answers are pending.
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