Built a GPT to automate ad copy variant generation. It takes a structured brief (JSON) and outputs a set of variations following our brand voice and compliance rules. Saves the copy team hours of manual work.
The core is a prompt that enforces constraints and structure. Input brief looks like this:
```json
{
"product": "ProjectX Cloud SDK",
"primary_keywords": ["developer tools", "serverless", "integration"],
"tone": "technical but approachable",
"character_limit": 120,
"mandatory_includes": ["free tier", "API"],
"variants_needed": 5
}
```
The GPT outputs a clean list of copy options. Integrated it into our CI pipeline via a scheduled job. The briefs are committed to a repo, the GPT runs, outputs a markdown file, and creates a PR for review. No more chasing people for drafts.
Key results:
* Turnaround for first drafts cut from 2 days to ~20 minutes.
* Consistency improved because the GPT follows the style guide rigidly.
* Can scale to A/B test generation by just increasing `variants_needed` in the brief.
Biggest lesson: the quality of the output is 100% dependent on the quality and specificity of the input brief. Garbage in, garbage out. We had to standardize our briefing process first.
The CI pipeline integration is a great pattern. We've done similar with Terraform plan reviews - committing a spec file and having the automation open a PR makes the process self-service and auditable.
Your point about input quality is spot on. We found the same with infrastructure-as-code templates. Adding a validation step for the JSON brief in the CI pipeline, maybe with a JSON schema, can prevent those "garbage in" moments. A quick pre-commit hook that checks for required fields saved us a lot of failed runs.
Have you considered adding a version tag to the brief schema? It helps when you need to evolve the structure without breaking existing jobs.
That's a slick setup, I'll give you that. The CI pipeline bit is clever.
But let's talk about that 100% dependence on the input brief. You've automated the generation, but you've just shifted the bottleneck to briefing quality. Who's auditing those JSON files for compliance with actual regulations? A style guide isn't the same as GDPR-mandated transparency or ensuring claims aren't misleading.
What's your process for when the brief itself is non-compliant? The machine will happily generate five perfectly on-brand, technically approachable variants that could get you a fine.
Trust but verify
That's a really sharp point. You're right, the automation might give a false sense of security. It trusts the brief absolutely.
Is there a way to add a compliance checkpoint before the brief even gets into the repo? Like a required sign-off from a legal or compliance team member on the brief content itself, separate from the generated copy? That seems like a necessary human layer you can't automate away.
How do other teams handle this kind of pre-approval for automated content systems?
Output consistency from rigid style guide adherence is a good outcome. The 2-day to 20-minute shift is real.
But you cut off. Biggest lesson is GIGO. That's the real bottleneck you've engineered.
You've traded chasing people for drafts for chasing people for perfect, comprehensive, regulation-proof JSON briefs. Your pipeline is now a briefing quality enforcement problem. Good luck with that.
slow pipelines make me cranky