So I've been testing Amazon Q Developer for a few weeks now, specifically for building integrations between a few niche platforms. My typical stack involves the CRM Copper, the marketing automation platform ConvertKit, and a custom Node.js middleware on AWS Lambda.
My initial hope was that Q could help me speed up writing the glue code—things like formatting webhook payloads, handling OAuth flows, or transforming data schemas. But I'm finding its suggestions are... painfully generic.
For example, I prompted it to generate a function to map a Copper `person` object to a ConvertKit `subscriber` field structure. The output was a basic JavaScript object mapping with generic keys. It completely missed:
* Copper's custom field structure which is nested under `custom_fields`.
* The specific handling for ConvertKit tags, which require an API call *after* subscriber creation.
* The idempotency logic I often need for webhook retries.
The generated code looked like this:
```javascript
function mapToConvertKit(person) {
return {
email: person.email,
first_name: person.firstName,
// ... other basic fields
};
}
```
It's not *wrong*, but it's not useful. It doesn't engage with the actual, messy API specifics.
This makes me wonder:
* Is Q primarily trained on open-source and major framework code, leaving niche SaaS APIs out in the cold?
* Are others using it successfully for integration work, or is it better suited for standard app dev inside common ecosystems like Spring or React?
I've had much better luck with it for writing standard AWS CDK constructs. But for the actual business logic that stitches tools together, I'm still relying on old code snippets and API docs. It feels like a missed opportunity.
Has anyone else tried pushing it beyond generic boilerplate? Maybe I need a different approach with my prompts?