Q Developer keeps suggesting deprecated AWS SDK methods. How to fix?

Hi everyone. I’ve been integrating Amazon Q Developer into our team’s workflow for a few sprints now, primarily for accelerating IaC and SDK code generation. Overall, it’s been a positive boost to velocity. However, we’ve hit a consistent and concerning pattern: **Q Developer frequently suggests the use of deprecated AWS SDK methods.**

This creates a subtle but significant reliability risk. New engineers, or those less familiar with a particular service, might accept these suggestions without question, baking technical debt and potential future breakages directly into our codebase. For example, when working with Python (`boto3`) for Lambda, it recently suggested using the deprecated `get_function` configuration parameter pattern instead of the current `get_function_configuration` method. In Node.js land, we’ve seen suggestions for older `AWS.Request` patterns that are no longer considered best practice.

From an SRE perspective, this is an observability and operational maturity issue. Code using deprecated paths might work today but could fail unpredictably during future SDK upgrades, directly impacting our error budgets. It also makes our runbooks and automation less durable.

I’m curious how others are mitigating this. My current methodical approach has been:

* **Implementing strict code review gates** that specifically flag AWS SDK usage for version and method checks.
* **Adding a pre-commit hook** that uses the SDK’s own metadata (where possible) to scan for known deprecated methods.
* **Providing explicit feedback to Q** when it occurs, though the learning loop seems slow.

Has anyone found a more systemic fix or configuration within Q Developer itself? Perhaps a way to pin or guide it towards specific SDK versions? I’m also considering if this is something a custom context file could help with, by including our team’s SDK best practices.

Here’s a small example of the type of suggestion we’re seeing and our correction:

```python
# Q Suggestion (Deprecated)
import boto3
client = boto3.client('lambda')
response = client.get_function(FunctionName='my-function')
configuration = response['Configuration'] # Old pattern

# Our Correction
import boto3
client = boto3.client('lambda')
response = client.get_function_configuration(FunctionName='my-function') # Current method
configuration = response
```

Any shared experiences or workflows would be really helpful. Let’s build a more resilient automation layer together.