Generative AI Stack and Amazon Q Developer
Introduction
- The presentation covers the Generative AI stack of AWS services, focusing on Amazon Q Developer.
- Amazon Q Developer is designed to help accelerate the entire software development lifecycle.
The Generative AI Stack
- At the bottom, there are EC2 instances with GPU and other accelerator options to build and train generative AI models.
- Bedrock was launched to make it easy to host models and provide configuration and customization capabilities.
- Amazon Q, launched at re:Invent last year, comes in two flavors:
- Q Business: Helps with building chatbots and conversational applications.
- Q Developer: Focuses on improving the developer experience across the software development lifecycle.
Amazon Q Developer
- Amazon Q Developer is integrated into various AWS experiences, such as the console, documentation, mobile apps, collaboration tools, and IDEs.
- It is trained on publicly available code examples, but the challenge is that it doesn't know about the user's internal SDKs, APIs, and custom solutions.
- Customization allows users to train Q Developer on their private code base, so it can learn about the unique aspects of their organization and make relevant suggestions.
Customization Preparation
- To prepare for customization, users need to have at least 10 files and 2 MB of data in Java, JavaScript, Python, or TypeScript.
- Best practices include using verbose method names, adding detailed comments, and providing examples of the intended usage of the code.
- The more code examples provided (around 100 MB or more), the better the results, as long as the code is unique and not duplicated.
Customization Creation and Monitoring
- Users can connect Q Developer to their existing code repositories, such as GitHub, Bitbucket, or GitLab, or directly ingest code from Amazon S3.
- The customization process takes around an hour and results in a score, which may initially be low but can be improved with more examples.
- It's important to grant access to the customization selectively, based on the specific needs of different teams or users.
- Monitoring the performance of the customization through the Q Developer console and CloudWatch can help understand its effectiveness and identify areas for improvement.
Real-World Examples
- Internal teams at Amazon, such as Prime Video, have seen a 30% increase in acceptance rates with the customized Q Developer.
- External customers, like National Australia Bank, have reported a 60% increase in productivity over using Q Developer without customization.
Overall, the presentation highlights the benefits of using Amazon Q Developer, especially with customization, to accelerate the software development lifecycle and improve developer productivity.