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GenAI Assistant Cover

Power Your Developer Experience with AI: Introducing Fauna’s AI Assistant

Matt Ryan|Dec 8th, 2023|

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CompanyFeatures
Today we're excited to introduce our Fauna AI Assistant, designed to help developers more easily find and consume relevant Fauna Query Language (FQL) resources that span documentation, driver and API references, code samples, and blogs. By providing a more targeted content generation experience through a natural language question and answer interface, developers can save time throughout their product development phases (from beginner to more advanced topics).
This launch marks the beginning of a significant investment in AI at Fauna to make developers more productive and in support of a rapidly evolving set of database capabilities and customer use cases.

Our First Step in AI-Driven DX

As an initial step in streamlining Fauna’s developer experience with AI, we're expanding our documentation site to include an experimental, generative AI question and answer agent to augment content retrieval. Answers are derived from topics that span our docs site, code repositories, technical references, tutorials, blogs, and whitepapers.
Feature access also requires an existing Fauna account.
We envision this AI Assistant as an evolving agent whose primary job is to help developers more rapidly learn about Fauna, quickly navigate our documentation and resources, and to serve as a guide for advanced concepts and power users.
This feature is currently labeled as experimental as it may not always provide the most relevant content and can produce inaccurate results (we encourage all customers to always validate results when in doubt). We also recommend that developers NOT include Personally Identifiable Information (PII) or sensitive data in any of their questions (although we don’t share any data with OpenAI or other providers).
Here are a few example questions Fauna AI can help you answer:
  • What is Fauna?
  • How does Fauna replicate data across regions?
  • What is the FQL equivalent of the SQL statement ‘SELECT * FROM Products’?
  • How do I iterate over Documents in a Collection?
  • How do I create a collection named 'Galaxies' and add documents named 'Andromeda' and 'Milky_Way' where both documents have a field name ‘type’ with the value of ‘spiral’?
  • How do I create a UDF (user-defined function) that calculates the circumference of a circle and call it?

What’s Next

While we’re starting with a docs and content-based question and answer AI Assistant, we envision this first version as a key building block and plan to continue expanding those capabilities to support a variety of emerging developer workflows.
We’re actively evaluating our product roadmap and priorities to incorporate these potential feature areas (where each is focused on developer productivity):
  • FQL syntax and type checks
  • FQL translations (from other languages into FQL)
  • Contextual chat (multi-question)
  • Modifying data within a local schema or database
  • Schema / field-level descriptions and queries:
  • “What is the largest value in the Temperature field?”
  • “Which fields exist on documents in the Inventory collection?”
  • Integrations with 3rd party tools and platforms (TBA)
Building AI capabilities into Fauna’s developer experience is a key investment area for us, and we’re excited to have you along for the ride!
Stay connected with us on Fauna's blog for product updates and visit our forum to provide feedback or request new features.

If you enjoyed our blog, and want to work on systems and challenges related to globally distributed systems, serverless databases, GraphQL, and Jamstack, Fauna is hiring!

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