Guides

📄️ Guide for AI Newcomers

Large Language Models (LLMs) are powerful tools, representing a paradigm shift in how we build and use software. Machines now have the ability to reason and understand natural language as well as source code. We predict over the coming years, incumbents will either remake themselves, or be disrupted by AI-native products and platforms.

📄️ Rules of AI.JSX

AI.JSX uses the familiar JSX syntax, but it's not React.

📄️ Prompting in AI.JSX

Prerequisites

📄️ AI + UI

In traditional UI development, human engineers write deterministic code to handle every possible UI state. With "Just in Time" UI (JIT UI), human engineers produce building block components, then hand those to an AI to use in its response.

📄️ Observability

In this guide, we'll start with the Hello World example from the AI JSX template and iteratively add logging.

📄️ Performance

- Deployment Architectures - Discusses the various options (and the trade-offs) for how to build and deploy your AI.JSX powered applications.

📄️ Deployment Architectures

- Performance - Discusses trade-offs between performance and correctness. Presents five strategies for improving performance in your AI-powered apps.

📄️ DocsQA: Grounding Answers with a Source of Truth

Large Language Models (LLMs) are powerful tools for answering open domain questions, but they're prone to making things up ("hallucination") when their responses are unrestricted. In addition, publicly available LLMs are trained on public data and consequently won't have knowledge of your internal information (documents, data, documentation, etc.).

📄️ ESM

AI.JSX exports both CJS and ESM files. When you import or require ai-jsx, you'll get the file that matches the module system you're using. If you have a problem with this, please let us know by either dropping us a line in Discord or by opening an issue on GitHub.