Vibe PRD is an AI agent designed for product teams to create complete product requirement documents in minutes. Users provide a prompt or basic project summary, and Vibe PRD generates detailed sections including an executive summary, objectives, KPIs, target user personas, user journey maps, use case scenarios, feature breakdowns with functional and non-functional requirements, development milestones, and acceptance criteria. Vibe PRD supports customization of document templates, versioning, and export to multiple formats such as Markdown and PDF. By automating repetitive tasks, Vibe PRD reduces documentation time, enhances collaboration, and ensures consistency across product initiatives.

OnLift is a platform that generates AI-ready documentation to streamline project development. It allows users to create Product Requirements Documents (PRD), Frontend and Backend Architecture, Implementation Guides, and Development Standards. The generated documents are engineered to work perfectly with AI coding tools such as ChatGPT, GitHub Copilot, and others, ensuring consistency and eliminating the time-consuming debugging process.

dbt-llm-agent leverages large language models to transform how data teams interact with dbt projects. It empowers users to explore and query their data models using plain English, auto-generate SQL based on high-level prompts, and retrieve model documentation instantly. The agent supports multiple LLM providers—OpenAI, Cohere, Vertex AI—and integrates seamlessly with dbt’s Python environment. It also offers AI-driven code reviews, suggesting optimizations for SQL transformations, and can generate model tests to validate data quality. By embedding an LLM as a virtual assistant within your dbt workflow, this tool reduces manual coding efforts, enhances documentation discoverability, and accelerates the development and maintenance of robust data pipelines.

Generate Project README using LangGraph is an AWS sample tool showcasing how to build AI-powered documentation generators with LangGraph, an innovative graph-based AI workflow framework. It traverses your project files, understands code structures, dependencies, and usage patterns, then automatically generates a clear, organized README in Markdown. By integrating LangGraph’s customizable nodes, developers define workflows that extract module descriptions, code examples, installation instructions, and contribution guidelines. The output supports multiple templates for different languages and frameworks. Users can extend the workflow with custom prompts, connectors, and template engines. This sample streamlines onboarding for new contributors, ensures consistent documentation across repositories, and can be integrated into CI/CD pipelines to auto-update READMEs on code changes.