Hypermode

The Knowledge Graph Mullet: Trimming GraphRAG Complexity - William Lyon

Jun 3, 2025 · 32:52

William Lyon presents the 'Knowledge Graph Mullet' concept, combining property graph interfaces with RDF triple storage in Dgraph to optimize GraphRAG systems and AI agent development. Dgraph uses a property graph model for data modeling and DQL (inspired by GraphQL) for queries, while leveraging RDF triples for scalable storage and data interchange. Features include vector similarity search (e.g., finding articles about 'money laundering'), geospatial indexes, and a Model Context Protocol (MCP) server that exposes tools to models like Claude Desktop for auto-generating schema and querying. Lyon demonstrates building a news knowledge graph from the New York Times, chunking articles into nodes, and using graph traversal to surface related topics after vector search. He also showcases Hypermode agents, created from a prompt with access to GitHub and Notion via MCP servers, which can analyze repos like hyper-news and generate social media posts with code snippets, then save them to a Notion workspace. Hypermode agents are now in early access.

Git push get an AI API: Ryan Fox-Tyler

Aug 23, 2024 · 45:01

Ryan Fox-Tyler and Matt Johnson Pint from Hypermode present a hands-on workshop demonstrating how to build and iteratively improve AI features using their platform, focusing on a GitHub issue triage app. They first illustrate the process with a multiplayer game (Hypercategories) that uses AI for classification and scoring. Then they build a trend summary function using OpenAI GPT-4 to summarize repository issues, and a classify issue function with a Hugging Face DistilBERT model for labeling issues as bug, feature, or question. Finally, they add natural language search for similar issues by creating an embeddings model (MiniLM) and a Hypermode collection, enabling vector search without external databases. The workshop emphasizes incremental iteration, mixing AI models with traditional code, and using Hypermode's automatic GraphQL generation and observability to speed development.

Hypermode Launch: Kevin Van Gundy

Aug 23, 2024 · 5:03

Kevin Van Gundy, founder of Hypermode, argues that iteration velocity is the compound interest of software and key to succeeding with AI, and presents Hypermode as a runtime that makes AI approachable by integrating models and data into AI functions with minimal friction. Drawing from his experience at Vercel, he explains how rapid iteration helped them win against competitors, and applies the same philosophy to AI development. Hypermode removes common pain points: it offers one-request RAG with in-memory embedding and search, model comparison and fine-tuning export, and strong defaults that work with existing stacks. The platform de-risks getting it wrong by making model switching and prompt changes frictionless. Kevin invites listeners to a workshop to build a demo and offers $1000 in Hypermode credits to get started.