After Andrej Karpathy outlined the idea of “LLM Knowledge Bases” on April 3, 2026, developers built Graphify in under 48 hours. Graphify turns any folder of code, docs, and images into an interlinked markdown wiki you can query without vector databases or complex setup. It persists across sessions, builds backlinks and concept maps, and cuts future query costs.

This article argues that using Markdown prompts and LLMs as a runtime interpreter for business rules is slow, expensive, unreliable, and insecure. It shows how mixing regular code, human approvals, and LLMs without a solid framework leads teams to overuse LLMs instead of writing proper code and handling state continuations.

The author uses a local LLM called pi that reads a global CAPABILITIES.md index in markdown, pointing to task-specific docs like SSHing into a studio Mac or driving a browser. Pi only loads detailed instructions when a task matches a capability, and new setups are documented and added to the index so agents grow more useful over time.

This browser extension strips away ads, navigation, scripts and other clutter to extract the main content of any page and convert it into clean Markdown. It uses Mozilla’s Readability library plus customizable options (images, links, metadata) and offers instant copy or download. It streamlines LLM workflows by providing structured, token-efficient input.

Three major AI agent platforms—Manus, OpenClaw, and Claude Code—store their memory in plain Markdown files instead of vector databases. The article breaks down how file-based context boosts token-cache economics, enables attention control, and layers optional semantic retrieval, plus when this approach starts to break down.

Karpathy proposes replacing on-the-fly retrieval with an LLM-maintained markdown wiki that ingests sources, compiles structured pages, and self-updates through ingest, query, and lint cycles. This approach builds a persistent, compounding knowledge base without vectors or re-retrieval, though it currently lacks enterprise controls.

This article compares two main options for setting up an AI agent: the user-friendly Claude and the customizable Hermes. It explains the differences between AI agents and chatbots, outlines the setup processes for each option, and emphasizes the importance of .md files for effective AI interaction.

Mermaid is a tool that converts natural language or Markdown into diagrams like flowcharts and ER diagrams. It integrates with existing workflows, allowing real-time collaboration and customization. Ideal for teams needing to visualize ideas quickly and effectively.

Markdown emerged in 2004 as a simple and intuitive way to format text for the web, developed by John Gruber to address the complexities of HTML. Its ease of use and effectiveness quickly led to widespread adoption across various platforms, fundamentally changing how content is created and shared online.