EXA

LLM Knowledge Bases: a practical guide — Ben Holmes, Warp

Aug 12, 2026 · 21:17

Ben Holmes, Developer Relations Lead at Warp, demonstrates how to turn a disorganized folder of voice-dictated notes into a browsable, interconnected knowledge base using LLM agents. He argues that voice dictation at 200 words per minute is the fastest capture method, recommending local tools like Handy and Voice Ink to avoid subscriptions. Holmes explains his 'enrich note' skill, which timestamps files, assigns tags from a fixed list to prevent Claude from inventing new ones, researches sources via web search, and adds backlinks through key term search. He then shows how to generate wikis from a Karpathy gist, grouping people, concepts, and organizations, and automates the entire pipeline on a daily schedule using Obsidian's headless CLI in a cloud sandbox via Oz.dev. Finally, he demonstrates asking an agent to build an HTML and Tailwind graph view of all notes, revealing clusters of interests and gaps in thinking.

Why the Best AI Agents Are Built Without Frameworks (Primitives over Frameworks) — Ahmad Awais, CHAI

Jun 3, 2025 · 27:06

Ahmad Awais, founder of LangBase/CHAI, argues that production AI agents like Perplexity, Cursor, v0, Lovable, Bolt, and CHAI itself should be built using AI primitives rather than frameworks. He demonstrates live coding a 'Chat with PDF' agent using LangBase primitives (memory, parser, chunker, threads). Awais presents eight agent architectures—augmented LLM, prompt chaining, agent router, parallel agents, orchestrator-worker, evaluator-optimizer, tool-calling, and memory-based—all built with plain code and no framework. He claims frameworks are bloated and slow, while primitives offer flexibility and automatic scaling (e.g., memory storing terabytes). Awais shows how to compose multiple LLMs (Gemini, DeepSeek Llama, Claude) in a router agent, and notes that his team has built agents for OCR, image analysis, and deep research using primitives and external tools like Mistral OCR.