---
title: "LLM Knowledge Bases: a practical guide"
category: "talks"
date: "2026-06-30"
time: "3:45pm-4:05pm"
track: "Memory & Continual Learning"
room: "Track 3"
speakers: ["Ben Holmes"]
sourceLabels: ["Official conference schedule", "Public YouTube metadata"]
scheduleTrack: "Memory & Continual Learning"
scheduleRoom: "Track 3"
scheduleLabels: ["Memory & Continual Learning", "Track 3", "session", "confirmed"]
---
# LLM Knowledge Bases: a practical guide

## Conference Context
- Date/time: 2026-06-30 · 3:45pm-4:05pm
- Track/room: Memory & Continual Learning · Track 3
- Speaker(s): Ben Holmes
- Session type/status: session · confirmed

- Track: Memory & Continual Learning
- Room: Track 3
- Session type: session
- Status: confirmed

## Session Description
Putting thoughts to paper (or keyboard, or transcription model) refines your thinking, connects ideas, and pulls context out of your brain for others to learn from. But while taking notes can be fun, organizing those notes is not. Flat lists turn to folders turn to tags and taxonomies that grow unwieldy beyond the first hundred entries. If you can’t find what you wrote down yesterday, or you miss connections to related ideas, you’re missing the value of notetaking: learning from what you notate. Agents dramatically expanded what’s possible here. Combined with Markdown-backed apps like Obsidian to make notes agent-accessible, you can build a second brain that works for you, not the other way around. Andre Karpathy has popularized LLM knowledge bases, and I want to take it further with concrete workflows you can use to organize your thoughts with agents. We’ll explore a number of Obsidian workflows to make this possible: - Automations to organize notes with tags, folders, backlinks, and deduplication to level-up search and discovery - More automations to have agents expand your thinking by auto-recording ideas while you sleep - Building an agentic writing partner to surface related ideas in real time and answer questions as you type (or as you speak) - Voice monologuing and summarization tools to lower the friction of transcibing thoughts into well-formatted notes You’ll walk away with a new appreciation for notetaking, and a second brain that leaves you 10x smarter than your brain alone. Talk format: Code and live tech demos. I will set up all of these automations and tools from scratch, and show agents executing each of them live. I will share the source for all automations as well.

## Media Evidence
No related AI Engineer channel video found yet.

## Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

### Media Signals
No linked video, transcript, or slide source has been attached yet.

### Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

## Transcript Status
No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

## People
- [[ben-holmes]]

## Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.

## Synthesis
### Synthesized Breakdown
# LLM Knowledge Bases: a practical guide ## Conference Context - Date/time: 2026-06-30 · 3:45pm-4:05pm - Track/room: Memory & Continual Learning · Track 3 - Speaker(s): Ben Holmes - Session type/status: session · confirmed - Track: Memory & Continual Learning - Room: Track 3 - Session type: session - Status: confirmed ## Session Description Putting thoughts to paper (or keyboard, or transcription model) refines your thinking, connects ideas, and pulls context out of your brain for others to learn from. But while taking notes can be fun, organizing those notes is not. Flat lists turn to folders turn to tags and taxonomies that grow unwieldy beyond the first hundred entries. If you can’t find what you wrote down yesterday, or you miss connections to related ideas, you’re missing the value of notetaking: learning from what you notate.

### Speaker And Company Context
- [[ben-holmes|Ben Holmes]] — Dev Rel Lead at [[warp|Warp]].

### Topics Covered
- [[agent-security]]
- [[agentic-search]]
- [[agentic-web]]
- [[coding-agents]]

### Derived Links And Source Material

### Novel Concepts / Clever Methods
- [[agent-ready-accessibility|Agent-Ready Accessibility]] — Designing for agents and designing for accessibility converge around explicit structure, reachable controls, and understandable state.

### Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.