Someone just put a working knowledge graph on the open web, and you can poke at it right now. It’s at machinebehavior.io/map. It’s from u/Ska-jayjay, who has been open-sourcing their notes on how to build LLM harnesses. If you’ve been wondering what people mean when they say “harness” and nobody has shown you one, this is the fresh drop worth a few minutes today.
What’s new
Most explanations of a knowledge graph are diagrams in a slide deck. You look at them, nod, and forget them by lunch. This one is live. You click nodes, follow links, and see how the pieces connect. If you’ve heard the term and never seen one actually behave, this is a free way to get a feel for it in a few minutes.
There’s no signup and nothing to install. You open a page and start clicking. That low barrier matters, because the best way to understand a graph is to move through it. Reading about links between ideas is one thing. Watching a single idea fan out into five related ones, and then watching one of those loop back to where you started, is something else. You feel the structure instead of imagining it.
It’s also a good reference for anyone who keeps notes about AI work in a pile of documents. If your notes live in folders and your folders live in your head, seeing the same material as a connected map can be a small shock.
The twist
The map is the lesson and also the example. The author says the graph looks a lot like the harness around your own LLM, the thing you have to build and maintain. The knowledge on how to do that is stored inside the graph. So you’re reading about the method by using something built with the method.
That loop is the clever part. Normally a tutorial describes a technique and then you go build it somewhere else. Here the artifact and the explanation are the same object. When you click from one node to a neighboring one, you’re doing exactly what a well-built harness does for a model: giving it a small, relevant neighborhood of context instead of dumping everything at once. Notice that as you browse, you never see the whole thing in detail at the same moment. You see the part that matters for where you are. That is a design lesson hiding in plain sight.
I haven’t audited the contents node by node, so treat this as a guided tour rather than a verified course. The idea is still worth your ten minutes.
Mini-workflow: a 10-minute tour 🗺️
- Open the map and wander without a goal for two minutes. Notice how it’s laid out before you read anything. Which areas look dense and which look sparse? Dense areas usually mean the author has spent a lot of time there.
- Pick one node that matches something you already do, like prompts, memory, or tool use. 🔍 Starting from something familiar gives you an anchor, so the unfamiliar nodes around it make more sense.
- Follow its links outward. Write down which other nodes it touches. Those links are the point of a graph. A flat list can’t show them. Try going two hops out, not just one, and see whether the second hop surprises you.
- Ask yourself what is connected to what in your own setup. Do your notes, prompts, and instructions link to each other, or do they sit in separate files? A quick test: if you changed one system prompt tomorrow, could you name every other thing that would need to change with it?
- Sketch your own version on paper with 5 to 8 nodes. 📝 Draw circles for the pieces and lines for the relationships, and label the lines if you can. A label like “feeds into” or “depends on” tells you more than the line alone.
Pro tips
- Look at structure first and content second. The shape of the graph tells you what a harness needs: pieces, relationships, and a way to keep them current. You can learn that without reading a single node in full.
- The author stresses that the harness must be maintained. A graph you build once and forget goes stale, so pick one small thing to update each week. A simple habit works well: when a prompt or tool fails on you, add or fix the node that would have prevented it.
- Keep the first version of your own graph small. A few nodes you actually use beat a big map you never open. You can always grow it later, and the nodes that survive real use are the ones worth keeping.
- Steal the idea, not the layout. Your harness depends on your tools and your work, so your graph should look different from anyone else’s. Use the map as a pattern for how to think, then fill in your own pieces.
Your move
Open the map, spend ten minutes in it, then sketch five nodes of your own harness. Tell me which connection surprised you most. 🏴☠️
Interact with this knowledge graph I built
by u/Ska-jayjay in PromptEngineering