tag > Ideas
-
Recursive Self-Improving Agent World-Models
An Agent World-Model cartridge is epistemically typed intelligence substrate for AI agents. Its primary function is belief-state initialization - supplying the domain, causal structure, confidence architecture, reasoning rules & boundaries of legitimate inference. World model cartridge contain not only knowledge, like most prompts, but governance: it tells the model how strongly to believe claims, how not to reason, what distinctions to preserve.
It controls:
- Attention — what the agent notices.
- Ontology — what kinds of things the agent believes exist.
- Inference — which causal moves are legitimate.
- Uncertainty — what the agent may claim confidently.
- Retrieval — where it looks for supporting detail.
- Narrative resistance — which seductive stories it must reject.
- Simulation — how it predicts the system will behave.
This is the state representation and epistemic constitution around which a recursive self-improving world model system can be built. The crucial phrase is external evidence. If the LLM recursively rewrites its own synthesis without new evidence, it does not improve. The most powerful form: prediction and reconciliation. Eventually the system can recursively improve not just its beliefs, but its method of belief formation.
-
Marshall McLuhan noted that the content of any new medium is always an older medium—like early cinema merely filming theater. Today, AI cinema is trapped in that exact same loop, emulating traditional filmmaking structures before it inevitably discovers its own native form.
-
"Life is a journey filled with lessons, hardships, heartaches, joys, celebrations & special moments that will ultimately lead us to our purpose in life"
-
We’re searching here, trying to get away from the cut and dried handling of things all the way through—everything—and the only way to do it is to leave things open until we have completely explored every bit of it.” – Walt Disney
-
What does the square root of minus 1 and fairies have in common?
-
Human Work Is Mostly Bullshit. Agents Eat it for Breakfast?
What most office work actually is (and why 80% of agent builders target the wrong market)
Human work today is mostly bullshit. 20% of people build things. 80% of people coordinate the movement of information so the 20% can build. Nobody knows what office workers actually do. Most people can't articulate their own job in concrete steps. There is no magic. No deep craft. Most office jobs are just low-level information logistics and break down to 5 primitive actions: Move data from A to B > Ask for something and wait > Compare two things > Summarize > Get permission.
AI Agents eat logistics for breakfast. Vertical AI Agent have gotten very good and are starting to replace entire departments in specific industries. Not a task. Not a workflow. A department. And yet most agent builders choose building agents for the 20% layer and fail - because those domains are specialized, regulated, and high-stakes. The gold is in the 80%. The logistics layer. Boring but huge. Millions of people doing mind-numbing work they want automated.
Agent builder love selling magical solution - but companies buy process automation with clear ROI, not "agentic job replacement" — that sounds scary and gets legal pushback. The gold is in friction, not efficiency. Efficiency is a spreadsheet win. Friction is a human win. When you automate a process, people don't just do it faster. They change what they do entirely. You're not selling efficiency. You're selling role evolution. Companies won't admit that.
Modern work is boring but It keeps the lights on and the "different economy" isn't coming any time soon. So: build for the 20% (noble, hard, most fail) or build for the 80% (boring, huge, prints money). Most pick the first and go nowhere. And so the entire economy is bullshit jobs. You categorically cannot automate them — even with AGI. But it will still happen.
