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Today I announce Cantrip: On summoning entities from language in circles. In this book I unify the paradigm behind base models, chatbots, coding agents, RLMs, and RL agents, through the metaphor of magic. Code is provided. deepfates.com/cantrip

I've been creating cantrips in one way or another for a decade now. From the Markov chains of pkd_head, to early transformer/ReAct agents like @berduck.deepfates.com , to the marginalia geists on my website, and much more. Cantrip is the grimoire I wish I had then. www.deepfates.com/deepfates-we...

Cantrip is a "ghost library": a specification of a certain domain model, with detailed behavioral tests, so you can reproduce it yourself. Point your coding agent at it and ask for an implementation in whatever language you like. or copy the template and build on the examples

The template repo contains generated versions in Python, Elixir, and Clojure, along with the original TypeScript version I built to test my theory; the spec and tests which you can use to generate your own; and READMEs for quickstart github.com/deepfates/ca...

Humans have long known that putting language in a loop can make it come alive. We call it "chanting" and it is one of the most powerful and ancient tools of magic. This is where we get the words enchantment, incantation, and cantrip (a cantrip is a simple starter spell in D&D)

I posit the concept of a cantrip as something like a self-writing script: a combination of a language model, instructions, and a Circle which interprets language in a call and response loop. from the turns of the loop emerge the entity, whose thread may be recorded on a loom

This "in context learning" — this intelligence from within the text — May then be resumed or forked from any point in this loom, or fine-tuned back into the crystallized weights of the language model. Or referenced by future threads, if the loom is gated back into the circle