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
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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...
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...
Cantrip recognizes that what we call artificial intelligence now is at all levels a loop of language: predict next token, next message, next command, next sub-agent, in a feedback loop with your own effects. The static intelligence of language come alive www.deepfates.com/recursive-la...
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
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When you write a script that can write other scripts and see the errors from running its scripts and course-correct, you have a script of a higher order. A cantrip. You can even have a cantrip that writes other cantrips. This is the RLM, or the Familiar www.deepfates.com/the-familiar/