Discourse — the theory behind the framework

dvergr calls its core abstraction a discourse rather than a "message bus" or an "agent graph" on purpose: the design takes the linguistic case seriously. Participants — humans, LLMs, scripts — are speakers exchanging utterances in a shared room, and the framework's primitives line up with ideas from the philosophy and the Bayesian modelling of language.

This page is short, optional theoretical context. The working reference is programming-model.md; this is the why it's shaped this way.

Messages as speech acts

A message carries a :type, and that :type is its illocutionary force — in the sense of speech-act theory (Austin, Searle): what the utterance does, not just what it says. :directive/raise-budget directs; :escalation/budget escalates; :probe/memory asks. Participants then subscribe by the kinds of speech act they answer (capability routing), so a room is organised around who responds to what kind of move — not by hardcoded sender→receiver wiring. Adding a new kind of interaction is adding a new tag, not rewiring the graph.

Theory of mind: RSA, made reactive

The deepest hook is theory of mind. In the Rational Speech Acts model (Goodman & Frank), a speaker chooses an utterance by predicting how a listener will update their beliefs — pragmatics as recursive Bayesian reasoning. dvergr makes this operational rather than a line in a system prompt, because the runtime forks cheaply:

(defn simulate-reply
  "Fork the room, deliver a hypothetical to `other`, await their reply in the
   fork, then discard it. Returns the imagined reply; the real room is untouched."
  [room other hypothetical]
  (spin
    (let [fork     (fork-room room)
          imagined (await (ask (get-participant fork other) hypothetical))]
      (discard fork)
      imagined)))

A speaker can run simulate-reply over a few candidate utterances and keep the one that best moves the listener — RSA as implementation, not as prompt. The same primitive underlies "imagine the conversation before speaking" (imagine-conversation), moderator previews, and debate look-ahead. The align-on combinator — iteratively refining a statement toward common ground — is named after Tessler et al.'s work on AI-assisted deliberation.

The inference reading (optional)

Pushed further, the substrate has a probabilistic reading: a participant is a particle in a Sequential Monte Carlo process, a message is an observation, a fork is "try another hypothesis," and an accepted artifact is a posterior that becomes the next prior — programming as and for inference. dvergr does not require this mode (most workflows run once, normally, with no resampling); spindel's inference suite simply makes population SMC over forked rooms available when a workflow wants it. The mathematical frame is Feynman–Kac (Del Moral).

Lineage

• Rational Speech Acts (RSA) — Goodman, Frank, Tessler et al., http://www.problang.org. Pragmatic reasoning as recursive Bayesian inference over utterances; dvergr's theory-of-mind hook follows it.
• Cohn-Gordon & Bärenz — linguistic-convention convergence + reactive probabilistic inference; bridges RSA-style pragmatics with reactive multi-agent FRP (Rhine FRP, choreographic programming) — the bridge dvergr's substrate makes concrete.
• rhine-bayes — Bärenz et al. (Tweag, 2023), online reactive Bayesian inference (SMC on clock-safe FRP streams); the conceptual ancestor of spindel's inference package.
• AI mediation / common ground — Tessler et al., Science 2024; the align-on combinator is named for it.
• Speech-act theory — Austin, How to Do Things with Words; Searle — the reading of :type as illocutionary force.
• Feynman–Kac — Del Moral (2004); the math for the optional inference reading.

The full internal design (the four-layer SMC ladder, the Feynman–Kac account, LLaMPPL/ToT/RAP comparisons) is kept out of the public docs deliberately — this is the distilled version.