s_brady
Show HN: Springdrift – A persistent runtime for long-lived LLM agents
https://github.com/seamus-brady/springdrift
I wanted to share something that I have been working on since about 2019, in one form or another. Springdrift is a persistent, auditable runtime for long-lived agents written in Gleam on the BEAM. It is my attempt at filling in some of the gaps in agent development. It is designed to do all the things an agent like Openclaw can do (and more eventually), but it can diagnose its own errors and...
Springdrift: An Auditable Persistent Runtime for LLM Agents
TallMountain – Stoic Virtue Ethics for an LLM Agent
I make no great claims for the system, it has major issues being prompt based. It is a prototype to explore the feasibility of the idea of giving a chatbot arete, a code of conduct. There are few tests, no evals so all the usual caveats! An intellectual exercise in possibilities not currently being explored anywhere else. Does it work? Hmm, almost :)
It extracts normative propositions from incoming user requests then compares then to it's own internal ethical normative propositions using the Normative Calculus. The system also uses the Decision Paradigm algorithm from Lee Roy Beach [3] to make a forecast on whether to take up the user's task or not.
[1] https://link.springer.com/article/10.1023/A:1013805017161 [2] https://www.jstor.org/stable/j.ctt1pd2k82 [3] https://books.google.ie/books/about/The_Psychology_of_Narrat...
Awesome Eiffel – a curated list of Eiffel libraries, resources and tools
Eiffel – Concurrency patterns in SCOOP [pdf]
However this does not necessarily have to be related to causality, and counterfactual statements about a causal model. The math behind counterfactuals and causality is actually well understood now (see any of Pearl's books). It does not actually require that a system be embodied, just that the system have some suitable (and correct) causal model of the world.
It would of course be amazing to have both in one system, but that is not required. An AI system that understood causality and language could be bootstrapped from causal models supplied by humans - or even other AIs :)
There is a way to pick and choose :)
The context menu in Mousemacs is a couple of dozen lines of Elisp and would be simple to rewrite. You can simply create your own context menus.