A2UI for Elixir/Phoenix/LiveView
Renders AI agent JSONL as LiveView components, but the protocol is still v0.9.
LLM Evaluation for Phoenix Apps
Phoenix LiveView embedding beats switching to LangSmith for Elixir teams.
Elixir/Phoenix developers building LLM-powered applications
LangSmith · Arize Phoenix · Helicone
Renders AI agent JSONL as LiveView components, but the protocol is still v0.9.
Runtime clicks for you instead of waiting for user input like shepherd.js.
Quoracle actually does something interesting: it queries a pool of models and only executes actions they agree on, while letting agents spawn children and persist full state to Postgres — all visible in a LiveView dashboard. The per-model conversation history, recursive hierarchy, and explicit consensus pipeline are clever touches; it’s clearly aimed at experimentation rather than drop-in production use (the README even flags security and deployment caveats).
Quoracle forces you to stop trusting one model and instead runs every decision through an explicit consensus pipeline, with per-model conversation history persisted to Postgres and a LiveView dashboard for realtime inspection. Agents can spawn children recursively and communicate via messages, which makes it a neat sandbox for studying emergent behaviors or building robust multi-model workflows — heavy, opinionated, and clearly aimed at folks who want to experiment rather than ship a lightweight chatbot.
Claude Opus spent $59.55 versus MiMo-Flash at $0.39 for identical bracket predictions.
LLM evaluation guide eats its own dogfood with eval-based site design.