A Ruby gem that integrates AI-powered judgment into code by adding System One (S1) model capabilities as native features. The gem enables typed probabilistic queries about data without generation, allowing code to ask questions and make decisions based on calibrated probability responses.
A programming language design discussion comparing Rust's minimal parameter features with Ruby's flexible argument handling, examining named parameters, defaults, and keyword arguments through examples like Rails's redirect_to function and FastAPI decorators.
RubyLLM 2.0 expands the framework with new provider coverage (now seventeen total), AI operations including tool approvals and citations, conversation controls for agentic workflows, and Rails integration. The release adds support for video, speech, OCR, reranking, batches, and usage tracking while maintaining consistent APIs across providers.
RubyLLM 2.0 expands support across multiple AI providers and introduces new features including video, speech, OCR, batches, and Rails integration. The framework adds human approval controls for tools, citations for document and web references, and separates providers from protocols for consistent APIs across different services.
RubyLLM 2.0 expands the framework with support for new providers (Cohere, Deepgram, ElevenLabs, Ollama Cloud), AI operations (video, speech, OCR, reranking, batches), and conversation controls including tool approvals, citations, and agentic workflows. The update adds consistent Ruby APIs across seventeen providers while maintaining streaming and usage tracking throughout.
A diagnostic guide for auditing Ruby on Rails applications to assess architectural clarity and suitability for AI coding agents. The prompt instructs auditors to inventory the app's structure, gems, and design patterns across three passes—without modifying code—to identify conflicts between stated and implicit architectural decisions, missing documentation, and genuine security risks versus stylistic preferences.