​Speaker - Matthew Solt

​Matt is a Rubyist with 20 years of experience, the founder of RoboRuby, and the author of The Ruby AI Newsletter. The Ruby AI Newsletter covers the intersection of Ruby programming and artificial intelligence, covering AI techniques for Rails developers, open source libraries, and generative AI applications and developer tooling being built for Ruby. RoboRuby is a consultancy that provides comprehensive data and analytics on the Ruby ecosystem, job matching and placement for Rubyists, and informational resources like the newsletter. 

​Summary 

​In this presentation, we'll explore how to build generative artificial intelligence (AI) applications using RubyLLM, a comprehensive library that brings modern Large Language Model (LLM) capabilities to Ruby developers. RubyLLM is a Ruby gem for integrating LLMs in Ruby and Rails applications, providing a single programming interface to build AI chat, vision, audio, image, and document analysis software, with full support for vector embeddings, tool calling, and streaming responses.

​We'll start by building an interactive chatbot in minutes using RubyLLM's built-in generators, and progress to basic generative AI tasks including text and image generation, audio and video transcription, and structured data extraction. Moving on to intermediate topics, we'll explore tool calling - programmatic extensions that allow you to delegate tasks that LLMs cannot perform such as calls to application code, databases, and APIs. We'll also compare tool calling with the Model Context Protocol (MCP), an open-source standard for connecting AI applications to external systems. 

​We'll move on to advanced topics such as Retrieval Augmented Generation (RAG), allowing you to use custom or proprietary datasets, enabling LLMs to use knowledge outside of their training data to generate authoritative or domain-specific responses. 

​Finally we'll examine the tech stack needed to build production-ready AI systems and workflows. 

​* Prompting and Context Engineering

​* Cost Management and Model Selection

​* Evaluation and Monitoring

​* Multi-Agent Systems

​* Infrastructure and Deployment

​Takeaway

​The presentation aims to be beginner friendly but a some knowledge of Ruby and Large Language Models is recommended. By the end, you should have the tools, techniques, and knowledge necessary to bring your generative AI workflows to life! 

​Agenda

• ​​10:00 – 10:30 AM: Meet & Greet (networking + coffee)

• ​​10:30 – 11:30 AM: Talk + Q&A

• ​​11:30 – 1:00 PM: Hands-on Workshop

​Target Audience

• ​​Founders & Technical Leaders — exploring how AI can boost productivity and reduce technical risk

• ​​Engineers & Developers — curious about integrating AI into coding, testing, and automation workflows

• ​​Students & New Grads — looking to gain hands-on experience with modern tools and future-proof skills

​​👉 Seats are limited—reserve your spot now to be part of this interactive session!