LOADING
In this talk, I’ll guide you through the crossroads where Scala intersects with AI, some applications aimed at boosting developer productivity, others focused on integrating your code with LLMs.
Artificial Intelligence (AI) is a term increasingly applied to a wide range of things every day, becoming a buzzword, especially among skeptical users. AI may refer to chatbots like ChatGPT, command-line coding assistants, IDE features, frameworks for building Model Context Protocol (MCP) servers for connecting tools and language models, or virtually any project involving a Large Language Model (LLM). It can even extend to no-code AI automation platforms like n8n, an open-source tool that lets you connect services and build workflows visually: self-hostable and highly customizable. Does that sound confusing? If so, do not fret, you are not alone!
In this talk, I’ll guide you through the crossroads where Scala intersects with AI, some applications aimed at boosting developer productivity, others focused on integrating your code with LLMs.
By the end of the talk, we’ll build a simple Scala application that can be incorporated into your agentic workflow and used within a no-code AI flow, making it self-hostable.
Key Takeaways:
1. Understand the current AI ecosystem in Scala: tools, frameworks, and interoperability.
2. Learn how to combine no-code platforms (like n8n) with Scala-based tools for real-world AI integrations.
3. See a demo of a custom MCP server written in Scala, and how it augments n8n workflows.
4. Leave inspired that individual developers and small teams can meaningfully innovate in the AI + Scala space.
We'll explore type classes in Scala 3, using its new rules for givens, extension methods, and mechanisms for automatic derivation via mirrors or macros.
In this talk, I will introduce the highlights of what to look forward to in Scala 3.9 LTS, as well as how to think about the upcoming new release.
This will be a live coding demonstration of Scala's newest feature set: capture checking.
In this talk, I will present insights from running the Open Community Build, where we continuously build and migrate nearly 2,000 open-source projects to the newest Scala Next versions, from scratch, every week.
Protobuf is commonly associated with code generation. However, in large projects with tens of thousands of message definitions, this approach can lead to an overwhelming amount of generated code. In this talk, I’ll share my journey in search of a different approach to this problem.
