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Drawing from multiple Scala LLM workshops we conducted this past year, I will share insights to significantly enhance your AI experience.
Large language models and agentic systems are currently very popular, with many advocating for their use. However, they sometimes fail to deliver the expected 'magical' results. Does this mean they are not useful? Absolutely not. With the right strategy and tools, you can leverage them effectively in Scala using existing solutions like the Metals Language Server. While this may not be a '10x developer' experience, even a 50% productivity boost is a significant win.
Drawing from multiple Scala LLM workshops we conducted this past year, I will share insights to significantly enhance your AI experience. I'll cover LLM fundamentals, but my primary focus will be on the Model Context Protocol and the agentic system tooling, particularly our solutions within the Scala ecosystem. These tools allow agents to interact with your machine and the external world in a controlled way, providing LLMs with crucial feedback to refine their output. My goal is for the audience to leave with a strong foundational understanding of how to use AI tools and where to seek further improvements.
Writing client-facing APIs involves mundane tasks, whether it be REST, GraphQL, or gRPC. In this talk, I will pick two repetitive tasks during API development and demonstrate how we can utilize Scala to automate the most boring parts.
I would like to present the use of NamedTuples to implement some cool things in SQL Libraries
In this presentation, I will demonstrate how we leveraged the strengths of Scala and TypeScript to develop a collaborative text editor that meets the strictest standards for security, performance, and real-time collaboration.
