Let's Teach LLMs to Write Great Scala! By Kannupriya Kalra
Large Language Models (LLMs) are transforming how we build intelligent applications, but most tooling and best practices are centered around Python. Why should Python have all the fun? In this talk, we'll explore how LLMs work, from zero-shot prompting to agentic feedback loops, and discuss why typed languages like Scala offer a better foundation for building reliable, maintainable AI-powered applications.
We'll examine lessons from Python’s ecosystem—LangChain, LiteLLM, and PydanticAI—and why Scala deserves its own first-class LLM toolkit. Enter LLM4S, a project bringing structured, type-safe AI development to Scala. We'll dive into how we can leverage Scala’s strengths for robust tool calling, multi-step workflows, and agentic programming.
Join us to see how we can teach LLMs to generate great Scala code—and why that’s a game-changer for AI development.
Kannupriya Kalra is a functional programming enthusiast and Scala developer with 10 years of experience in building scalable software solutions. Currently a Software Engineer at Sky in London, she develops and maintains critical backend applications using functional Scala. She has previously contributed to Scala projects in various organizations in India, focusing on data engineering. Her expertise includes Scala, Akka, and big data technologies.
As a Google Summer of Code 2024 mentor with Scala Center, she contributed to Scaladex and Scala CLI projects. Additionally, Kannupriya is the org admin for the Google Summer of Code 2025 program with Scala Center, where she plays a pivotal role in guiding and shaping future open-source contributions. In 2024, she represented Scala Center at the Google Open Source Conference in Sunnyvale, California. With a passion for sharing knowledge, Kannupriya has delivered talks in four countries, inspiring and engaging developers worldwide.
Learn more about Kannupriya Kalra on LinkedIn
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