Skills To Go! Bringing Your Kotlin Knowledge Across AI Agents

After adopting an AI agent, you often run into the same friction: recurring development tasks such as running code style checks, static analysis, and automated workflows still require you to write prompts manually. Even as large language models get better at understanding developers' intent, team development knowledge remains difficult to pass to an agent in a stable, portable, and low-cost way.

This talk traces the evolution of developer and AI collaboration and explains why Agent Skills are becoming the next tool worth investing in for Kotlin engineers. A Skill packages repeatable workflows, tool usage, and team conventions into a reusable unit, so the agent loads the right knowledge only when needed, reducing token waste and lowering the cost of teaching AI the same things over and over.

We will then walk through scenarios familiar to Kotlin developers to introduce the basic architecture of Skills, how scope and management differ across agents and development environments, and what kinds of knowledge and use cases in the Kotlin ecosystem are worth turning into Skills. Finally, we will look at how open-source tooling can keep Skills from being locked to a single vendor, machine, or project, maximizing the value that Skills can bring.