Industrial sensors are becoming more capable, more configurable, and more software-defined. Yet developer support for programming these devices often lags behind their technical complexity. In this talk, we share how SICK is building an agent-powered developer experience for a programmable industrial sensor platform using a domain-specific LUA-based framework.

We walk through our journey from an initial RAG-based GitHub Copilot extension—designed to provide code completions and contextual guidance for our APIs—to a conversational developer assistant supported by a custom Bot and an MCP (Model Context Protocol) server. Building on these foundations, we are now aiming to transition to a fully agentic approach, moving toward an A2A (Agent-to-Agent) architecture capable of richer reasoning, tool use, and autonomous workflows.

Participants will learn how structured RAG, domain-specific knowledge models, and MCP-based tooling can evolve into multi-agent systems that provide deep, context-aware support for engineering teams. We highlight our practical lessons, pitfalls, and architectural decisions—showing how agentic technologies can accelerate onboarding, reduce development errors, and unlock a new generation of intelligent support for industrial sensor developers.