Speaker

Daniël Stegeman

Daniël Stegeman

Software Engineer @ Info Support

Software Engineer @ Info Support

Nijmegen, The Netherlands

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Daniel is a software engineer specialising in .NET and Azure, with experience spanning DevOps and project teams. A strong advocate for continuous improvement, Daniel is currently focused on agentic development and regularly shares insights through writing and mentoring. Daniel is passionate about software architecture and loves connecting with others who are building the future of intelligent software.

Daniël is een software engineer gespecialiseerd in .NET en Azure, met ervaring in zowel DevOps- als projectteams. Als een sterk voorstander van continue verbetering richt Daniël zich momenteel op agentische ontwikkeling en deelt regelmatig inzichten via schrijven en het begeleiden van collega's. Daniël is gepassioneerd door software-architectuur en maakt graag verbinding met anderen die bouwen aan de toekomst van intelligente software.

Area of Expertise

  • Information & Communications Technology
  • Region & Country

Topics

  • Agentic Development
  • Software Engineering & Architecture

From IDE Agents to Operational Systems: Building Production-Ready Agent Infrastructure

You've built agents that supercharge your development workflow. They're wired into your tools through MCPs, they handle the grunt work, and your team is shipping faster. Now you're seeing agent potential everywhere: internal tooling, operations, customer-facing features. But scaling beyond IDE customization requires a different skillset: building agents as operational software systems.

This talk maps the evolution from IDE agents to internal productivity agents to customer-facing systems, with deep focus on the first critical transition. The core challenge? IDE agents are configuration and local workflows. Internal productivity agents are production software engineering with cloud resources, deployed code, agent frameworks, monitoring, and disciplined prompt and eval control. Most teams know how to customize VS Code but haven't architected autonomous systems that run unsupervised.

By treating internal productivity as a controlled-risk learning environment, you build operational trust through dogfooding before the stakes involve customers. Using real examples from one product context, we'll explore the architecture and tooling patterns that distinguish operational agent systems from IDE customization. Then we'll look toward customer-facing agents as the horizon: what skills from internal productivity transfer forward, and how to know when you're ready.

You'll walk away knowing how to identify where you are today, the operational patterns needed to transition from IDE customization to production agent systems, and what readiness signals indicate you can move toward customer-facing work.

Daniël Stegeman

Software Engineer @ Info Support

Nijmegen, The Netherlands

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