We are thrilled to welcome you to our 12th edition of AI Native Netherlands, hosted at the Studytube headquarters in Amsterdam.
In this edition, Pini takes the organisational view of AI coding adoption - how it progresses across an engineering org and the order things tend to break as it scales. Aleksei goes hands-on into the tooling - what happens when you build an MCP server the way the docs suggest, where it falls apart, and the pattern that replaces it.
A massive thank you to our host, Studytube, for their generosity in providing the venue and drinks for this evening and for supporting the Dutch AI engineering community.
How AI coding adoption progresses across an engineering org, from first licences toward a mostly automated delivery process
The order things usually break as adoption scales: coordination, review, testing, context, security boundaries, ownership, CI/CD, and product flow
Why faster individual developers don't automatically mean faster team delivery
The platform and infrastructure foundations for scaling AI-generated code safely
Where traditional MCP tools fit, and where they hit their limits
Giving a model an API plus a sandboxed code environment instead of writing a new tool for every use case
Running model-generated code safely: sandboxing, module allowlists, CPU and memory limits, static analysis, and audit logs
Speaker 1: Pini Reznik (re:cinq)
Pini Reznik is a seasoned technology leader with extensive experience in the software industry. He is the CEO and Co-Founder of re:cinq, experts in Cloud Native and AI Native engineering. Former software engineer, Co-Founder of two successful consulting businesses and an O’Reilly author.
Talk: The AI Adoption Ladder: From First Licences to the Dark Factory
AI coding tools make individual developers faster, but many teams discover that delivery does not improve at the same rate. PR volume rises, review queues grow, tests become less convincing, context gets messy, and eventually
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