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Model Context Protocol (MCP)

Articles, podcasts, talks, and more about People, Culture, and Diversity.

The Data Dilemma, Part 2

The first part showed why agents fail on undocumented data semantics and why Data Mesh is not a realistic answer for many mid-sized companies. This second part gets concrete: a Minimum Viable Data Mesh in four layers, from an honest inventory through curated views with ODCS contracts to agent access via MCP. A purchasing agent that compares suppliers and evaluates price histories serves as a running example.

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The Data Dilemma, Part 1

When AI agents fail in a company, it is rarely the model’s fault. The real problem is the data: semantics, quality, and context are written down nowhere, they live in the heads of the domain experts. Data Mesh addresses exactly this problem, but it organizationally overwhelms many mid-sized companies. This first part describes why that is and derives a Minimum Viable Data Mesh from it. The second part shows the implementation in four layers.

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Beyond Claude & GPT

How we use open-weights models for chat, coding agents, and production workloads

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Nebu: Self-made sovereignty

There are plenty of open-source alternatives to Slack. None of them deliver real sovereignty. Community editions are deliberately pared down so no company can run them in production, while enterprise features sit behind commercial licenses. This article shows why “building it yourself” is no longer a utopian idea today, but a realistic option for anyone with a product vision and a bit of DIY courage.

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AI Features for Jira Data Center – No Atlassian Cloud Required

Imagine this: after every customer meeting, structured Jira issues are created automatically. You just paste your notes into an AI, and it does the rest. Atlassian already offers that kind of magic in Jira Cloud: natural-language search, automatic summaries, and issue creation from unstructured text. But not everyone wants to move to the cloud, and many teams plan to keep using Jira Data Center through 2029. In this article, we show how to get many of the same benefits on-premises with Jira Server and your own AI stack: GDPR-compliant, resilient to Cloud Act exposure, and without data leaving your environment.

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Spec-Driven Architecture: When Agents Build, Architecture Must Speak

SDD describes how a system is built. SDA describes how systems fit together

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Let’s Not Normalize Insecure AI Assistants

AI assistants like OpenClaw promise convenience, autonomy, and increasingly personalized help. But beneath that promise lies an architecture that quietly combines private data, internet access, and exposure to untrusted content—the lethal trifecta of security risk. Sandboxing and physical isolation help, but they don’t address the core problem. As we add more capabilities, the potential blast radius only grows. This post is a case for slowing down, questioning defaults, and refusing to normalize insecure architectures.

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AI and Elaboration: Which Coding Patterns Build Understanding?

AI tools let you complete coding tasks without connecting new information to your existing mental models—a cognitive process known as elaboration that is crucial for building understanding. But some AI interaction patterns preserve this elaboration while others bypass it entirely. Let’s explore what elaboration is, why it helps with learning, and how we can use AI tools in a way that helps with this process rather than circumventing it.

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From Data Graveyards to Knowledge Landscapes

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AI — Behind the Buzzword Garbage

Tired of AI hype? Me too. But beneath the buzzwords lies real value for developers. Tools like Claude Code save me hours on routine tasks, freeing me to focus on what matters: understanding problems and building the right solutions. It’s not magic—it’s practical support that makes development faster without replacing our core skills.

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Beyond the hype: An engineer’s journey into ReBAC and AI with the Model Context Protocol

In this article, I share my experiences on my journey into the AI world. During this journey, we’ll build our own Model Context Protocol (MCP) Server using C Sharp, learn about access management with relationship based access control (ReBAC) on the way, and in the end I’ll provide my thoughts on the current state of AI and MCP, focusing on security and UX.