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Understanding AI Coding Patterns Through Cognitive Load Theory

AI coding assistants either severely harm learning or enhance it beyond manual coding—depending entirely on interaction patterns. A recent study reveals six distinct patterns with dramatically different outcomes. We’ll examine why through cognitive psychology and explore the study’s limitations.

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Neuland reloaded

When Angela Merkel said in 2013 that the internet is ‘Neuland’ (uncharted territory) for all of us, the amusement online was considerable. Viewed from some temporal and substantive distance, one can now recognize a perspective from which she was indeed correct.

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From Vibe Coder to Code Owner

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I sandboxed my coding agents. Now I control their network.

I want my AI coding agents to work independently, but I don’t want them to have unrestricted access to the internet. In this post, I describe how I routed all network traffic from my development sandbox through a strict proxy allowlist, allowing only a small set of explicitly approved domains. This setup finally gave me enough confidence to loosen the guardrails without constantly staying in the loop.

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Your Database Table is an awful API

A shared database table can feel like the ultimate shortcut: no API design, no contracts - just a schema. The catch is that this convenience quietly turns into friction: it blurs boundaries, slows change, and makes independent evolution harder than it needs to be. This article looks at why tables (and data-model-shaped “generated APIs”) are such a tempting trap - and what better integration boundaries look like.

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Let’s Not Normalize Insecure AI Assistants

How the Lethal Trifecta Makes Today’s AI Assistants Unsafe by Design

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What to Do While the AI Is Thinking

AI can write code while we wait — but that doesn’t mean we suddenly have free time. Whether we should think, multitask, review, or rest depends on what kind of work we are doing.

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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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I sandboxed my coding agents. You should too.

My Lima VM + JetBrains Gateway setup for safe agentic development

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Leave It Better Than You Found It

Leave your code better than you found it. This advice, also known as the Scout Rule, sounds so simple, but what does it look like in practice? This is the story of how I followed the advice and cleaned up a fat controller along the way, and how this unexpectedly enabled us to handle new requirements quickly and with minimal effort. It’s a lesson in habits and continuous architecture.

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Why not scatter @Transactional everywhere?

@Transactional — great when you know when not to use it. Use it consciously instead of sprinkling it everywhere!

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From FOMO to Focus

Clear Priorities in the AI Jungle with AI Opportunity Mapping

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Speed vs. Skill

Every AI coding tool promises the same thing: unprecedented speed, effortless productivity, freedom from tedious work. The pitch is compelling. But what if feeling more productive and being more capable aren’t the same thing? Research shows that automation makes us feel more productive while eroding our skills. Let’s examine this tension through the lens of cognitive psychology.

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Context Engineering: Managing AI-Generated Code Complexity

AI tools make developers more productive at writing code, but can overwhelm code reviewers with massive changes. Learn practical strategies for managing context in AI-assisted development to keep your code comprehensible, your reviews manageable, and your team’s productivity genuinely improved. Small scope was always good practice—with AI, it’s essential.

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Swiss Army Knife for Salesforce: LLM with In-Memory Database

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Git Clarity: Building Meaningful Commits and Linear History

Feeling overwhelmed by Git’s complexity? Discover a streamlined workflow that centers on creating single, comprehensible commits. Learn how this approach leads to clearer code reviews, fewer merge conflicts, and a beautiful linear commit history that tells the story of your code. This isn’t just about Git commands—it’s about aligning your tools with how your brain works.

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Achieving Digital Sovereignty with Standard Software

In the context of IT system landscapes, digital sovereignty is often equated with autarky— complete independence from third parties. By that logic, , a company developing and operating all applications in-house would be the ultimate example of digital sovereignty. But does this idea really hold up?

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Managing Geopolitical Risks with Enterprise Architecture

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Modern Legacy (thanks to AI)

The discussion around software modernization is currently dominated by solutions involving artificial intelligence (AI) in software development. AI-assisted code completion, agentic software engineering, and other tools promise to massively accelerate development processes. The obvious thought is to apply these tools directly to existing code as well: refactorings, re-documentation, or even generated code for new features in legacy systems. Technically, much of this is already possible, and the buzzword industry is once again in full swing. Yet these code-centric, AI-driven approaches can be shortsighted for organizations tangled in a jungle of legacy systems. A modernization that focuses solely on code quickly leads to modern legacy: systems that appear technically advanced and well documented thanks to AI, but whose actual purpose has long become questionable.

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A Governance Framework for Digital Sovereignty

In an increasingly connected world where digital infrastructure forms the backbone of our economy and society, the topic of digital sovereignty is gaining more and more attention. For decision-makers in German-speaking countries, this goes far beyond merely selecting a cloud provider. It’s about strategic agency, resilience, and the ability to actively shape one’s digital future. This article explores how a robust governance methodology can help organizations not only understand digital sovereignty but also put it into practice—without sacrificing convenience or innovation.

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The Path to Heterogeneous Cloud Platforms

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Data Inventories in the EU Data Act: The Democratization of IoT Devices

Starting in September 2025, the EU Data Act (Regulation (EU) 2023/2854) will require companies that collect or process data from connected devices to maintain comprehensive data inventories.

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Digital Sovereignty: Why Architecture Matters and How to Make Your Company Resilient

In an era where digital systems form the backbone of our economy and society, control over one’s digital future is increasingly becoming the focus of strategic decisions. For many technology decision-makers in German-speaking regions, this is not just a political or regulatory challenge, but a fundamental task with far-reaching implications for software architecture work.

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EU Data Act: The Beginning of the End for Cloud Monoculture?

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Think Locally: On-Premise LLMs as Drivers of Competitive Advantage

Consider this scenario: Your organisation has integrated AI tools into critical business processes, your legal team has carefully reviewed data processing agreements, and your IT department has configured systems to comply with GDPR requirements. Then, a foreign court issues an order that overrides all these protections, requiring your AI provider to indefinitely retain data that should be deleted—including potentially sensitive corporate information shared by your employees.