Claude Desktop in the enterprise: data protection and GDPR in practice
Data flows, data residency, bring-your-own-key: what I always clarify first in consulting projects before Claude Desktop is rolled out in a company.
What comes up in my work: what works, what doesn't, and why.
Data flows, data residency, bring-your-own-key: what I always clarify first in consulting projects before Claude Desktop is rolled out in a company.
Desktop for knowledge work, Code for the terminal. Comparison table, risk profiles, plans, and what I actually recommend teams start with.
Log file, status page, network path: three checks find the cause in minutes. Symptom index, MCP servers and corporate networks, with the actual commands.
Which MCP servers in Claude Desktop are actually worth it: my proven selection, safe setup and what I really use day to day.
Before the first installer run I clarify three things: plan, data, MCP servers. After that, installation takes under ten minutes on every platform.
Andrej Karpathy’s three-layer method for working with Claude and friends: spec, verification, environment. Get more out of AI, without the hype.
The 12 most useful Claude Code features in practice, what they do and when they pay off. Explained concisely by Martin Pletzenauer.
Sub-agents divide up the work: a clean context, parallel jobs, cheaper models and honest reviews. When they are worth it, and when they are not.
Everyone uses the same AI model. Your context is what makes the difference. How one simple questioning routine gets your knowledge cleanly into the system.
What is answer engine optimization? How AEO differs from SEO, why AI search converts, and how to win mentions instead of rankings.