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Insights · AI trends for mid-market

AI analysisfrom an operational angle.

We write about what we build daily — and what's changing right now for owner-led mid-market companies in the DACH region. No hot takes, no hype cycles. Insights from operational reality.

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8 articles

SWE-bench explained: what the key coding-agent benchmark really measures

Why real GitHub issues matter more than toy tasks — and what companies should learn from SWE-bench.

Claude Code vs OpenAI Codex vs GitHub Copilot

The business comparison: assistance, agent work, limits and useful company workflows.

Vibe coding is not enough: companies need agentic coding

Demos are easy. Maintainable software needs structure, tests, architecture and ownership.

54 AI agents in use: how Digital Maker automates coding, marketing and operations

Our proof: not just talking about agents, but working daily with specialized roles.

AI coding agents: how good are they really?

The pillar article on benchmarks, SWE-bench and the difference between tools and managed agent systems.

Model Context Protocol: Why 2026 is the year of AI integration

MCP sounds like tech insider jargon but is probably the most important development of the year for anyone wanting to connect AI to business systems. What it is, and why it matters now.

"Agentic AI" and other buzzwords: What does it actually mean for your operation?

When consultant decks throw around "Agentic AI", "Autonomous Workflows" and "Multi-Modal Systems", a reality check pays off. We translate the buzzwords into operational reality — showing where the hype holds, and where it tips over.