Context Engineering on Pfisterer Consulting

My LinkedIn strategy as code: building a multi-agent content pipeline

Tue, 19 May 2026 15:00:00 +0200

Last Sunday, 22:00. On my desk are eleven Markdown files, next to them an open spreadsheet with 90 days of LinkedIn analytics. Cold mate in the glass, an honest question in the back of my head about why I am building a pipeline rather than writing the next post.

The spreadsheet gives a clear answer. My profile has 511 followers and delivered 44,483 impressions over the last 90 days at an engagement rate of 0.18 percent, a factor of 11 to 16 below the LinkedIn benchmark of two to three percent. On 52 of those 90 days the feed stayed entirely silent, without a single reaction to any of my posts.

Context Rot in AI Agents: Why Quality Degrades

Tue, 31 Mar 2026 14:30:00 +0200

Anyone who works with Claude Code, Cursor, or Copilot knows the pattern. The problem has a name: Context Rot. The first results are sharp and the architecture holds up. Then quality drops off. After 20, 30 minutes, the answers start repeating themselves. The AI agent loses context. It produces code that contradicts what it wrote five prompts ago.

Not a user error – an architecture problem. The solution lies in context engineering: the deliberate management of context windows through multi-agent orchestration. These are exactly the kinds of real-world problems I address in my AI & Automation consulting.