An AI agent built our blog system. It worked. It also shipped a ticking time bomb. Here's why human expertise matters more, not less, in the age of agentic engineering.
A chronological account of how I went from treating AI as a smart autocomplete to running 18 specialized agents on a production engineering pipeline.
Claude Code now remembers things you didn't tell it to. For interactive use, that's a nice feature. For autonomous pipelines, it's a different problem entirely.
Claude Code keeps full conversation transcripts. I mined 700MB of them to reconstruct 20 lost journals and find the founding conversations I thought were gone.
Building CodeWithAgents.de with AI agents. What worked, what broke, what surprised me.
AI makes content production trivial. That's not the revolution — surviving the flood of mediocrity is.
I started with an empty Git repository and ended with a fully deployed mobile-first presentation on GitHub Pages — without writing a single line of code myself.
Three phases, five critical bugs, and what 97.78% OCR confidence actually looks like when real users upload real photos.
How I used an AI agent as a planning partner — not a code generator — to design a complex database migration before writing a single line.
When 18 agents each maintained their own memory files, the system became unmaintainable. The solution was a philosophical split: separate data collection from knowledge curation.