# From the factory floor to AI developer: tools that run in my own plant

> Source: <https://dev.to/maurice_putinas_bc9141cbc/from-the-factory-floor-to-ai-developer-tools-that-run-in-my-own-plant-1f58>
> Published: 2026-06-20 21:23:29+00:00

For 13 years I have worked in production at a steel-tube manufacturer. Not in an office — on the floor, with the machines, the night shifts, the handovers at 6 a.m.

A few years ago I started building software in my free time. Not tutorials for their own sake — tools that solve problems I actually see every day.

In production you learn one thing fast: it does not matter what looks good on a slide. It matters what works at shift handover. That perspective turned out to be my biggest advantage as a self-taught developer — I know the problem before I write the first line.

**PIPEZ — a shift & part-count PWA.** Offline-capable, running on Cloudflare Workers + D1, live in production to capture shift and piece-count data that used to live on paper.

**A tool-management app.** A multi-user client-server app with optimistic concurrency and a local AI assistant, used daily in the office to manage the lifecycle of dies in tube production.

**DeepCode — an agentic AI coding client.** Electron + React + TypeScript, with its own tool loop, a swarm mode, and CI/tests. The project I am proudest of.

Plus multi-agent systems, RAG pipelines, and n8n automations that run every day.

Python/FastAPI, TypeScript/React, Node, Docker, PostgreSQL + pgvector, Cloudflare Workers, MCP, computer vision.

I will be writing here about the bridge I keep coming back to: real production experience plus building with AI. If you are automating something messy and real, I would love to compare notes.