16 posts tagged with "Automation"

I thought I was building a blogging platform.

Then I thought I was building a note-taking platform.

Then I realized I wasn't really building either.

The blog and the notes are simply different workflows.

The actual product is something much larger.

A Git-native workflow platform.

The more I build with MCP, the more I think we're still at the beginning.

Right now people are connecting AI to GitHub.

While working on my GitOps blogging platform, another idea clicked into place.

I've wanted to organize my notes for years. Like most developers, they're scattered everywhere:

• text files;
• OneNote;
• random Markdown documents;
• Discord messages;
• ChatGPT conversations;
• scraps of paper;
• and the occasional "I'll remember this later."

I never do.

Then I realized I already built most of the solution.

When most people hear GitOps, they think Kubernetes.

Or: How I Accidentally Became an AI Middle Manager

There are weeks where you ship a feature.

Then there are weeks where you accidentally redesign your entire career.

This was one of those.

This blog is Git-backed, but that does not mean I need to sit at a desktop to publish something.

The authoring surface is ChatGPT Work. I can start from my phone, describe an idea in a normal conversation, refine it naturally, and let a repository-aware agent carry the work from Markdown all the way to production.

The interesting part is that ChatGPT is not the publishing system.

The repository is.

Status: Living document
Last updated: July 29, 2026
Maturity: Actively used and rapidly evolving

Executive Summary​

This workflow treats AI systems as specialized members of a software engineering team rather than as interchangeable coding assistants. Repository conventions, specifications, ranked milestones, reusable protocols, automated reviews, and infrastructure-as-code provide the operating structure. Short commands such as “do the next milestone” work because the repository already describes how the agent should operate.