📈 Letting AI Drive: From Hell Loops to Happy Commits

-letting-ai-drive:-from-hell-loops-to-happy-commits

What does 600,000+ lines of AI-generated code look like in the wild?

🛠️ What I Built (Still Private)

The project lives inside company infrastructure and isn’t public (yet).

But it’s real. And it works.

  • NodeJS-based
  • Structured with full test coverage
  • Designed to be extended by others (once approved)
  • Architecture evolved through prompt iteration

If I get approval, I’ll share everything — code, planning docs, prompt chains, and even some of the generated reports. Might take time, but it’s in progress.

📊 Code & Commit Stats

Section Files Lines
Source Code 19 2,417
Tests 25 5,424
Config 17 465
GitHub (instructions + prompts) 11 693
Copilot Output (raw history + generated reports) 52 597,908
User Docs 5 733
Total 129 607,640

Yes, those numbers are real.

Yes, Copilot occasionally lies — but it does ship.

📆 Git Commit Summary

From the full project commit history:

  • Files changed: 514
  • Lines added: 626,703
  • Lines removed: 5,011

Commit messages were detailed, line-item breakdowns — generated by Copilot and checked by Commitlint.

Several early Copilot hell loops led to entire archived branches in the beginning.

But as I refined prompts and adjusted expectations, the implementation strategy matured.

Fewer rewrites, cleaner commits, better momentum.

⚠️ What This Isn’t (But Still Is)

  • Not production-ready
  • Not public
  • Not a product

But it is:

  • A real, working proof of concept
  • A hands-on case study
  • Enterprise-driven architecture and implementation (yes, really)
  • A patience-builder
  • Magic + madness = perfect

🎨 Parting Thought

Happy committing!

Happy Commits

“There are no mistakes, only happy little commits.”

— Bob Ross × GitHub Copilot

✨ Let’s Compare Notes

Been through the AI dev trenches? Want to swap commit stats, prompting techniques, or chaos stories?

I’m always down to talk shop — just give me a minute to come up for air.

Still chasing approval for the repo, but if you’re curious (or skeptical), I’m open to questions, ideas, or even a friendly challenge.

This was Part 2 of the series.

If I get approval, I’ll follow up with sanitized prompt guides, redacted instruction templates, or maybe even a Copilot-powered case study… written by ChatGPT.

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