Still Your Car. Still Your Wrench.
What AI Coding Tools Don’t Tell You About Building Real Software
When One AI Rewrites for Another
Prompt rewriting isn’t just a clever trick — it’s becoming core infrastructure. From cloud tools to agent chains, we’re seeing a shift: one AI clarifies the ask, another executes. The result? Fewer errors. Smarter systems.
Help Me Help You (Help Me)
One AI helps another do its job better. I use GPT to rewrite prompts for Lovable — cutting errors, saving time, and revealing a deeper pattern: intent → refiner → executor. This isn’t just prompt cleanup. It’s the start of a new architecture.
How I Used One AI to Train Another: A Tactical Reset in Data Architecture and AI Tooling Strategy
Like most devs experimenting with AI tools, I’ve found myself juggling multiple platforms, APIs, and half-understood schemas to build things faster. Sometimes it works. Other times, it works against you.
$50 of AI Later: Lessons from Burning Credits Fast
AI credits vanished quickly, highlighting hidden costs and forcing clarity into my development process. Here's how a $50 investment turned into a practical blueprint for smarter AI‑assisted builds.
The Lost‑Phone Test for AI: Could Your Org Still Function Tomorrow?
Dropped phone, lost life. Same test applies to corporate AI: if your copilots vanished tomorrow, would work even slow down? The “Lost-Phone Test” exposes integration gaps and makes the case for a Chief Intelligence Officer to weave tools into real workflows.
Overnight Dev: From Rage-Quit to Release in 72 Hours—With AI Riding Shotgun
Burned-out coder to live app in one weekend: two failed scrapers, one hidden JSON API, and AI tools that scaffolded the rest. How DevTools + GPT turned AES volleyball data into an MVP—and why your next Jira ticket might build itself.