How I Work With AIs (And Why)
A behind-the-scenes look at how I use GPT and Lovable together. One rewrites the prompt. One generates the code. I just define the intent — and stay out of the way. This isn’t a tech stack. It’s a new mode of working.
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Prompt Strategists, Agent Orchestras, and What Comes Next
Prompting is evolving into orchestration. One AI clarifies, another executes, a third checks the result. We’re entering an era where modular intelligence matters — and prompts become the interface between thinking systems.
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.