Two years ago I hit a wall with prompt engineering. I kept tweaking prompts. Rewording them. Adding more context. Getting inconsistent results. And I realized — the problem wasn’t the prompt. The problem was I hadn’t defined my intent. That realization became Intent-Driven Engineering. Not a rebrand. Not a consulting package. A methodology I built from scratch at LearnTeachMaster.org — free, open, practitioner-first — because I needed it to work on real enterprise delivery. S

How Enterprises Save Themselves: Stop Chasing AI Hype and Start Empowering Your People There’s a strange pattern happening across the technology world right now. Big corporations are racing to build “the ultimate AI platform.” Executives are holding emergency strategy meetings. Vendors are promising revolutionary systems. Universities are redesigning programs around automation. And somehow, in the middle of all of this… …the people actually solving the problems every day are

Escaping the Sandbox: Where Developer Creativity Fits Inside Intent-Driven Engineering There’s a danger starting to appear in enterprise AI engineering. Everybody got excited about agents. Then governance showed up. Then plugins. Then hooks. Then policy engines. Then execution guardrails. Then “approved patterns.” Then 47 bootstrap files before a developer can even write a line of business logic. And suddenly the engineering team feels trapped inside a giant compliance maze.

🚀 Most teams don’t fail because of bad intent. They fail because of blind execution. Every team wants the same things: Better performance Higher reliability Faster delivery Lower cost But look at what actually happens: ❌ Add caching everywhere ❌ Retry every request ❌ Log everything ❌ Move everything to Kubernetes ❌ Add auth everywhere ❌ Add more tests ❌ Catch all exceptions 👉 It feels like progress 👉 It’s actually noise ⚠️ The hidden pattern Action → Guess → Add More → Hop