I started using AI over a year ago and kept hitting the same wall. Magic prompts, inconsistent results, starting over every time. Sound familiar?
Then I started building something different. Not better prompts. Frameworks.
Here's what I mean. After tailoring several resumes and repeatedly telling AI "don't embellish my experience" or "don't invent technologies I haven't used," I asked it to analyze our interactions and create a framework capturing all these recurring requirements. The framework became part of project knowledge, making future attempts consistent. No more repeating the same corrections.
When Claude released Skills, I recognized the concept. I'd been building something similar for over a year. Skills take it further with bundled code and executable scripts. My frameworks focus on workflow stages, MCP tool orchestration, and preserving human decision points. Same core idea, different implementations.
The results: 3 published Drupal contrib modules, 17+ blog articles, automated social media campaigns generating 5-10 posts per piece. For Drupal development, I have AI read SDC documentation, Core code, and relevant resources, then create frameworks from that foundation.
You'll see the actual frameworks I use. Phase-based development for contrib-quality modules. A 7-stage editorial workflow with real quality control. Content systems with database tracking. I'll show what failed along the way and demonstrate how frameworks turn AI from unpredictable helper into reliable partner.
Whether you're developing modules, writing content, or analyzing data, these systems work because they're built on what you already know, not AI magic.
