Personalized AI Collaboration Framework

The problem

Most AI assistants are built for everyone, which means they’re optimized for no one. Generic prompting produces generic collaboration — and for people whose thinking patterns don’t fit the default, AI tools can feel like friction rather than flow.

What we designed

A framework for building personalized AI collaborators matched to specific cognitive styles and work rhythms. Rather than one-size-fits-all prompting, the methodology uses explicit role definitions with communication protocols tuned to how someone actually thinks and works.

The flagship implementation — Pemtu — is an AI project manager designed for ADHD-aligned workflows: rapid ideation cycles, momentum-preserving handoffs, and documentation that happens as a byproduct of working rather than a separate task.

What it demonstrated

• AI collaboration improves dramatically when the interaction layer accounts for cognitive diversity
• Concept-to-working-prototype sprints compressed to 2.5 hours with the right AI partnership structure
• The methodology is transferable — the same framework adapts to different cognitive profiles and working styles