TOOLS & PATTERNS
AI prototyping
I pair low-code tools with AI to make ideas tangible early. The goal is to build prototypes that test assumptions, gather reactions, and help teams converge before we commit engineering effort.
Overview
AI prototypes help teams see possibilities before investing heavily. I blend existing systems, low-code scaffolding, and AI calls to validate workflows, surface constraints, and decide what deserves a real build.
What I ship
- Lightweight prototypes that combine AI with existing tools.
- Experiments aimed at testing assumptions and edge cases early.
- Artifacts that teams can react to so we converge before committing.
Patterns
Assumption mapping
Map the riskiest assumptions, then design prototypes that provoke quick feedback.
Low-code scaffolding
Use low-code shells plus AI calls to simulate the flow without heavy lift.
Convergence artifacts
Produce artifacts teams can react to—scripts, flows, or small demos—to decide what to build.
Examples
Artifacts coming soon.
Notes
AI prototyping works best when we want to test direction, not productionize. It helps teams see tradeoffs quickly and avoid over-investing in ideas that don’t hold up when exposed to real workflows or users.