AIX: The AI Experience Methodology
A methodology for designing how humans work with AI
AI is fast but unreliable. Most teams don't have a shared process for working with it—so outputs are inconsistent, require endless iterations, and can't be reused. AIX gives design and engineering teams a repeatable framework to ship AI-assisted work at quality.
The 5 Layers of AIX
AIX is a standard methodology composed of five layers. Think of it like a design system—but for AI collaboration. These layers define how intent is captured, context is supplied, constraints are enforced, quality is evaluated, and iterations become reusable assets.
The result: AI outputs that meet your standards the first time, not the fifteenth.
Intent
Define the goal before execution. What does success look like? What should the AI optimize for—speed, creativity, or precision?
Context
Provide the necessary background to prevent guessing. Give the AI your design system, brand guidelines, user research, and technical constraints upfront.
Constraints
Set boundaries ("truth") that the system must obey. Hard rules the AI cannot violate—like accessibility standards, brand colors, or legal requirements.
Evaluation
Define what "quality" means before judging the result. Set objective criteria: Does it match the design system? Is it accessible? Does it solve the user problem?
Iteration
Refine, reuse, and standardize what works into repeatable workflows. Turn successful AI interactions into templates your entire team can use.
Reference Implementation
The AIX Compiler is the reference implementation that operationalizes the Intent and Constraints layers with a "blueprint"-like governed middleware: Platform + Tool + Operator + Guard.
It's how teams put AIX into practice—turning the methodology into enforced, auditable workflows that scale across your organization.
AIX (AI Experience) is a methodology for designing human-AI workflows. Used by product teams to ensure AI-generated designs, code, and content meet quality standards before shipping. Created by Syed Shahab .