Skip to content

nerdwglassez/ai-experience-framework

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

AI Experience Framework

A structured, repeatable system for designing and prototyping AI-enabled product experiences. Built for product designers, UX designers, and design technologists working in vibe coding workflows.


What this is

This framework gives teams a shared behavioral model for AI-assisted product design. Instead of starting with screens or ad hoc prompts, teams define the logic first — what signals are available, how confident the system can be, and what AI behavior is appropriate — then express that logic in UI.

It is designed to be used alongside AI coding tools (Claude, Cursor, Copilot, etc.) to produce consistent, reviewable prototype outputs across multiple designers and projects.


What problem it solves

Without a shared model, two designers using the same AI tool can produce completely different results — not because of skill differences, but because there are no common rules connecting signals to behavior to interface expression.

This framework makes the decision chain explicit and shared:

Signals → Intent → Confidence → Condition Logic → AI Level → Pattern → UI

Who it's for

  • Product designers and UX designers building AI-enabled product concepts
  • Design technologists prototyping adaptive experiences in vibe coding environments
  • Product teams who want to explore AI behavior systematically rather than screen by screen

How it's organized

/ai-experience-framework
  README.md                        ← You are here
  CLAUDE.md                        ← AI tool entry point and load order
  ONBOARDING.md                    ← Team onboarding guide

  /core                            ← Shared framework logic. Do not edit per-project.
    00-framework-overview.md       ← Mental model and system overview
    01-principles.md               ← Non-negotiable rules and the Level 0 gate
    02-pattern-library.md          ← 12 reusable AI interaction patterns
    03-design-system-rules.md      ← Generic component vocabulary and DS setup guide
    04-prompting-guidelines.md     ← How AI tools should interpret and respond
    05-components.md               ← Component behavior, states, and code annotation spec

  /projects
    _template/                     ← Copy this to start a new project (files 10–19)

Getting started

1. Read the core files

Start with /core/00-framework-overview.md to understand the mental model, then 01-principles.md for the rules that govern all projects.

2. Set up your design system mapping

Open /core/03-design-system-rules.md and complete the setup section — map the framework's generic component vocabulary to your team's actual design system components. This step takes 30–60 minutes and makes every subsequent session significantly more consistent.

3. Copy the template

cp -r projects/_template projects/your-project-name

4. Fill in the behavioral files first

Complete files 10 through 15 before touching 16 through 19. Behavioral logic before UI expression — always.

File What it defines
10-project-context.md Product, users, scope, constraints
11-user-jobs-and-intents.md Jobs to be done, intent states
12-signals.md Explicit and implicit signals, strength ratings
13-confidence-model.md How confidence is defined for this product
14-decision-model.md Behavior rules: given this signal state, what should the system do?
15-control-model.md Confirm, edit, dismiss, undo, transparency rules

5. Define patterns, composition, and scenarios

Complete 16-pattern-selection.md, 17-ui-composition.md, and 18-prototype-scenarios.md.

6. Set your output request

19-output-request.md tells the AI tool how to structure its responses for this project. This is what makes outputs consistent across designers.

7. Start a session

Load the AI Experience Framework for [project name].
Core files: /ai-experience-framework/core/
Project files: /ai-experience-framework/projects/[project-name]/
Begin with the output request format defined in 19-output-request.md.

The core model

Condition Logic — the four signal types

Condition What it means Confidence Starting level
A Explicit action or accumulated implicit signal High 2 or 3
B Context of focus known, specific intent unknown Medium 2
C Ambiguous signal or low implicit data Low 1–2
D Inaction, error state, or passive signal only Low 1

AI Presence Levels

Level Name Description
0 Route or withhold AI routes to existing destination or withholds action. The Level 0 gate.
1 Nudge Ambient prompt entry points, suggestion chips, non-intrusive cards
2 Conversational panel AI panel alongside existing page UI
3 Conversational canvas Conversation thread + generative output surface

The Level 0 gate

Before generating any AI pattern, evaluate whether the task involves legal consent, audit trail requirements, security verification, or intentional friction. If any apply — route to an existing destination rather than generating AI UI. See 01-principles.md for the full checklist.


Adapting for your design system

/core/03-design-system-rules.md defines a generic component vocabulary that maps to the framework's levels and patterns. Before using the framework on a project, complete the mapping table in that file to connect the generic names to your actual design system components.

/core/05-components.md defines the behavior spec, interaction states, visual rules, and code annotation guidance for each component. Two components (AssistantPanel and RecommendationCard) are fully worked as reference examples. All others follow the same structure with commentary guiding your team to fill in design-system-specific values.


Contributing

Contributions welcome:

  • New patterns for 02-pattern-library.md
  • Additional worked example projects in /projects/
  • Design system adapters (Figma component mapping, token reference sheets, etc.)
  • Improvements to the template files or component specs

Please open an issue before submitting a large change so the approach can be discussed first.


License

CC BY 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License by Bradly Zavakos.

About

A structured, repeatable system for designing and prototyping AI-enabled product experiences.

Topics

Resources

License

Stars

0 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages