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Layr – a modular UX and product constraint system for AI-built interfaces

Layr, a modular production system for AI-built interfaces, enables developers to turn UX, design, accessibility, security, and other principles into enforceable constraints, reducing friction and improving usability. The system works with tools like Claude and Cursor, requiring zero setup, and provides structured prompts to guide AI in generating production-ready apps. Layr aims to solve common issues in AI-generated interfaces such as weak hierarchy and excessive decision-making.

read10 min views1 publishedJun 18, 2026

A modular production system for turning AI-built interfaces into production-grade apps. Layr turns proven UX, design, accessibility, security, performance, SEO, CRO, marketing, and copywriting principles into enforceable constraints that reduce friction, build trust, and drive action.

Works with Claude, Cursor, and other agentic development tools.

Turn typical AI output into a clearer, more usable, more production-ready interface.

Layr works with zero setup.

Start with Option 1. If your tool cannot read GitHub URLs, use Option 2.

Use this when your tool can read GitHub URLs.

Copy this prompt, paste it into your tool, then replace the task line with your own request:

Use https://github.com/layr-hq/layr as the production system for AI-built apps.

Read SYSTEM.md first, then RUN.md, then follow them.

Scope: Auto
Depth: Standard

Task:
Improve the pricing page so users can choose a plan faster.

Use this when your tool works best with local files or cannot reliably read GitHub URLs.

  • Download or clone this repo into your project root as layr

. - Copy this prompt and paste it into your tool.

  • Replace the task line with your own request.
Use ./layr/RUN.md for this task.
Read ./layr/SYSTEM.md first, then ./layr/RUN.md, then follow them.

Scope: Auto
Depth: Standard

Task:
Improve the pricing page so users can choose a plan faster.

This is optional. Use it when you want stronger product and brand fit.

  • Copy this file:
layr/layr.config.example.md
  • Rename the copy to:
layr/layr.config.md
  • Fill only what you know. Leave the rest blank.

Do not edit modules/

, methods/

, or RUN.md

.

This is optional. Use it for important screens where precision matters.

  • Copy the screen template:
layr/screens/screen-template.md
  • Rename the copy to match the screen:
layr/screens/pricing.md
layr/screens/onboarding.md
layr/screens/dashboard.md
  • Fill only the fields that materially affect the result.

“Create a dashboard for a project management app”

→ Layr selects the relevant modules and improves the output against production rules.

What this isWhat it’s based on / MethodsWhy it mattersHow the system worksSystem kernelSurface playbooksQuality modesModule systemInstructionsFilesVersion historyGoalLicense

Layr is a rule-based production system for AI-built software.

It gives agentic tools a structured way to select the right product modules, apply proven methods, score the result, and improve weak areas before the output ships.

  • Hick’s Law - reduce choices
  • Cognitive Load - reduce thinking
  • Fitts’s Law - make actions easier
  • Jakob’s Law - use familiar patterns
  • Peak-End Rule - improve memorable moments
  • Goal Gradient - show progress
  • Gestalt - create clear structure
  • Signal vs Noise - remove clutter
  • Default Bias - guide decisions
  • Colour Theory - guide attention
  • Typography - improve readability
  • Spacing Rhythm - clarify structure
  • Accessibility - make interfaces usable for more people
  • Security - catch unsafe patterns before shipping
  • Performance - keep the product fast and stable
  • Analytics - measure behaviour and product learning
  • QA - catch edge cases and release risks
  • AI Product - make AI features trustworthy and controllable
  • CRO - reduce friction and increase action
  • SEO and AI Search - make content easier for search engines and AI systems to understand
  • Marketing - sharpen positioning and value communication
  • Copywriting - make messages clear, specific, and persuasive
  • and more

Most tools know these ideas. Layr makes them operational.

AI can generate working screens quickly, but working is not the same as production-ready.

Without a system, AI output often has:

  • weak hierarchy
  • too many decisions
  • unclear flows
  • inconsistent design
  • missing accessibility
  • fragile security
  • poor performance
  • weak conversion paths
  • vague copy

Layr pushes the AI toward:

  • clarity
  • speed
  • trust
  • accessibility
  • measurable behaviour
  • obvious next steps
  • production quality

Build with real production standards, not AI guesses.

flowchart TD
    A["Task or repo URL"] --> B{"Optional context?"}
    B -- "No setup" --> C["Infer from task + codebase"]
    B -- "Config or screen brief" --> D["Read layr.config.md / screens"]
    C --> E["Scope + depth control"]
    D --> E
    E --> F["Selected module rules"]
    F --> G["Methods index + selected methods"]
    G --> H["Build or improve interface"]
    H --> I["Scorecard with evidence"]
    I --> J{"Score >= 85?"}
    J -- "No" --> K["Improve weak areas"]
    K --> I
    J -- "Yes" --> L["Clear, usable output"]

    classDef input fill:#0f172a,stroke:#64748b,color:#f8fafc;
    classDef rules fill:#111827,stroke:#818cf8,color:#f8fafc;
    classDef action fill:#172554,stroke:#60a5fa,color:#f8fafc;
    classDef decision fill:#312e81,stroke:#a5b4fc,color:#f8fafc;
    classDef output fill:#064e3b,stroke:#34d399,color:#ecfdf5;

    class A,C,D input;
    class E,F,G rules;
    class H,I,K action;
    class B,J decision;
    class L output;
Mode Best for What the user provides Quality
Zero setup Trying Layr quickly, simple fixes, reviews Task only Strong production improvement
Recommended Real product work Task + optional layr.config.md
Better product, user, and brand fit
Screen-level High-value screens and flows Task + config + optional screen brief Highest precision

Layr should never block on missing context unless the missing detail would materially change the product direction.

If context is missing, Layr should infer it and state assumptions briefly.

SYSTEM.md

is Layr's central operating layer.

It defines how the system selects surface types, loads playbooks, applies hard gates, resolves method conflicts, and keeps recommendations tied to evidence.

The kernel improves consistency across tasks by requiring every recommendation to connect to at least one of:

  • a selected Layr module
  • a selected Layr method
  • an observed product issue
  • a scorecard hard gate
  • a measurable production risk

This keeps Layr science backed, evidence driven, and focused on production quality rather than taste.

Surface playbooks make Layr practical for common production work.

They define the required modules, recommended methods, hard gates, production rules, failure patterns, and evidence requirements for each major surface.

Current playbooks cover:

  • pricing
  • signup and onboarding
  • dashboards and workspaces
  • forms and settings
  • checkout and upgrade
  • public pages and docs
  • AI features

Surface scorecards in scorecards/

make scoring more specific and consistent for each surface.

Layr started with UX and Design because that is where AI-built products usually break first: unclear flows, weak hierarchy, messy screens, and interfaces that work but do not feel production-ready.

Layr now works as a broader production layer for AI-built software.

Active modules cover UX, Design, Accessibility, Security, Performance, Analytics, QA, AI Product, CRO, SEO, Marketing, and Copywriting.

AI Search is supported through the SEO module when the task involves AI answers, retrieval visibility, GEO, ChatGPT search, Copilot visibility, or answer-engine discoverability.

The system is designed so new modules can be added without making Layr harder to use.

The prompt stays simple:

Use Layr for this task.

Scope: Auto
Depth: Standard

Layr chooses the relevant active modules automatically, so you don't have to understand the whole system.

See ROADMAP.md

for the planned module direction.

Use this system to build, review, or improve generated product work until it is clearer, safer, faster, more accessible, more measurable, and more production-ready.

If your tool can read GitHub URLs, copy this prompt and paste it into your tool:

Use https://github.com/layr-hq/layr as the production system for AI-built apps.
Read SYSTEM.md first, then RUN.md, then follow them.

Scope: Auto
Depth: Standard

Task:
Improve the pricing page so users can choose a plan faster.

If your tool cannot read GitHub URLs, download or clone this repo into your project root as layr

.

Then copy this prompt and paste it into your tool:

Use ./layr/RUN.md for this task.
Read ./layr/SYSTEM.md first, then ./layr/RUN.md, then follow them.

Scope: Auto
Depth: Standard

Task:
Improve the pricing page so users can choose a plan faster.

If your tool cannot read GitHub URLs reliably, use the local folder option.

Replace the example task with what you want the AI to build, fix, review, or improve.

Good:

Improve the pricing page so users can choose a plan faster.

Better:

Improve the pricing page for early-stage SaaS founders.
The primary action is starting a free trial.
Preserve the existing design system.

This step is optional.

For better product fit, copy layr.config.example.md

, rename the copy to layr.config.md

, and fill only what you know.

Minimum useful context:

Product name:
Primary user:
Core user goal:
Primary product action:
Design source:

This is optional. Layr still works without it.

This step is optional.

For important screens, copy layr/screens/screen-template.md

, rename the copy, and fill only what matters.

Minimum useful screen context:

Screen name:
User intent:
Primary goal:
Primary action:

This is optional. Layr should infer missing screen context from the task and codebase.

Layr will:

  • read the system kernel
  • load the relevant surface playbook
  • read Layr rules
  • select relevant methods
  • infer missing context when safe
  • ask at most 3 questions only when context is truly blocking
  • build, review, or improve the product surface
  • score the result with evidence
  • fix weak areas
  • repeat until the output scores at least 85
File Purpose User edits?
SYSTEM.md
Central operating layer for surface selection, hard gates, conflict rules, and evidence standards No
RUN.md
Main execution entry point for agentic tools No
playbooks/index.md
Surface playbook routing No
playbooks/*.md
Production playbooks for common product surfaces No
modules/index.md
Active and planned module routing No
modules/ux.md
UX behaviour, rules, scoring, and validation No
modules/design.md
Layout, hierarchy, spacing, and visual clarity No
modules/accessibility.md
Accessibility rules and validation No
modules/security.md
Security rules and risk checks No
modules/performance.md
Performance rules and interaction checks No
modules/analytics.md
Measurement and event tracking rules No
modules/qa.md
QA, edge case, and release readiness rules No
modules/ai.md
AI product behaviour and trust rules No
modules/cro.md
Conversion and friction reduction rules No
modules/seo.md
SEO and AI Search rules No
modules/marketing.md
Positioning and messaging rules No
modules/copywriting.md
Copy clarity and persuasion rules No
methods/index.md
Routes relevant methods by scope, surface, and problem No
methods/*/*.md
Science-backed production methods by module No
scorecard.md
Evidence-based UX scoring No
scorecards/index.md
Surface-specific scorecard routing No
scorecards/*.md
Surface-specific evidence scoring templates No
layr.config.example.md
Optional product context template Copy to layr.config.md
screens/screen-template.md
Optional screen brief template Copy for important screens
prompts/master.md
Compatibility prompt for users who prefer /prompts
No
ROADMAP.md
Future module direction No
CHANGELOG.md
Version history and release notes No

See CHANGELOG.md

for version history.

The end user should:

  • understand instantly
  • know exactly what to do
  • take action without hesitation
  • never feel confused or overwhelmed
  • move through the flow with minimal effort
  • reach value as quickly as possible

The experience should feel:

  • obvious
  • fast
  • clear
  • predictable
  • low effort

If the user has to:

  • think
  • re-read
  • hesitate
  • search for what to do

It failed.

Free to use in personal and commercial projects.

Not allowed to resell or redistribute this as a standalone product.

Build with real production standards, not AI guesses.

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