A Beginner-to-Production Handbook for Building Scalable, Maintainable, Collaborative Products with AI Agents
Status: Reusable master handbook
Audience: Absolute beginners through experienced developers joining an AI-assisted project
Scope: Product discovery → specification → design → AI reference generation → repository/bootstrap → agent system → architecture → implementation → testing → collaboration → CI/CD → release → production operations → continuous improvement
Technology stance: Technology-agnostic core. Current framework/runtime/package choices are selected through a documented freshness audit at project start.
Current-date note: Current ecosystem facts referenced in this handbook should be re-verified at the beginning of every new project. Do not copy version numbers from this book blindly.
Table of Contents
How to Use This Book
The Core Philosophy
The SDLC Operating Model
The AI Agent Mental Model
The Source-of-Truth Hierarchy
Product Discovery Before Coding
The Grill-Me Skill
Product Context and Product Specification
Project Terminology
Requirements, Scope, Non-Goals, and Acceptance Criteria
Technology Freshness and Current-Stack Research
Environment and Developer Machine Setup
Git, GitHub, Identity, and Repository Governance
Repository Bootstrap and Structure
The Agent Constitution: AGENTS.md
Rules, Skills, References, and Progressive Disclosure
The AI Agent Operating Protocol
Architecture and Module Boundaries
Collaborative Development Without Team Chaos
Independent Workspaces and Worktrees
Contract-First and Dependency-Ready Development
Task Packets and Change Packets
Collaboration for Teams with Unequal Skill Levels
Design Philosophy and Product Feel
Design Tokens
AI-Generated HQ UI Mockups
Mockup Refinement, Approval, and Reference Tiers
UI Foundation and Component Laboratory
Application Shell and Scaffold
UI Implementation with Reference Fidelity
UX Psychology, Visual Hierarchy, and Motion
Accessibility and WCAG
Security and OWASP
Data, API, and Integration Contracts
Vertical Delivery and Phase Planning
Testing Strategy
CI/CD and Merge Gates
Release and Deployment Engineering
Production Operations and Incident Response
Dependency Management and Technology Upgrades
Refactoring and Architecture Evolution
AI Review and Independent Verification
Metrics and Engineering Health
Master Prompt Library
Master Templates
Project Completion Checklist
Final Operating Rules
Appendix: Current-Technology Research Sources
1. How to Use This Book
This handbook is intended to be executed in order. A beginner should not jump directly to the application-feature chapters.
Never skip a phase because "AI can figure it out later."
AI is very useful at implementation, transformation, research, analysis, testing, and iteration. It is not a substitute for establishing the project's source of truth.
1.2 Phase gates
Every phase has:
Inputs
Work
Outputs
Verification
Exit criteria
If the exit criteria are not met, the phase is not complete.
Do not build detailed pages before the design system exists.
Do not build dependent APIs before the contract is stable.
Do not release before CI is enforcing the quality checks.
Do not make destructive production changes without rollback planning.
4. The AI Agent Mental Model
An AI coding agent generally combines:
text
Instructions
+ Context
+ Tools
+ Model reasoning
+ Repository state
+ Feedback
Your repository therefore needs to become self-describing.
4.1 What the agent knows
The agent may have access to:
system instructions
repository instructions
task prompt
selected files
search results
tool outputs
images/screenshots
skills
existing code
test failures
4.2 What the agent does not automatically guarantee
The agent does not automatically guarantee that it will:
read every line of every document
invoke every available skill
use current APIs
reproduce a screenshot exactly
recognize every security issue
prefer your architecture over patterns it sees elsewhere
notice that a package is outdated
preserve every design constraint
Therefore the workflow must make these actions visible and verifiable.
4.3 Context selection is a project concern
If the agent receives only part of a large document, important rules may never become active context.
Use:
text
docs/INDEX.md
with a trigger map:
text
Task type Read these first
-------------------------------------------------------
UI design + UX + motion + UI refs
API architecture + contracts + security
Database architecture + data model + migration policy
Authentication security + architecture + contracts
Production bug operations + architecture + incident process
Dependency update technology policy + dependency policy
This is better than one giant document.
4.4 Progressive disclosure
Keep high-priority instructions small. Put detail into references and skills. Current agent-skill guidance recommends concise skill bodies and moving detailed material into referenced resources; it also recommends clear trigger descriptions and deterministic scripts when exact behavior matters.
5. The Source-of-Truth Hierarchy
Use this hierarchy consistently.
text
1. Explicit product requirements
2. Approved product decisions
3. Approved design references
4. Current official technology documentation
5. Project architecture
6. Project design system
7. Canonical implementation examples
8. External standards
9. General model knowledge
10. AI preference / aesthetic intuition
5.1 Domain-specific authority
Different decisions have different sources of truth.
text
Product behavior → Product Spec
Terminology → Product Terminology
Visual appearance → Approved Design Reference
Exact tokens → Design Tokens
Architecture → Architecture document + ADRs
API boundary → API Contract
Database structure → Data Model + migrations
Security → Security Policy + automated checks
Accessibility → Accessibility Policy + tests
Current API syntax → Official current docs
5.2 Conflict rule
If a lower-priority source conflicts with a higher-priority source, the higher-priority source wins unless an explicit architectural decision changes it.
This is a reusable AI skill for requirements discovery.
7.1 Mission
The skill must continuously question the user until the requirements are implementation-ready or every remaining unknown is explicitly accepted as risk.
7.2 Behaviour rules
The skill must:
ask one useful cluster of questions at a time
challenge vague assumptions
detect contradictions
revisit previous decisions when new information conflicts
distinguish fact, requirement, preference, assumption, constraint, decision, and risk
maintain an unresolved list
never silently invent business rules
refuse to declare the specification final while material unknowns remain
7.3 Exact prompt: start the Grill-Me process
text
You are the Product Discovery and Specification Interviewer.
Your job is NOT to code, architect, or design the interface yet.
Your job is to interrogate me until the product is sufficiently
specified for implementation.
Be rigorous and persistent. Do not accept vague answers when they
could affect product behavior, architecture, UX, security, data,
permissions, cost, reliability, or future maintenance.
Work through these areas:
1. Product vision
2. Problem statement
3. Target users
4. Secondary users
5. User roles and permissions
6. User environment and devices
7. Jobs-to-be-done
8. Primary user journeys
9. Secondary journeys
10. Core features
11. Non-goals
12. Business rules
13. Data entities
14. Data ownership
15. State transitions
16. Integrations
17. Notifications
18. Search/filter/sort behavior
19. Error behavior
20. Empty/loading/success states
21. Accessibility requirements
22. Security requirements
23. Performance requirements
24. Reliability requirements
25. Analytics requirements
26. Administration
27. Compliance requirements
28. Deployment assumptions
29. Operational requirements
30. Future extensibility
Rules:
- Do not ask everything at once.
- Ask the next most valuable questions.
- When my answer is ambiguous, ask follow-up questions.
- Detect contradictions with earlier answers.
- Tell me when two answers conflict.
- Challenge assumptions respectfully.
- Do not silently decide business behavior for me.
- Maintain an explicit unresolved-question list.
- Maintain an explicit decision log.
- Mark each item as requirement, preference, assumption, constraint,
decision, or risk.
- Continue until all material questions are resolved or explicitly
accepted as risk.
At the end of every round provide only:
1. What is now decided
2. What remains ambiguous
3. The next questions
Do not produce application code during this phase.
Do not declare the process finished prematurely.
7.4 Exact prompt: finalize the discovery
text
You are the Product Specification Finalizer.
Using the completed interview:
1. Check for contradictions.
2. Check for missing material requirements.
3. Check business rules for undefined states.
4. Check roles and permissions for gaps.
5. Check core workflows for missing failure paths.
6. Check data ownership and lifecycle.
7. Check integrations and external dependencies.
8. Check non-functional requirements.
9. Check accessibility and security.
10. Check operational requirements.
Classify every statement as:
- requirement
- preference
- assumption
- constraint
- decision
- risk
- non-goal
Do not silently fill gaps.
If material unknowns remain, output an unresolved-question list and
STOP before finalization.
If complete, generate:
- 00-project-context.md
- 01-product-spec.md
- 02-product-terminology.md
- ADR candidates
- acceptance-criteria summary
- open-risk register
Then run a consistency audit across all generated documents.
8. Product Context and Product Specification
8.1 00-project-context.md
Use this structure:
markdown
# Project Context
## Product
## One-Sentence Definition
## Why It Exists
## Problem
## Primary Users
## Secondary Users
## User Environment
## Product Personality
## Desired Feel
## Must Never Feel Like
## Core User Jobs
## Primary Workflows
## Business Context
## Competitive Context
## Non-Goals
## Constraints
## Success Definition
## Known Risks
Terminology drift is a major source of AI-generated architecture problems.
Create:
text
docs/02-product-terminology.md
For every project-specific term document:
text
Term
Market meaning
Our project meaning
Why this meaning is used
Example
Non-example
Related terms
9.1 Recommended core glossary
Define at minimum:
text
Module
Feature
Capability
Component
Primitive
Pattern
Shell
Scaffold
Controller
Service
Repository
Use Case
Adapter
Contract
Provider
Integration
Reference
Token
Skill
Rule
Decision
ADR
Source of Truth
Task Packet
Change Packet
Dependency
Hotspot
Release
Incident
9.2 Example conventions
text
Module
= a bounded business capability with owned code/data behavior.
Feature
= a user-visible or business-visible capability inside a module.
Controller
= transport/interface layer; does not contain business rules.
Service
= business/application behavior; does not directly manage HTTP concerns.
Repository
= persistence boundary; does not decide product policy.
Primitive
= low-level reusable UI behavior.
Component
= reusable user-interface implementation.
Shell
= shared frame around a class of pages.
Reference
= approved visual source used to evaluate implementation fidelity.
These are project conventions, not claims that every company uses the terms identically.
10. Requirements, Scope, Non-Goals, and Acceptance Criteria
10.1 Requirement quality
Every important requirement should answer:
text
Who?
What?
Why?
When?
What is success?
What is failure?
What is the edge case?
Every major phase should include explicit non-goals.
This prevents AI agents from expanding scope automatically.
11. Technology Freshness and Current-Stack Research
This is a mandatory gate before framework/package decisions.
11.1 The technology rule
Choose the latest stable, production-supported, officially recommended option that is compatible with the project.
11.2 Never use model memory for current versions
For current versions, breaking changes, package APIs, CLI syntax, support status, and security advisories, the agent must consult current official sources.
11.3 Technology Audit Record
Create:
text
docs/03-technology-policy.md
Recommended table:
Area
Selected
Stable?
Supported?
Official source
Breaking changes checked?
Reason
Runtime
TBD
Package manager
TBD
Frontend framework
TBD
Backend framework
TBD
Database
TBD
ORM/data layer
TBD
Validation
TBD
Testing
TBD
UI primitives
TBD
CI platform
TBD
11.4 Exact technology-research prompt
text
You are the project's Technology Researcher and Upgrade Analyst.
Your task is to determine the current production-safe technology
baseline for this project.
Do not rely on model memory for anything that can change.
For every major technology or dependency:
1. Identify the currently supported stable release.
2. Verify official support or LTS status.
3. Read the official installation documentation.
4. Read official migration/breaking-change documentation.
5. Identify deprecated APIs.
6. Identify the current recommended architecture.
7. Identify official security guidance.
8. Identify runtime compatibility requirements.
9. Determine whether the newest release is stable, RC, beta, canary,
nightly, or experimental.
10. Determine whether the project should use it now.
11. Record the exact official sources.
12. Record known migration work.
13. Record upgrade risk.
Do not choose a dependency merely because its version number is higher.
Prefer the latest stable, production-supported, officially recommended
version compatible with the project.
Output:
- Technology Decision Record for every major dependency
- baseline version table
- deprecated-pattern blacklist
- upgrade watchlist
- unresolved compatibility questions
Do not modify application code during this phase.
11.5 Technology adapter principle
The book intentionally does not hard-code one framework stack into the methodology.
Instead define a technology adapter:
text
Technology Adapter
├── CLI initialization command
├── version pinning mechanism
├── folder conventions
├── build command
├── test command
├── lint command
├── type-check command
├── local development command
├── database migration command
├── production build command
├── deployment command
└── official documentation links
At project start, AI generates this adapter from current official documentation.
12. Environment and Developer Machine Setup
This is not Docker-specific.
Every contributor needs an independently reproducible local environment.
12.1 Required categories
text
Operating system
Shell
Git
Runtime
Package manager/build tool
Project CLI(s)
Editor/IDE
GitHub/GitLab/etc. CLI if used
Credential manager
Environment variable strategy
Optional database client
Optional API testing client
12.2 Version pinning
Use repository-visible version metadata appropriate to the ecosystem:
text
runtime version file
package-manager version field
lockfile
CLI/version notes
Never rely only on:
text
"Install whatever is newest"
12.3 Exact setup-audit prompt
text
Act as the Developer Environment Engineer.
Inspect the target operating system and repository requirements.
Determine:
- required runtime
- exact supported runtime line
- package manager
- required CLI tools
- optional tools
- authentication requirements
- environment variables
- local service requirements
- database requirements
- test prerequisites
- browser prerequisites
Research current official installation instructions for every tool
that has version-sensitive installation steps.
Then produce a beginner-safe setup guide with:
1. exact installation commands
2. verification commands
3. expected output
4. common failure modes
5. troubleshooting
6. repository setup commands
7. first successful test
Do not assume Docker.
Do not assume a specific operating system unless detected.
Do not install unnecessary global packages.
12.4 Environment verification script
Create a repository command such as:
text
setup doctor
that checks:
text
runtime version
package manager version
Git
CLI tools
environment files
required ports/services
lockfile integrity
basic build
The exact implementation depends on the chosen stack.
13. Git, GitHub, Identity, and Repository Governance
13.1 Identity setup
Every contributor should verify:
text
git config user.name
git config user.email
Use organization-approved email/identity policy.
13.2 Repository governance
Recommended:
text
protected main
PR required
required CI checks
required review(s)
CODEOWNERS where useful
secret scanning
dependency/security checks
merge queue where appropriate
14.1 Do not create a folder because a tutorial has one
Every folder needs a responsibility.
14.2 Exact repository-bootstrap prompt
text
You are the Repository Bootstrap Engineer.
Use the approved Product Context, Product Specification, Technology
Policy, and Architecture decision.
Before changing files:
1. Read docs/INDEX.md if it exists.
2. Read the relevant architecture documents.
3. Verify the technology baseline against current official sources.
4. Generate the repository using the current official CLI for the
selected technology.
5. Use only supported stable options.
6. Avoid unnecessary default dependencies.
7. Establish version pinning.
8. Establish the canonical folder structure.
9. Establish baseline scripts for format, lint, typecheck, test,
build, and verification.
10. Add initial agent documentation.
11. Run every baseline check.
12. Confirm the repository is clean and reproducible.
Do not implement product features.
Do not invent architecture.
Do not add dependencies without a documented reason.
Output:
- files created
- tools installed
- versions selected
- verification results
- known follow-up tasks
15. The Agent Constitution: AGENTS.md
15.1 Purpose
AGENTS.md should be the project's compact operating constitution.
Keep it focused. Your preferred target of roughly 100–150 lines is reasonable.
# Project Agent Constitution
## Role
Act as a senior product engineer working inside this repository.
You are responsible for producing maintainable, secure, accessible,
tested, current, and product-consistent changes.
## Mission
Implement the requested product outcome while preserving:
- product requirements
- approved architecture
- design system
- security boundaries
- accessibility requirements
- repository conventions
## Non-Negotiables
1. Read relevant project documentation before implementation.
2. Read and use the applicable skill for the task.
3. Use current official technology documentation when APIs or versions
may have changed.
4. Never introduce deprecated patterns when a supported replacement exists.
5. Do not invent architecture when an established project pattern exists.
6. Do not invent UI patterns that conflict with approved references or design tokens.
7. Do not add dependencies without a concrete need and recorded decision.
8. Do not change unrelated files.
9. Do not bypass validation, authorization, or security checks.
10. Do not claim work is complete without verification.
## Source of Truth
Product → docs/01-product-spec.md
Terminology → docs/02-product-terminology.md
Technology → docs/03-technology-policy.md
Architecture → docs/04-architecture.md
Design → docs/05-design-philosophy.md + docs/06-design-tokens.md
UX → docs/07-ux-principles.md
Motion → docs/08-motion-principles.md
Security → docs/09-security-policy.md
Data → docs/10-data-model.md
API → docs/11-api-contracts.md
Testing → docs/12-testing-strategy.md
Deployment → docs/13-deployment.md
Operations → docs/14-production-operations.md
Dependencies → docs/15-dependency-policy.md
Collaboration → docs/16-contribution-model.md
## Working Method
1. Understand the requested outcome.
2. Identify affected module(s).
3. Read the smallest relevant context set.
4. Inspect canonical examples.
5. Check dependencies and contracts.
6. State the implementation plan before large changes.
7. Implement only the necessary scope.
8. Validate continuously.
9. Review the diff.
10. Run required checks.
11. Report evidence of completion.
## UI Rules
- Reference images are visual source of truth.
- Do not redesign approved references.
- Use project design tokens.
- Preserve visual hierarchy.
- Preserve product-specific feel.
- Do not introduce generic AI aesthetics.
- Do not introduce unapproved colours, gradients, or decorations.
- Motion must communicate purpose and respect reduced-motion preferences.
## Engineering Rules
- Follow module boundaries.
- Keep transport, business logic, and persistence responsibilities separate.
- Prefer explicit, boring, maintainable code over clever code.
- Use current supported APIs.
- Keep types/contracts explicit.
- Validate untrusted input.
- Enforce authorization at the correct trust boundary.
## Verification
Before completion, run the relevant:
- formatter
- linter
- typecheck/compiler
- unit/integration tests
- build
- E2E tests
- accessibility checks
- security checks
- browser/visual checks
## Completion
A task is complete only when its acceptance criteria are satisfied and
verification evidence exists.
15.5 Important rule
The placeholder above is a template, not a universal final file. Replace links, commands, terminology, and architecture with project-specific values.
16. Rules, Skills, References, and Progressive Disclosure
---
name: ui-implementation
description: Implements approved UI references using project tokens,
canonical components, responsive rules, accessibility requirements,
and browser-based visual verification. Use for new UI screens,
complex UI modifications, and reference-image replication.
---
# Purpose
...
# When to use
...
# Inputs
...
# Required workflow
...
# Verification
...
# Failure conditions
...
Current OpenAI skill guidance recommends a concise skill body, clear metadata, and progressive disclosure for detailed references/scripts. Adapt the exact skill packaging to the target agent/IDE.
Act as the implementation engineer for this repository.
TASK:
[task]
Before editing:
1. Read the relevant project context.
2. Read the relevant rules and skills.
3. Inspect existing implementations.
4. Identify the module boundary.
5. Check current dependencies and contracts.
6. Identify shared-file hotspots.
7. Identify tests required.
8. Identify security/accessibility implications.
9. If UI is involved, inspect all relevant approved references.
Then produce:
- understanding
- scope
- assumptions
- dependencies
- implementation plan
- verification plan
During implementation:
- modify only the required scope
- reuse canonical patterns
- follow project naming
- avoid deprecated APIs
- avoid unnecessary abstractions
- avoid unnecessary dependencies
- preserve unrelated behaviour
After implementation:
1. Run focused tests.
2. Run relevant quality checks.
3. Review the diff.
4. Search for accidental unrelated changes.
5. Verify acceptance criteria.
6. Provide evidence.
If a requirement conflicts with repository rules, STOP and explain the
conflict before choosing a new convention.
18. Architecture and Module Boundaries
18.1 Architecture must be explicit
Create:
text
docs/04-architecture.md
Include:
text
system boundaries
applications/services
modules
responsibilities
data flow
trust boundaries
integration boundaries
shared packages
error strategy
logging strategy
configuration
When change B depends on change A, use a stacked branch/PR strategy rather than waiting unnecessarily or creating giant branches.
GitHub's current stacked pull request documentation describes stacks as dependent PR chains where each layer can be reviewed separately; GitHub also documents merge-queue support for stacks. Availability and exact UI/CLI behavior may change because stacked PRs are currently documented as public preview.
19.5 Do not promise zero merge conflicts
A real engineering system cannot guarantee zero conflicts.
The goal is:
Minimize collision probability and make integration cheap and predictable.
20. Independent Workspaces and Worktrees
This does not require Docker.
A developer/agent can work in an independent Git worktree.
Git officially supports multiple working trees attached to a repository.
When possible, consumers can begin against the stable contract without waiting for the final implementation.
21.4 Shared hotspot list
Identify early:
text
root package manifest
lockfile
CI workflows
global configuration
base styles/tokens
database schema
migration folder
main routing registry
shared API contract
AGENTS.md
Assign a single active writer or controlled integration window for high-collision artifacts.
22. Task Packets and Change Packets
The task packet is the fundamental unit of collaborative work.
22.1 YAML template
yaml
task_id: AUTH-023
title: Add refresh-token rotation
objective: >
Implement secure refresh-token rotation according to the authentication policy.
context:
- docs/09-security-policy.md
- docs/11-api-contracts.md
depends_on:
- AUTH-021
produces:
- auth refresh endpoint
- token rotation service
allowed_paths:
- modules/auth/**
- tests/auth/**
forbidden_paths:
- design/**
- unrelated modules
contracts:
reads:
- AuthSession
changes:
- RefreshTokenResponse
dependencies:
add: []
update: []
database_impact:
- none
api_impact:
- POST /auth/refresh
security_impact:
- session security
accessibility_impact: none
tests:
- unit
- integration
- E2E
acceptance_criteria:
- old refresh token is invalidated after rotation
- replay attempts are rejected
risk: high
integration_notes: >
Shared auth contract must remain backwards compatible during rollout.
22.2 Why this scales
A developer with less context gets a precise boundary.
An experienced developer can work faster because the intent is explicit.
An AI agent can operate with less ambiguity.
A reviewer can understand the intended change without reading the entire repository.
23. Collaboration for Teams with Unequal Skill Levels
The project can explicitly prohibit things such as:
text
unapproved purple/violet/indigo identity
AI sparkle/magic-wand imagery
neural-network decoration
arbitrary gradients
glassmorphism
random floating blobs
excessive pill controls
excessive cards
gradient text
unnecessary shadows
meaningless animation
invented decorative elements
Do not use this exact list automatically for every product. Keep only prohibitions that match the actual product philosophy.
25. Design Tokens
Create:
text
docs/06-design-tokens.md
design/tokens source files
a working design-token page
25.1 Token groups
text
color
font family
font size
line height
font weight
spacing
radius
border
shadow/elevation
motion duration
motion easing
breakpoints
content width
layer/z-index
25.2 CSS-first principle
For CSS styling, prefer the project's canonical CSS/Tailwind/design-token mechanism rather than moving all styling into JavaScript/TypeScript objects.
Use objects in TypeScript for data/configuration/variants where appropriate, not as a blanket replacement for CSS.
25.3 Token page
Create a real page that visibly demonstrates:
text
colors
typography
spacing
radii
buttons
forms
cards
navigation
states
motion
responsive behavior
The token page is an executable visual reference.
26. AI-Generated HQ UI Mockups
This is a full engineering phase, not an optional artistic exercise.
Communicates realistic layout and product behavior.
Canonical reference
Approved visual authority for implementation.
26.3 Do not generate "a modern website"
Use product context.
Required prompt inputs
text
product
users
context
primary task
content structure
visual personality
colour system
typography
spacing
component language
density
responsive target
anti-patterns
reference images
26.4 Visual direction prompt
text
You are the visual art director and senior product designer for a real
production product.
Do not start by creating a random "modern website".
First explore distinct visual directions that emerge from the product.
PRODUCT:
[product]
DOMAIN:
[domain]
PRIMARY USERS:
[users]
PRIMARY USER GOAL:
[goal]
CORE CONTEXT:
[context]
PRODUCT PERSONALITY:
[4–6 adjectives]
THE PRODUCT SHOULD FEEL LIKE:
[description]
THE PRODUCT MUST NOT FEEL LIKE:
[description]
EXPLORE 4 DISTINCT DESIGN DIRECTIONS.
Each direction must meaningfully differ in:
- typography
- composition
- density
- component geometry
- navigation treatment
- colour relationships
- imagery
- hierarchy
Do not produce four minor color variants.
For each direction explain:
1. design philosophy
2. emotional impression
3. typography strategy
4. color strategy
5. layout strategy
6. component strategy
7. information density
8. navigation strategy
9. motion philosophy
10. strengths
11. risks
12. fit for this product
Avoid generic AI/SaaS aesthetics, invented visual decoration, and
trend-driven effects unless justified by the product context.
26.5 HQ screen generation master prompt
text
You are a senior product designer and visual art director.
Generate a HIGH-FIDELITY UI REFERENCE MOCKUP for a real production
product.
This is NOT an inspiration image.
This is NOT a Dribbble concept.
This is NOT a generic SaaS template.
This image will be handed to a frontend engineer as a visual reference.
PRODUCT
Name: [name]
Purpose: [purpose]
Domain: [domain]
Primary users: [users]
User context: [context]
Primary task: [task]
SCREEN
Name: [screen]
Purpose: [purpose]
Viewport: [desktop/tablet/mobile]
INFORMATION ARCHITECTURE
[exact content/sections/components]
CONTENT
Use believable domain-specific content.
Avoid lorem ipsum and meaningless placeholder labels.
DESIGN SYSTEM
Typography: [typography]
Primary colors: [tokens]
Surface colors: [tokens]
Spacing philosophy: [description]
Radius: [description]
Elevation: [description]
Iconography: [description]
VISUAL DIRECTION
[approved direction]
VISUAL HIERARCHY
Establish a clearly identifiable primary objective and primary action.
Use scale, whitespace, grouping, contrast, and alignment to establish
hierarchy.
Do not make everything visually loud.
PRODUCT CONTEXT
The screen should feel specific to [domain/product].
Do not make it look like an interchangeable template.
UX PRINCIPLES
- recognition over recall
- predictable navigation
- progressive disclosure
- obvious primary action
- meaningful feedback
- error prevention
- clear grouping
- appropriate information density
ACCESSIBILITY
Design toward WCAG 2.2 AA.
Use readable type, sufficient contrast, understandable controls, and
states that do not rely on color alone.
MOTION INTENT
The composition should support purposeful transitions for state change,
feedback, and spatial relationships. Do not add animation for spectacle.
ANTI-PATTERNS — DO NOT USE UNLESS EXPLICITLY PRESENT IN THE APPROVED DESIGN:
- generic AI visual language
- purple/violet/indigo branding
- AI sparkles
- magic-wand imagery
- neural-network decoration
- arbitrary gradients
- glassmorphism
- neon glow
- floating decorative blobs
- excessive pills
- excessive cards
- gradient text
- random 3D objects
- decorative elements without product purpose
REFERENCE IMAGES
Use attached approved references as constraints.
Preserve their applicable hierarchy, spacing rhythm, typography
relationship, component language, and composition.
FINAL REQUIREMENT
The result must feel like a real product used by real people.
Prioritize product clarity, hierarchy, usability, consistency,
accessibility, and implementation realism over visual spectacle.
26.6 Landing page prompt
text
Using the approved product context and visual direction, generate a
high-fidelity landing-page reference for [PRODUCT].
Required structure:
- navigation
- hero
- primary CTA
- secondary action if justified
- trust/social proof if appropriate
- product explanation
- key workflows or benefits
- evidence
- final CTA
- footer
Do not invent sections merely to fill space.
The page must tell the product story in a deliberate hierarchy.
The reference is for implementation, so use realistic spacing,
content density, typography, and component dimensions.
Generate desktop first at a realistic large desktop viewport.
26.7 Application-shell prompt
text
Generate a high-fidelity application-shell reference for [PRODUCT].
The shell must establish:
- application navigation
- sidebar/topbar behavior
- page header
- breadcrumbs when justified
- primary actions
- account/user control
- notifications/status
- content container
- responsive transformation
Do not decorate the shell unnecessarily.
The shell must support long-term product usage and high information
clarity rather than looking like a marketing hero.
26.8 Dense information screen prompt
text
Generate a high-fidelity information-dense screen for [PRODUCT].
The screen must demonstrate how the design system behaves under high
content density.
Include only information that real users need.
Show:
- clear page purpose
- meaningful filtering/search where necessary
- table/list/card density appropriate to the domain
- status representation
- sorting/pagination when justified
- empty/loading/error considerations
Avoid dashboard-widget soup.
Avoid decorative charts without decision value.
Preserve visual hierarchy even under density.
26.9 Workflow/form screen prompt
text
Generate a high-fidelity workflow/form screen for [PRODUCT].
The user must have a clear sense of:
1. where they are
2. what they need to do
3. what information is required
4. what will happen next
5. how to recover from mistakes
Design realistic validation, help text, grouping, progressive disclosure,
and confirmation behavior.
Do not create a form that looks like a generic component-library demo.
26.10 Mobile prompt
text
Using the approved desktop reference, generate the corresponding mobile
reference.
Do not simply shrink the desktop screen.
Preserve the same design language and information hierarchy while
adapting:
- navigation
- stacking
- content density
- touch targets
- typography scale
- action placement
- tables/lists where appropriate
- dialogs/drawers
Do not invent a separate visual identity for mobile.
27. Mockup Refinement, Approval, and Reference Tiers
27.1 Generate directions first
Create 3–5 different visual directions.
Select one.
27.2 Generate the design-system reference
Show the component language before generating every page.
27.3 Recommended reference set
For a substantial web product, start with approximately:
Act as an independent senior product-design reviewer.
Review the attached proposed UI references against the product context,
UX requirements, design philosophy, tokens, and anti-patterns.
Do not immediately redesign them.
First identify:
1. product-context mismatch
2. visual hierarchy problems
3. usability problems
4. accessibility risks
5. inconsistent components
6. unnecessary decoration
7. generic AI-generated patterns
8. information-density problems
9. responsive risks
10. implementation risks
11. brand/visual-language drift
For each issue report:
- severity
- location
- problem
- why it matters
- correction recommendation
Do not praise the design without concrete evidence.
Do not introduce aesthetic preferences that conflict with the approved
product direction.
default
hover
focus
active
disabled
loading
error
success
selected
empty
28.3 Component lab prompt
text
Using the approved design direction and design tokens, create a
high-fidelity component reference system.
The components must all belong to one coherent visual language.
Include:
- typography hierarchy
- buttons
- icon buttons
- inputs
- search
- select
- checkbox
- radio
- switch
- tabs
- cards
- tables
- pagination
- tooltip
- dropdown
- dialog
- alert
- toast
- breadcrumbs
- navigation
- loading
- empty
- error
- success
For interactive components show:
default, hover, focus, active, disabled, loading, error, success,
selected where relevant.
Use realistic domain-specific content.
Do not invent a new visual style for individual components.
Do not rely on generic UI-library defaults.
Do not add visual effects merely to look modern.
29. Application Shell and Scaffold
Follow your intended sequence:
text
Design Tokens
↓
Component Lab
↓
Marketing Shell
↓
Application Shell
↓
Demo Navigation
↓
System States
↓
Real Product Pages
Top navigation or application header
Sidebar/drawer if appropriate
Breadcrumbs if appropriate
Page header
Primary actions
Notifications
Account control
Main content
29.3 Scaffold definition
A scaffold is:
Stable page structure and integration surfaces without pretending that final content/design decisions are complete.
Do not call unfinished UI "production-ready".
30. UI Implementation with Reference Fidelity
30.1 Reference fidelity rule
The reference is not inspiration.
It is the visual source of truth for that screen.
The agent may improve:
semantics
accessibility
responsive adaptation
performance
implementation architecture
It must not casually redesign:
hierarchy
composition
spacing language
typography relationship
component geometry
visual identity
30.2 Exact UI implementation prompt
text
You are the UI implementation engineer.
The attached reference is the authoritative visual specification for
this screen.
DO NOT redesign it.
DO NOT reinterpret it as inspiration.
Before editing:
1. Read the product context.
2. Read design philosophy.
3. Read design tokens.
4. Read UX and motion principles.
5. Inspect the existing component library.
6. Inspect canonical examples.
7. Inspect all related reference images.
8. Determine desktop/mobile requirements.
Implementation rules:
- reuse canonical components
- use design tokens
- follow project architecture
- preserve visual hierarchy
- preserve density and spacing rhythm
- avoid generic AI/SaaS aesthetics
- do not invent decorations
- do not add unapproved colors or gradients
- do not add unnecessary animation
- preserve accessibility
Verification:
1. Run the application.
2. Render the route in a real browser.
3. Capture the required viewport screenshot.
4. Compare it against the reference.
5. Record visual discrepancies.
6. Fix the highest-severity discrepancies first.
7. Repeat until the visual acceptance gate passes.
8. Run accessibility checks.
9. Run required tests.
10. Run lint/typecheck/build.
Do not claim completion based on code inspection alone.
31. UX Psychology, Visual Hierarchy, and Motion
31.1 Visual hierarchy
Every screen should answer:
text
What is the primary purpose?
What should the user notice first?
What is the primary action?
What information supports it?
What can be de-emphasized?
Use:
scale
contrast
whitespace
alignment
grouping
density
position
Do not make everything visually prominent.
31.2 UX principles to teach the AI
Useful heuristics include:
text
recognition over recall
progressive disclosure
choice reduction
error prevention
clear feedback
user control
consistency
proximity
alignment
information scent
predictability
Treat laws such as Hick's or Fitts's as heuristics, not mathematical design commands.
31.3 Motion
Create:
text
docs/08-motion-principles.md
Motion should communicate:
text
continuity
state change
feedback
spatial relationship
progress
orientation
Avoid animation merely to demonstrate animation ability.
Always consider reduced-motion preferences.
31.4 Motion review prompt
text
Review this interaction design as a motion and UX specialist.
For every animation/transition determine:
1. what information it communicates
2. whether it improves comprehension
3. whether it is necessary
4. whether duration/easing is appropriate
5. whether it creates distraction
6. how reduced-motion users experience it
Recommend removal when motion has no functional purpose.
32. Accessibility and WCAG
Use current W3C guidance. WCAG 2.2 is the current W3C Recommendation.
32.1 Accessibility target
Default product target:
WCAG 2.2 AA, unless the product specification requires a stricter standard.
Act as the Accessibility Engineer.
Audit the implementation against WCAG 2.2 AA.
Check:
- semantics
- keyboard access
- focus order
- visible focus
- labels
- errors
- instructions
- contrast
- non-text content
- status messages
- reflow
- motion
- reduced motion
- responsive behaviour
Use automated checks where possible, but do not treat automation as
proof of complete accessibility.
For each issue provide:
- criterion/area
- severity
- user impact
- location
- correction
- verification method
Do not change unrelated behaviour.
33. Security and OWASP
Use current OWASP guidance rather than an old memorized checklist.
OWASP Top 10:2025 is the current major Top 10 awareness document as of this handbook's current date.
Its 2025 categories include:
text
A01 Broken Access Control
A02 Security Misconfiguration
A03 Software Supply Chain Failures
A04 Cryptographic Failures
A05 Injection
A06 Insecure Design
A07 Authentication Failures
A08 Software or Data Integrity Failures
A09 Security Logging & Alerting Failures
A10 Mishandling of Exceptional Conditions
Act as the security reviewer.
Review this change against the project's security policy and current
OWASP guidance.
Check:
- authentication
- authorization
- input validation
- injection
- access control
- secrets
- session/token handling
- file handling
- network boundaries
- error handling
- logging/alerting
- dependency/supply-chain risk
- data integrity
- abuse/rate limiting
For every finding provide:
severity
exploit scenario
affected boundary
recommended mitigation
required regression test
Do not declare the code safe merely because a linter passes.
Consumers should depend on an explicit contract, not undocumented behaviour.
34.4 API implementation prompt
text
Implement this API change from the approved contract.
Before coding:
- read the API contract
- read architecture
- read security policy
- inspect existing patterns
- inspect tests
Implementation constraints:
- validate all untrusted input
- enforce authorization at the server boundary
- preserve documented response shapes
- return documented error shapes
- avoid leaking internal details
- avoid unrelated changes
After coding:
- unit test business logic
- integration test the endpoint
- test unauthorized/forbidden cases
- test validation failures
- test important edge cases
- run the full relevant quality gates
35. Vertical Delivery and Phase Planning
The project should be broken into dependency-aware slices, not blindly feature-based or frontend/backend-only.
when the work does not actually require that sequence.
35.3 Phase-planning prompt
text
You are the Project Planner.
Using the final Product Specification, Architecture, Design System,
and Technology Policy:
1. Build the dependency graph of the complete product.
2. Identify foundational work.
3. Identify parallelizable work.
4. Identify shared-file hotspots.
5. Identify integration points.
6. Identify work that blocks other work.
7. Identify work that can use contracts before implementation exists.
8. Identify testing requirements per phase.
9. Identify production-risk work.
10. Minimize critical-path length without creating unsafe coupling.
For every phase provide:
- objective
- prerequisites
- outputs
- tasks
- parallel tasks
- blocking dependencies
- hotspots
- risks
- acceptance criteria
- exit gate
Do not organize phases purely by department.
Do not create artificial phases merely because a technology has its own
folder.
36. Testing Strategy
Create:
text
docs/12-testing-strategy.md
36.1 Test layers
text
Unit
↓
Integration
↓
Contract
↓
End-to-End
↓
Accessibility
↓
Visual
↓
Production verification
36.2 Unit tests
Use for:
pure business rules
utilities
validation logic
transformations
36.3 Integration tests
Use for:
database interaction
API behavior
authentication boundaries
repository/service integration
36.4 Contract tests
Use for:
producer/consumer compatibility
API schemas
external integrations
36.5 E2E tests
Test critical user journeys.
Do not reproduce every unit test at E2E level.
36.6 Visual tests
For approved references:
text
reference.png
↕
browser screenshot
36.7 Testing prompt
text
Act as the test engineer.
Based on the task acceptance criteria, determine the minimum complete
test set.
Classify tests as:
- unit
- integration
- contract
- E2E
- accessibility
- visual
Test:
- happy path
- validation failures
- permission failures
- important edge cases
- state transitions
- regression risks
Avoid redundant tests that verify the same thing at every layer.
Implement the tests and run them.
Report exact results.
37. CI/CD and Merge Gates
CI must run from the beginning, not after the application "works."
A merge must not depend on the author's statement that:
"It works locally."
37.3 CI prompt
text
Act as the CI/CD engineer.
Inspect the repository and current technology baseline.
Create or improve CI so every change is evaluated consistently.
Required categories:
- dependency integrity
- formatting
- lint
- type/build verification
- tests
- contract checks
- E2E smoke tests
- accessibility where appropriate
- security/dependency checks
Requirements:
- fail fast on invalid prerequisites
- use pinned/appropriate action/tool versions
- avoid silently ignoring test failures
- avoid leaking secrets
- preserve useful logs
- make critical failures visible
Document which checks are required for merge.
37.4 Merge queue
For a busy repository, a merge queue can reduce the risk that a pull request passes in isolation but breaks when integrated with newer changes. GitHub documents merge queues for this purpose.
38. Release and Deployment Engineering
38.1 Environment progression
text
Local
↓
CI
↓
Preview / Test
↓
Staging
↓
Production
38.2 Release gate
Before production:
text
requirements ✓
CI ✓
review ✓
security ✓
accessibility ✓
E2E ✓
visual QA ✓
migration plan ✓
rollback plan ✓
monitoring ✓
38.3 Deployment prompt
text
Act as the Release Engineer.
Prepare this change for production.
Check:
1. version/release identity
2. dependency state
3. build artifact
4. database migrations
5. backward compatibility
6. environment variables
7. secrets
8. health checks
9. monitoring
10. rollback path
11. smoke tests
12. post-deploy verification
Do not perform destructive production changes without an explicit
approved migration and rollback strategy.
Output a release checklist and deployment sequence.
P0 — catastrophic / data loss / major security event
P1 — critical functionality unavailable
P2 — important degradation
P3 — minor defect
P4 — cosmetic / improvement
Customize definitions to your organization.
39.3 Production debugging prompt
text
You are the Production Incident Engineer.
Do not immediately rewrite code.
First:
1. Identify the exact symptom.
2. Identify affected users/functions.
3. Identify first known occurrence.
4. Inspect recent deploys.
5. Inspect recent dependency/config changes.
6. Inspect logs, metrics, traces, and errors.
7. Reproduce safely.
8. Establish the smallest plausible root cause.
9. Determine containment and rollback options.
10. Propose the smallest safe mitigation.
11. Add a regression test.
12. Verify in a safe environment.
13. Deploy the fix through the release process.
14. Verify production.
15. Document the root cause and prevention.
Rules:
- do not modify unrelated code
- do not hide uncertainty
- do not claim resolution without evidence
- prefer containment over risky broad changes
40. Dependency Management and Technology Upgrades
The product must stay current over time.
40.1 Dependency categories
text
security update
patch
minor
major
runtime/framework
architecture-affecting
breaking
40.2 Dependency lane
Create a dedicated maintenance workflow:
text
Observe
↓
Research
↓
Classify
↓
Prepare
↓
Upgrade
↓
Test
↓
Staging
↓
Production
40.3 Prevent dependency drift
Do not allow each feature branch to update packages independently.
Use:
text
golden dependency baseline
lockfile discipline
dependency update lane
automated maintenance tool where appropriate
40.4 Dependency update prompt
text
Act as the Dependency Upgrade Engineer.
For the requested dependency update:
1. inspect the currently installed version
2. identify current stable production-supported release
3. inspect official release notes
4. inspect breaking changes
5. inspect migration guide
6. inspect security advisories
7. inspect compatibility requirements
8. identify affected project code
9. create a minimal upgrade plan
10. upgrade in an isolated change
11. run all relevant tests
12. verify build
13. review lockfile changes
14. document follow-up work
Do not upgrade unrelated dependencies merely because updates are available.
41. Refactoring and Architecture Evolution
Never refactor solely because AI says the code "could be cleaner."
41.1 Refactor triggers
measurable defect
performance issue
repeated maintenance cost
boundary violation
security requirement
deprecated platform API
dependency migration
clear duplication with stable semantics
41.2 Refactor prompt
text
Act as the Refactoring Engineer.
First establish:
- what problem the refactor solves
- measurable evidence
- affected boundary
- risk
- expected benefit
Do not change behaviour unless explicitly required.
Plan:
1. tests protecting current behaviour
2. smallest viable structural change
3. migration steps
4. validation
5. rollback/revert path
Avoid broad cleanup unrelated to the objective.
42. AI Review and Independent Verification
The implementation agent should not be the only judge of its own work.
You are an independent reviewer.
Review the change without assuming the implementation is correct.
Read:
- task packet
- acceptance criteria
- relevant architecture
- relevant design references
- diff
- tests
Check:
- missing requirements
- architecture violations
- incorrect assumptions
- security problems
- accessibility problems
- outdated APIs
- unnecessary dependencies
- unrelated edits
- insufficient tests
- UI drift
- operational risk
Classify findings:
BLOCKER
HIGH
MEDIUM
LOW
A BLOCKER means the change should not merge.
Do not rewrite the feature during review unless specifically requested.
42.3 Review independence
The reviewer can be:
a human
another AI session
a separate agent
a different model
For high-risk changes, prefer a reviewer independent from the original implementation context.
43. Metrics and Engineering Health
Track simple metrics.
Delivery
text
lead time
PR size
review time
deployment frequency
change failure rate
conflict frequency
hotspot collisions
blocked tasks
dependency waiting time
stack depth
AI quality
text
number of out-of-scope edits
number of invalid assumptions
number of review corrections
number of obsolete API uses
number of visual-QA iterations
Do not optimize a metric simply because it is easy to count. Use metrics to find process problems.
44. Master Prompt Library
This chapter is intended as the copy/paste command center.
44.1 Project starter
text
Start a new product using the AI-Native Product Engineering workflow.
Do not write product code yet.
Step 1: determine whether product discovery is complete.
Step 2: if not complete, start the Grill-Me process.
Step 3: finalize the product specification.
Step 4: create the terminology glossary.
Step 5: perform the current technology audit.
Step 6: create the architecture proposal.
Step 7: create the documentation index.
Step 8: create the initial AGENTS.md.
Step 9: create the skill map.
Step 10: identify required design documents.
Stop after the planning gate.
Do not silently choose unresolved product decisions.
44.2 Context loading prompt
text
Before changing code, determine the minimum complete context set for
this task.
List:
- required project documents
- applicable rules
- applicable skills
- canonical examples
- references
- contracts
- tests
Read them before implementation.
Report what you read.
44.3 Current-API research prompt
text
Before using this technology/API:
1. identify installed version
2. consult current official docs
3. consult current migration/deprecation docs
4. identify supported API
5. identify legacy API
6. confirm compatibility
Do not use model memory when an official source is available.
44.4 Full-project planning prompt
text
Act as the Principal Product Engineer.
Given the finalized product specification, design system, technology
policy, and architecture:
Produce the complete phased implementation plan.
The plan must:
- minimize critical-path length
- minimize shared-file collisions
- minimize dependency waiting
- support parallel contributors
- support unequal developer skill levels
- establish contracts before consumers when possible
- keep main releasable
- include tests in every phase
- include security/accessibility work where applicable
- include CI/CD from the beginning
- include production-readiness milestones
For every phase provide:
- objective
- prerequisites
- tasks
- parallel tasks
- dependency graph
- shared hotspots
- allowed paths
- outputs
- acceptance criteria
- verification
- exit gate
44.5 Task creation prompt
text
Convert this requested outcome into an implementation-ready task packet.
Include:
- task ID
- objective
- context
- dependencies
- outputs
- allowed paths
- forbidden paths
- contracts
- dependency changes
- database changes
- UI changes
- security impact
- accessibility impact
- test requirements
- acceptance criteria
- risk
- integration notes
Do not split the task merely by frontend/backend.
Split it at stable responsibility and contract boundaries.
44.6 Start-task prompt
text
Execute this task packet.
Do not begin by editing.
First verify:
- dependencies are ready
- contract is available
- relevant docs are present
- skill is applicable
- allowed paths are clear
- shared hotspots are understood
Then plan, implement, test, review, and report evidence.
44.7 Review-before-merge prompt
text
Review the change as an independent gatekeeper.
Reject it if:
- acceptance criteria are missing
- required tests are missing
- current APIs were not verified when necessary
- security boundary is incorrect
- accessibility requirements are ignored
- visual reference is materially different
- unrelated files changed
- project conventions were broken without an ADR
- CI evidence is incomplete
44.8 Final project audit prompt
text
Perform a complete production-readiness audit.
Review:
Product
Requirements
Terminology
Architecture
Dependencies
Agent rules
Skills
Design system
UI references
UX
Accessibility
Security
Data
API contracts
Testing
CI/CD
Deployment
Monitoring
Rollback
Documentation
Collaboration workflow
Identify:
- blockers
- high-risk gaps
- outdated technology
- contradictory documentation
- untested critical paths
- unverified UI
- operational weaknesses
Do not claim production readiness unless every blocker is resolved.
45. Master Templates
45.1 docs/INDEX.md
markdown
# Documentation Index
## Read for every task
- AGENTS.md
- this index
## Product
- 00-project-context.md
- 01-product-spec.md
- 02-product-terminology.md
## Technology
- 03-technology-policy.md
## Architecture
- 04-architecture.md
- adr/
## Design
- 05-design-philosophy.md
- 06-design-tokens.md
- 07-ux-principles.md
- 08-motion-principles.md
- design/references/
## Security
- 09-security-policy.md
## Data / API
- 10-data-model.md
- 11-api-contracts.md
## Quality
- 12-testing-strategy.md
## Delivery
- 13-deployment.md
- 14-production-operations.md
- 15-dependency-policy.md
- 16-contribution-model.md
45.2 Definition of Ready
markdown
# Definition of Ready
A task is ready only when:
- objective is explicit
- acceptance criteria exist
- dependencies are identified
- contracts are available or intentionally part of the task
- allowed paths are known
- shared hotspots are known
- required references are identified
- security impact is known
- accessibility impact is known
- test strategy is known
45.3 Definition of Done
markdown
# Definition of Done
[ ] Product requirement satisfied
[ ] Acceptance criteria satisfied
[ ] Correct module/architecture used
[ ] Current APIs verified where necessary
[ ] No deprecated pattern introduced
[ ] Naming conventions followed
[ ] Existing canonical components reused
[ ] Design tokens used
[ ] Reference fidelity verified where applicable
[ ] Responsive behaviour verified
[ ] Accessibility checked
[ ] Security checked
[ ] Tests added/updated
[ ] Type/build checks pass
[ ] Lint/format checks pass
[ ] Diff reviewed
[ ] No unrelated changes
[ ] Documentation updated
[ ] CI green
[ ] Release/operational impact assessed
When using a specific framework, runtime, database, testing tool, or CLI:
Search the official project site.
Read the release/support page.
Read installation/CLI documentation.
Read migration/breaking changes.
Read security advisories.
Record the selected baseline.
Do not treat this appendix as a substitute for a current audit.
One-Page Beginner Execution Map
When starting a completely new project, execute this list in order.
text
01 Create a private project workspace/repository.
02 Install Git and the approved developer tooling.
03 Run the Environment Setup AI prompt.
04 Start the Grill-Me prompt.
05 Continue until requirements are internally consistent.
06 Run the Product Specification Finalizer.
07 Review and approve product docs.
08 Run the Technology Freshness Audit.
09 Approve the stable production-safe stack.
10 Run the Repository Bootstrap prompt.
11 Create docs/INDEX.md.
12 Create AGENTS.md.
13 Create skills and scoped rules.
14 Create architecture + ADR structure.
15 Create contribution/worktree policy.
16 Create design philosophy.
17 Create design tokens.
18 Build the token page.
19 Build the component laboratory.
20 Generate 3–5 visual directions.
21 Select one direction.
22 Generate 8–10 high-fidelity reference images.
23 Review and revise references.
24 Approve Tier-1 references.
25 Build marketing/application shells.
26 Establish API/data contracts.
27 Prepare shared dependencies.
28 Create task packets from the dependency graph.
29 Assign independent workspaces.
30 Implement in small, reviewable changes.
31 Test continuously.
32 Run visual QA for reference-backed screens.
33 Run security and accessibility audits.
34 Keep CI green.
35 Integrate through PRs/merge queue/stacks as appropriate.
36 Deploy to staging.
37 Run release verification.
38 Deploy production.
39 Monitor.
40 Use the production incident workflow for failures.
41 Maintain dependencies.
42 Re-run the technology audit periodically.
Closing Principle
The goal is not to make the AI "smart enough" to build everything without supervision.
The goal is to make the engineering environment clear enough, structured enough, and verifiable enough that a capable human or AI can work inside it safely.
A good AI-native repository should make the next action obvious to a beginner, the intended boundaries obvious to a senior developer, and the verification requirements obvious to every AI agent.
That is the objective of this handbook.
49. The AI-IDE Adapter Layer
The methodology is universal, but AI coding products expose instructions and skills through different mechanisms.
Do not guess the current mechanism from memory.
At the beginning of a project, ask the AI to inspect the current official documentation for the IDE/agent being used and generate a project adapter.
49.1 Universal agent contract
Every supported agent should receive the same conceptual information:
text
ROLE
MISSION
SOURCE OF TRUTH
NON-NEGOTIABLES
DOCUMENT INDEX
SKILL INDEX
WORKFLOW
COMMANDS
VERIFICATION
STOP CONDITIONS
DONE CRITERIA
49.2 Agent adapter prompt
text
You are the AI-Development-Environment Adapter Engineer.
The project uses the following agent/IDE:
[AGENT_OR_IDE]
Do not rely on memory for current configuration conventions.
Consult the agent/IDE's current official documentation.
Determine:
1. repository instruction file format
2. scoped rule mechanism
3. skill mechanism
4. skill discovery/invocation behaviour
5. project-level versus user-level instructions
6. image/reference support
7. browser/computer-use support
8. shell/tool permissions
9. context/retrieval behavior relevant to project instructions
10. recommended repository structure for agent instructions
Then create the smallest adapter necessary to expose this project's
AI-Native Product Engineering system to the chosen agent.
Requirements:
- keep AGENTS.md as the conceptual cross-agent constitution
- do not duplicate long documentation unnecessarily
- point to canonical project documents
- expose relevant skills using the IDE's supported mechanism
- preserve the same source-of-truth hierarchy
- preserve the same Definition of Done
- preserve the same security boundaries
Do not change application code.
Output:
- adapter files
- their purpose
- how the agent loads them
- how to invoke each major skill
- how to verify the adapter is working
49.3 Adapter verification prompt
text
Verify that the current AI IDE is actually loading the project's agent
instructions and exposing the intended skills.
Perform a non-destructive verification.
Determine:
- which project instructions were loaded
- which relevant skill metadata was available
- which references were read
- which commands are available
- whether the definition of done is visible
Do not modify production code.
Report any missing context or unsupported capability.
50. The Project Context Pack
Every serious task should have a small context pack.
This is the answer to the problem:
"The project has excellent documentation, but the AI did not read all of it."
Build the minimum complete context set for this task.
Do not read the entire repository blindly.
Do not rely on memory.
Identify:
- governing documents
- task-specific documents
- relevant architecture
- relevant design references
- relevant contracts
- canonical files
- applicable skills
- required scripts/checks
Then read them before implementation.
At the beginning of the implementation response, report:
"Context loaded: ..."
Do not begin code changes until all required context has been loaded.
50.4 Why this works
It balances two risks:
text
Too little context → wrong implementation
Too much context → noise/context pressure
The goal is not "more context".
The goal is complete relevant context.
51. The Project State Ledger
AI agents can lose track of what has already been decided across sessions.
Create:
text
docs/PROJECT_STATE.md
Keep it short.
markdown
# Project State
## Current Phase
P07 — Event Registration
## Last Completed Gate
G6 — Contract Gate
## Active Work
- EVT-031
- EVT-032
## Blocked Work
- EVT-033 — waiting for external provider contract
## Current Technology Baseline
See docs/03-technology-policy.md
## Current Design Baseline
See docs/05-design-philosophy.md
## Active Risks
- ...
## Important Recent Decisions
- ADR-0012
- ADR-0013
The state ledger should not duplicate the specification. It should answer only:
Where are we now?
52. The Planning Board for AI Agents
A project plan should exist in a machine-readable form.
The machine-readable version makes it easier for AI agents to identify:
what can be worked on now
what is blocked
what should not be modified
what depends on another task
53. The Change Graph
Before assigning many tasks, build a dependency graph.
Example:
text
PRODUCT DECISION
│
▼
API CONTRACT
/ \
/ \
▼ ▼
DOMAIN A DOMAIN B
│ │
▼ ▼
API A API B
│ │
┌──┴──┐ ┌──┴──┐
▼ ▼ ▼ ▼
UI A E2E A UI B E2E B
Tasks at the same level can often be parallelized.
Tasks crossing a contract boundary need a defined dependency.
53.1 Dependency graph prompt
text
Build the complete change dependency graph for the project.
For each planned change determine:
- prerequisites
- produced artifacts/contracts
- consumers
- shared-file hotspots
- whether it can run in parallel
- whether it should be stacked on another change
- whether a mock/stub/contract is sufficient to unblock consumers
Optimize for:
- minimal critical path
- minimal shared-file collisions
- minimal waiting
- small reviewable changes
- stable main branch
Do not create parallelism where it would create hidden coupling.
54. Dependency Readiness Windows
A major source of team slowdown is discovering a required dependency after development has already started.
selected
version
support status
reason
migration impact
54.2 Shared dependency policy
Only a designated dependency change may modify the shared dependency baseline during a planning window unless the change is urgent and explicitly coordinated.
This dramatically reduces lockfile collisions.
54.3 Dependency freeze window
For high-concurrency integration phases, consider:
text
T-2 days: dependency preparation
T-1 day: baseline verified
T0: feature work starts
T+N: dependency changes reopened through dedicated PRs
The exact duration depends on the product.
55. Hotspot Ownership Protocol
Some files naturally create conflicts.
Create:
text
docs/HOTSPOTS.md
Example:
Path
Reason
Default owner
Change protocol
root manifest
dependency collision
integrator
dedicated dependency PR
lockfile
generated shared state
integrator
never hand-merge casually
DB schema
migration collision
data owner
integration window
CI workflows
deployment risk
release owner
review required
global tokens
UI collision
design-system owner
design-system PR
AGENTS.md
agent behavior
project maintainer
reviewed change
This does not mean one person permanently owns everything.
It means there is a known coordination protocol.
56. Merge-Conflict Prevention Protocol
Before starting a task, the agent checks:
text
1. What files will I modify?
2. Which are hotspots?
3. Who else is changing them?
4. Can I avoid them?
5. Can I move the shared change into a smaller prerequisite PR?
6. Can I consume an existing contract instead?
56.1 Exact prompt
text
Before implementation, perform a collision-risk analysis.
Identify:
- files I am likely to modify
- shared/hotspot files
- concurrent tasks affecting those files
- potential dependency conflicts
- potential migration conflicts
For each risk propose:
- avoid
- coordinate
- split
- stack
- schedule
Do not proceed with a high-collision change until the integration
strategy is explicit.
57. The Integration Packet
When a change is ready, provide the integrator with:
Prepare this completed task for another engineer/agent to integrate.
Provide:
1. what changed
2. why it changed
3. files changed
4. contracts changed
5. dependencies changed
6. database changes
7. test evidence
8. security evidence
9. accessibility evidence
10. visual evidence
11. known risks
12. follow-up work
13. any rebase/integration considerations
Do not include unrelated implementation commentary.
59. Recovering From an AI Agent That Violates Rules
Analyze why the previous implementation violated the project rules.
Do not fix the code yet.
Determine whether the failure originated from:
1. missing context
2. ambiguous instruction
3. unavailable skill
4. incorrect skill selection
5. outdated documentation
6. conflicting existing code
7. missing automated enforcement
8. insufficient verification
9. unclear ownership
10. incorrect task scope
For each root cause propose a SYSTEM-LEVEL prevention.
Prefer improving the workflow over merely correcting the one instance.
This turns an AI failure into a process improvement instead of repeatedly fixing the same symptom.
60. The Rule-to-Enforcement Matrix
Every important rule should be classified.
Rule
AI guidance
Deterministic check
Human review
naming
yes
often
sometimes
formatting
no/brief
yes
no
type safety
brief
yes
sometimes
auth
yes
partial
yes
authorization
yes
partial
yes
WCAG
yes
partial
yes
visual fidelity
yes
partial
yes
API contract
yes
yes
yes
dependency policy
yes
partial
yes
branch policy
no/brief
yes
no
business rules
yes
tests
yes
The point is to identify what remains dependent on human/AI judgment.
61. The Anti-Hallucination Protocol for Code
Before implementation:
text
Evidence
↓
Decision
↓
Implementation
Avoid:
text
Assumption
↓
Code
↓
Discover later
61.1 Prompt
text
For every non-trivial implementation decision, distinguish:
FACT — verified from repository or authoritative source
ASSUMPTION — not verified
DECISION — selected project choice
UNKNOWN — requires clarification/research
Do not present assumptions as facts.
When an unknown could materially affect correctness, security,
architecture, or data, stop and research or request resolution.
62. The Beginner's First 24 Hours
A new beginner should follow this schedule conceptually, without rushing.
Hour 1–2: product
text
Grill-Me
Hour 2–4: specification
text
Product Context
Product Spec
Terminology
Hour 4–5: technology
text
Technology Audit
Hour 5–6: architecture
text
Architecture
ADR
Hour 6–7: repository
text
Bootstrap
Git
CI baseline
Hour 7–8: agent system
text
AGENTS.md
rules
skills
context index
Remaining setup time
text
Design philosophy
Tokens
UI lab
reference generation plan
Do not rush into business features merely because the repository now runs.
63. The First Working Vertical Slice
After the foundation, choose one meaningful end-to-end path.
It should demonstrate:
text
UI
↓
validation
↓
API
↓
business logic
↓
data
↓
response
↓
UI state
↓
tests
This proves the architecture before the team builds dozens of dependent features.
Exact prompt
text
Select the smallest meaningful end-to-end vertical slice that tests
our architecture.
It must exercise:
- UI
- validation
- API
- domain/business logic
- persistence
- error handling
- accessibility
- tests
It should expose architectural problems early.
Do not choose a trivial hello-world flow.
Do not choose the largest feature.
64. The Golden Path Example
The project should maintain at least one canonical implementation for:
text
one read flow
one write flow
one authenticated flow
one authorized flow
one form
one data-heavy screen
one tested API module
one database migration
These become references for future agents.
Instead of writing another 200 lines of instructions, tell the agent:
text
Follow the architecture of:
[path]
Canonical examples are especially powerful because they show how the project's rules actually interact.
Use this when the page structure is already decided.
text
Generate a high-fidelity visual reference for exactly this page.
DO NOT invent the page structure.
DO NOT add sections.
DO NOT remove sections.
PRODUCT:
[product]
USER:
[user]
JOB TO BE DONE:
[job]
PAGE:
[page]
EXACT PAGE STRUCTURE:
1. [section]
2. [section]
3. [section]
4. [section]
PRIMARY ACTION:
[action]
SECONDARY ACTIONS:
[actions]
CONTENT PRIORITY:
1. [highest]
2. [next]
3. [supporting]
DESIGN SYSTEM:
[approved tokens and component language]
REFERENCE STYLE:
[approved visual direction]
VIEWPORT:
[viewport]
Produce a realistic production interface with believable domain
content. Preserve hierarchy, spacing rhythm, proportions, and visual
relationships.
Do not introduce generic AI aesthetics, unapproved gradients,
unapproved colors, meaningless decorative elements, or unrelated UI.
68. UI Mockup Prompt: Exact Reference Refinement
Use after generating a first draft.
text
Refine this existing UI reference rather than generating a different
visual concept.
Preserve the approved:
- layout
- visual language
- typography relationship
- color system
- component geometry
- content hierarchy
Correct only:
[list exact problems]
Do not introduce:
- new decorative elements
- new color families
- random gradients
- AI visual motifs
- new layout sections
The goal is controlled refinement, not reinterpretation.
69. UI Mockup Prompt: Comparative Design Direction
Use when deciding between two candidate directions.
text
Compare these two proposed visual directions for the same product.
Do not choose based on generic "modernity" or visual impressiveness.
Evaluate:
- product-context fit
- user trust
- cognitive load
- information hierarchy
- information density
- brand distinctiveness
- accessibility
- long-term maintainability
- responsiveness
- implementation complexity
Recommend one and explain why.
70. UI Mockup Prompt: Product Feel Audit
text
Review this UI without discussing code.
Answer:
1. What kind of product does this look like?
2. Who appears to use it?
3. What is the user's primary goal?
4. What feels trustworthy?
5. What feels generic?
6. What feels decorative rather than useful?
7. What looks AI-generated?
8. What does not match the intended product context?
9. Where is visual hierarchy weak?
10. What would make this feel like a real product rather than a mockup?
Do not redesign yet.
71. UI Mockup Prompt: Anti-AI-Aesthetic Audit
text
Perform an adversarial visual audit specifically for unwanted
AI-generated design patterns.
Flag:
- generic AI startup aesthetics
- purple/indigo default palettes
- sparkle/magic-wand motifs
- artificial glows
- arbitrary gradients
- futuristic decoration
- glassmorphism without product purpose
- floating blobs
- generic SaaS card grids
- meaningless charts
- excessive pills
- excessive rounded containers
- decorative 3D objects
- gradient text
- visual noise
For every finding explain why it is inappropriate for the product
context.
Do not introduce replacement decoration unless the product context
requires it.
72. Browser Visual-Verification Procedure
For each Tier-1 reference:
text
1. Build
2. Start application
3. Navigate to route
4. Set viewport
5. Wait for stable render
6. Capture screenshot
7. Compare against reference
8. Record differences
9. Fix
10. Repeat
Is the code maintainable and consistent with the architecture?
74. The Complete Feature Protocol
Every product feature follows:
text
1. Understand
2. Specify
3. Contract
4. Design
5. Prepare dependencies
6. Implement
7. Unit test
8. Integration test
9. E2E test
10. Accessibility
11. Security
12. Visual QA if applicable
13. Independent review
14. CI
15. Integration
16. Staging
17. Production
18. Observe
Not every trivial change requires every expensive step, but the task must explicitly classify which gates apply.
75. Risk-Based Verification
Do not treat all changes equally.
Low risk
Examples:
text
typo
copy change
documentation
May need:
text
lint/build
Medium risk
Examples:
text
UI component
business logic
API response
Needs:
text
tests
review
possibly visual/a11y
High risk
Examples:
text
auth
authorization
payments
migrations
secrets
security configuration
production infrastructure
Needs:
text
deep review
security checks
regression tests
staging verification
rollback plan
76. Exact Prompt: Risk Classification
text
Classify this change by risk.
Consider:
- user impact
- data impact
- security impact
- financial impact
- operational impact
- reversibility
- shared-file collision risk
- migration risk
- dependency risk
Return:
- risk level
- reasons
- required verification gates
- required reviewer type
- rollback strategy
77. CI Failure Debugging
When CI fails, do not ask:
"Can you make CI green?"
Ask:
text
Why did CI fail?
Exact prompt
text
Act as the CI failure investigator.
Inspect the failure.
Determine:
1. first failing check
2. root cause
3. whether failure is deterministic or flaky
4. whether code, environment, dependency, or CI configuration caused it
5. whether the change should actually be modified
Do not weaken or disable the failing check merely to make CI green.
Fix the root cause and preserve the intent of the check.
78. Flaky-Test Protocol
A flaky test is not a successful test.
Workflow:
text
Detect
↓
Reproduce repeatedly
↓
Classify source
↓
Fix determinism
↓
Run repeated verification
↓
Document if infrastructure-related
Never normalize flaky tests by retrying forever.
Retries can be a temporary containment mechanism, not the final solution.
79. Production Observability Baseline
A production product needs to answer:
text
Is it healthy?
Who is affected?
What failed?
When did it start?
What changed?
Can we reproduce it?
Can we roll back?
At minimum consider:
text
application errors
request latency
availability
background job failures
database health
resource saturation
critical business events
security alerts
Exact tooling is selected during the technology audit.
80. Production Health Checks
A deployed service should expose appropriate health/readiness signals where the hosting model supports them.
Health should distinguish:
text
process is running
from:
text
service is actually ready to serve traffic
Do not report healthy merely because the process exists.
81. Release Rollback Protocol
Every release should answer:
text
How do we undo application code?
How do we undo configuration?
How do we handle database changes?
How do we disable the feature?
How do we verify rollback?
variable name
purpose
required/optional
where configured
rotation procedure
Never document secret values.
84. Security Incident Prompt
text
Treat this as a potential security incident.
Do not immediately patch and close it.
First determine:
- affected asset
- affected users
- attack surface
- possible exposure
- whether exploitation is ongoing
- containment options
- credentials/tokens that may require rotation
- data that may be affected
Then:
1. contain
2. preserve useful evidence
3. patch
4. invalidate compromised credentials where appropriate
5. test
6. deploy
7. verify
8. document
Do not expose sensitive incident details in public logs or commits.
85. Data-Migration Runbook
For any significant production data migration:
text
1. define source data
2. define target state
3. estimate volume
4. estimate duration
5. identify locking/downtime risk
6. design backward compatibility
7. test against production-like data
8. define observability
9. define rollback/remediation
10. run staging rehearsal
11. execute
12. verify counts/invariants
13. monitor application behavior
14. complete contract phase
AI migration prompt
text
Act as the database migration engineer.
Before writing a migration:
- inspect current schema
- inspect application consumers
- inspect existing migrations
- identify backward compatibility requirements
- estimate destructive risk
- identify data transformation needs
- define verification queries/checks
- define rollback or remediation strategy
Prefer expand/migrate/contract for changes that require compatibility.
Do not generate a destructive production migration solely from the
requested end state.
86. Production Bug Knowledge Base
Every meaningful incident should generate a short knowledge record:
An AI session should never require the next session to reconstruct everything from chat history.
Before ending a substantial task, create:
text
docs/handoffs/HANDOFF-XXXX.md
Template:
markdown
# Handoff
## Task
## Current State
## Completed
## Not Completed
## Decisions
## Files Changed
## Remaining Issues
## Tests
## Known Risks
## Next Exact Step
Exact handoff prompt
text
Prepare a concise machine-readable handoff for the next engineer or AI agent.
Include:
- current phase
- task state
- files changed
- decisions
- tests run
- failures remaining
- blockers
- known risks
- next exact step
Do not assume the next agent has access to this conversation.
88. The "Never Guess" Escalation Rules
The agent should continue autonomously when the choice is low-risk and local.
It should stop or escalate when the decision can materially affect:
text
business behaviour
security
data loss
production availability
architecture
public API compatibility
user privacy
billing
legal/compliance requirements
This is better than "always ask for confirmation" because excessive confirmation destroys productivity.
88.1 Exact escalation prompt
text
Use autonomous judgment for reversible, low-risk implementation details.
Escalate before making an irreversible or materially product-affecting
choice when the requirement is ambiguous.
Always escalate uncertainty involving:
- security boundaries
- destructive data changes
- incompatible public API changes
- production infrastructure
- secrets/credentials
- unresolved business rules
- significant design-direction changes
89. The Complete Project Orchestration Prompt
This is the closest thing in the book to a "start the entire methodology" command.
text
You are the Principal AI Product Engineering Orchestrator.
You are responsible for guiding this project through the complete SDLC.
IMPORTANT:
Do not jump directly into feature implementation.
Do not rely on model memory for current technology facts.
Do not declare work complete without verification.
Do not invent unresolved product decisions.
Do not override approved design references.
Do not introduce generic AI aesthetics.
Do not modify unrelated files.
OPERATING MODEL
Product truth:
- product context
- product specification
- terminology
Technology truth:
- technology policy
- official current documentation
Architecture truth:
- architecture
- ADRs
- canonical examples
Design truth:
- design philosophy
- design tokens
- approved references
Quality truth:
- testing strategy
- security policy
- accessibility requirements
- CI gates
OPERATING SEQUENCE
0. Confirm current project state.
1. Determine whether product discovery is complete.
2. If not complete, invoke the Grill-Me process.
3. Finalize product documentation.
4. Audit terminology and contradictions.
5. Research the current production-safe technology baseline.
6. Finalize architecture and ADRs.
7. Bootstrap the repository using current official CLIs.
8. Create the agent constitution and skill system.
9. Create the design philosophy and token system.
10. Generate and approve HQ reference directions.
11. Build the component laboratory.
12. Build application/marketing shells.
13. Establish contracts and dependency baseline.
14. Build the complete dependency-aware work graph.
15. Generate implementation-ready task packets.
16. Execute tasks in independent workspaces.
17. Verify continuously.
18. Integrate through small reviewable changes.
19. Run CI gates.
20. Deploy to staging.
21. Run release checks.
22. Deploy production.
23. Verify production.
24. Monitor and maintain.
25. Run dependency/technology refreshes periodically.
AT EVERY PHASE
- identify source of truth
- identify dependencies
- identify shared hotspots
- identify risk
- define acceptance criteria
- define verification
- record important decisions
If the project is not ready for the next phase, explain exactly what
is missing and continue from the current gate rather than skipping ahead.
90. The New-Project Checklist to Give to Any AI
Paste this at the beginning of a new AI conversation if the repository already contains the handbook.
text
This repository follows the AI-Native Product Engineering handbook.
Your first task is NOT to code.
Read:
- AGENTS.md
- docs/INDEX.md
- docs/PROJECT_STATE.md if present
Then determine the current SDLC gate.
Report:
1. current phase
2. completed gates
3. active blockers
4. relevant documents
5. applicable skills
6. next exact action
Do not skip gates.
Do not invent missing requirements.
91. Recommended Repository Automation
The methodology becomes much stronger when the repository has simple helper commands.
Suggested conceptual command set:
text
project doctor
project verify
project test
project lint
project typecheck
project build
project context
project status
project task validate
project visual-check
project security-check
project a11y-check
project dependency-audit
Exact implementation depends on the technology stack.
The important principle is one obvious command per recurring verification activity.
92. Repository `README.md` for Beginners
The README should not become a giant architecture essay.
It should answer:
text
What is this?
How do I set it up?
How do I run it?
How do I verify it?
Where are the docs?
How do I start a task?
How do I contribute?
Suggested sections:
markdown
# Project
## What This Is
## Quick Start
## Environment
## Development
## Verification
## Documentation
## Contribution
## Support / Troubleshooting
93. Contribution Workflow for a Beginner
A beginner should not need to understand the entire architecture before making a small change.
Their workflow:
text
1. Read README
2. Read AGENTS.md
3. Read docs/INDEX.md
4. Pick an assigned task
5. Read task packet
6. Create worktree/branch
7. Run project doctor
8. Implement scoped change
9. Run focused checks
10. Run full required checks
11. Open PR
12. Fix review feedback
13. Merge
14. Delete worktree
These ten questions catch a surprising amount of drift.
95. The Architecture Drift Audit
Run periodically.
text
Are modules still respected?
Are shared folders becoming junk drawers?
Are controllers doing business logic?
Are repositories making business decisions?
Are UI components bypassing the design system?
Are packages crossing boundaries incorrectly?
Are deprecated APIs appearing?
Are duplicate patterns emerging?
Are task changes becoming too large?
Exact prompt
text
Perform an architecture-drift audit.
Compare the current implementation against the approved architecture
and canonical examples.
Identify:
- boundary violations
- duplicate patterns
- new competing abstractions
- misplaced files
- dependency-direction violations
- deprecated patterns
- growing shared/junk folders
- UI system bypasses
Do not refactor automatically.
Produce a prioritized remediation plan.
runtime status
framework status
dependency updates
support/LTS changes
deprecations
security advisories
breaking changes
build tooling
CI actions
browser support
Prompt
text
Perform a Technology Drift Audit using current official sources.
Do not upgrade automatically.
Identify:
- packages behind supported stable versions
- deprecated APIs
- end-of-life runtime/tooling
- security advisories
- upcoming breaking changes
- recommended migrations
- experimental dependencies accidentally used in production
Classify each finding:
security / urgent / scheduled / optional.
98. The Final Launch Audit
The launch audit should be adversarial.
text
Assume the project is NOT ready.
Try to prove it.
Prompt:
text
Act as the independent launch-readiness reviewer.
Try to prove that this project should NOT ship.
Inspect:
- requirements
- critical user flows
- permissions
- security
- accessibility
- performance
- dependencies
- migrations
- monitoring
- rollback
- CI
- staging verification
- visual references
- documentation
- production configuration
Find the smallest number of high-impact blockers that could make the
release fail or harm users.
Do not praise the project.
Do not redesign unrelated areas.
If no blockers remain, provide evidence for each major launch gate.
99. Teaching the AI to Explain Its Work to Beginners
For beginner collaboration, AI output should not assume unexplained expertise.
Require:
text
What changed?
Why?
Where?
How to run it?
How to test it?
How to verify it visually?
What can go wrong?
This makes AI a teaching aid as well as an implementation engine.
Prompt
text
Explain this completed change to a beginner without hiding technical
accuracy.
Use:
- what
- why
- where
- how
- verification
- common failure
Do not use unexplained jargon.
Do not omit important caveats.
100. What "Perfectly Scalable" Actually Means
The handbook should never promise impossible guarantees.
A scalable engineering process means:
text
adding developers does not require proportional chaos
adding features does not require rewriting conventions
adding agents does not require re-teaching the project
upgrading dependencies does not require random breakage
new contributors can discover how the system works
production incidents have a repeatable response
It does not mean:
text
zero conflicts
zero bugs
zero downtime
zero human review
zero future migration work
The goal is not perfection of outcome.
The goal is predictability of process and containment of failure.
101. The Complete Book-to-Project Mapping
A beginner using this handbook should create the following artifacts in order:
Understand before building.
Specify before implementing.
Research before selecting current technology.
Design the system before designing pages.
Generate references from product context.
Treat approved references as visual truth.
Use tokens instead of arbitrary styling.
Use canonical code instead of reinvention.
Use modules instead of folder chaos.
Use contracts before dependent work.
Use independent workspaces for independent changes.
Coordinate hotspots deliberately.
Prepare dependencies before parallel development.
Test at the correct layer.
Automate what machines can enforce.
Review what requires human judgment.
Never call unverified work complete.
Ship through CI and staging.
Operate production as part of the product.
Learn from every failure.
Keep the technology current through deliberate research.
103. Current Official Reference Notes
The methodology in this book intentionally avoids freezing exact package versions. Current facts should be verified at project start.
Agent and skill guidance
The AGENTS.md convention is intended to communicate repository-level instructions to coding agents.
OpenAI's current public skill-creator guidance emphasizes:
clear skill metadata
a concise skill body
progressive disclosure
separate references/scripts for deeper material
deterministic scripts when exact operations benefit from automation
Git worktrees support multiple working trees attached to a single repository:
https://git-scm.com/docs/git-worktree
GitHub currently documents stacked pull requests and merge queues as mechanisms for handling dependent or high-volume changes. Stacked pull requests are currently documented as public preview, so the exact experience should be re-verified before standardizing on them: