How to organize product context in Worklayer

Use Case: When you need to structure your product knowledge so AI can reference it in every workflow Time to Complete: 15-20 minutes Prerequisites: Workspace set up with Context/ folder created

Quick Answer

In Worklayer, organize product context by creating structured files in Context/Company/ and Context/Product/ that capture your goals, personas, metrics, features, and constraints. Once stored, AI references these files using @ to generate grounded outputs instead of generic content.

Step-by-Step Instructions

Step 1: Create Context Folder Structure

Set up two main folders: Context/Company/ for business context and Context/Product/ for product-specific information.

Example structure:

Context/
├── Company/
│   ├── goals-and-okrs.md
│   ├── constraints.md
│   └── target-segments-and-icp.md
└── Product/
    ├── personas-and-use-cases.md
    ├── product-features.md
    ├── product-metrics-and-funnel.md
    └── user-problems-and-jtbd.md

Step 2: Document Company Context

Create files for company-level information that affects product decisions.

Example: goals-and-okrs.md

# Company Goals and OKRs

## Q1 2026 Goals
1. Validate product-market fit with alpha users
2. Validate willingness to pay and monetization model
3. Start building growth and early revenue pipeline

OKRs

Objective	Key Result	Target	Current	Owner
Validate product	Recruit alpha testers	10+ active users	0	Founder
Validate monetization	Launch pricing page	Paywall live	Not started	Founder

Step 3: Document Product Context

Create files for product-specific information: personas, features, metrics, and problems.

Example: personas-and-use-cases.md

# Personas and Use Cases

## Persona Catalog

Persona	Segment	Primary Goal	Main Friction
Overwhelmed PM	PM at 10-200 employee tech company	Keep product context in one place	Spends 30-60 min/day gathering context
AI-Curious PO	Product Owner using ChatGPT	Use AI without losing context	Copy-pastes context into each chat

Step 4: Keep Context Files Updated

Update context files quarterly or when major changes occur (new goals, new personas, metric shifts).

Tip: Add a "Last Updated" date at the top of each file.

Step 5: Reference Context in Prompts

Use @ to reference context files in your AI prompts.

Example:

Use @Context/Company/goals-and-okrs.md and @Context/Product/personas-and-use-cases.md to draft a PRD for [feature].

Example: End-to-End Workflow

Let's organize context for a product management tool.

Step 1: Create folder structure (shown above)

Step 2: Use AI to populate company context:

Go to worklayer.pro and extract:
- Company goals and current priorities
- Target customer segments
- Key constraints (budget, timeline, team size)

Create Context/Company/goals-and-okrs.md with this information.

Step 3: Document product context:

# Product Features (product-features.md)

## Core Features
- AI chat with workspace file references
- Local file workspace (markdown, code editing)
- Task planner with status management
- MCP integrations (Jira, Slack, Linear)
- Skills and Agents builder

## Positioning
- Local-first PM workspace
- AI-assisted documentation environment
- Bridge between product thinking and task execution

Step 4: Set update schedule:

Review and update context files:
- Monthly: product-features.md (as features ship)
- Quarterly: goals-and-okrs.md, personas-and-use-cases.md
- As needed: constraints.md (when budget/timeline changes)

Step 5: Test by generating a PRD:

Use @Context/Company/goals-and-okrs.md, @Context/Product/personas-and-use-cases.md, and @Context/Product/product-features.md to draft a PRD for "Visual Mode Enhancements."

Result: AI generates a PRD grounded in your actual goals, personas, and features.

Time to organize: 15-20 minutes initially, 5-10 minutes per quarter to update

Tips & Best Practices

Use AI to create initial context: Don't manually type context files. Ask AI to research your product (from website, docs, Jira) and generate context files for you.
Keep files focused: Each file should cover one topic (personas, metrics, goals). Don't create one giant "context.md" file with everything.
Add "Last Updated" dates: Add a date at the top of each file so you know when to refresh stale information.
Reference 2-3 files per prompt: When generating outputs, reference multiple context files (goals + personas + metrics) for richer, more grounded content.
Update quarterly, not daily: Context files capture stable information. Update them quarterly or when major changes occur, not every sprint.

Common Mistakes to Avoid

Creating too many context files: Don't create 15 context files on day one. Start with 3-4 core files (goals, personas, features, metrics) and add more as needed.
Never updating context files: If your goals-and-okrs.md shows last year's goals, AI will generate outputs based on outdated priorities. Update context files quarterly.
Storing tactical information: Don't put sprint-specific tasks or one-time decisions in Context files. Context files should capture stable, long-term product knowledge.