Introduction to Windsurf & AI-Assisted Development
The current generation of AI-assisted coding tools is powerful—but also prone to drifting from your intentions if you don’t actively guide them. Windsurf, an AI-powered code editor, offers some unique advantages over more lightweight autocomplete tools. It combines conversational assistance with the ability to execute commands in your development environment, check results, and iterate. This creates opportunities for rapid prototyping and refactoring—but only if you give it the right guardrails.
Those guardrails come in the form of context. Windsurf performs best when you provide it with structured, explicit documentation that it can repeatedly reference. The Product Requirement Document (PRD) is the most important of these. A good PRD captures your project’s purpose, its functional and non-functional requirements, the constraints you must operate within, and—critically—the patterns you expect to be followed in implementation.
When you connect Windsurf to your PRDs via ChatPRD’s Model Context Protocol (MCP) integration, that document becomes a live source of truth. MCP allows Windsurf to pull the latest PRD content directly from ChatPRD into its context—no manual copy-paste, no risk of referencing an outdated file. This keeps your AI coding assistant aligned with your current requirements at all times.
In short: without a PRD, Windsurf is guessing. With a PRD—and especially with MCP—it’s executing with purpose.
Structuring PRDs for Windsurf
Like any AI coding assistant, Windsurf benefits from documentation that’s predictable, easy to parse, and broken into well-labeled sections. The difference with Windsurf is that it can—and often will—be told to re-read your PRD mid-session. The more structured your PRD, the easier it is for Windsurf to retrieve exactly the section it needs, whether you’re feeding it manually or via MCP.
Recommended PRD structure for Windsurf projects:
Introduction & Vision
- High-level purpose of the product or feature.
- The “why” behind the work.
Problem Statement
- The pain points you are solving.
- Who the target users are and what their needs look like.
Feature Overview
- Summary of the capabilities and scope.
- Boundaries—what is explicitly out of scope.
User Stories & User Flows
- Written in “As a [user], I want [feature], so that [benefit]” format.
- Include diagrams or bullet sequences for key flows.
Technical Requirements
- API contracts, expected data shapes, and any existing services to integrate with.
- Preferred libraries, frameworks, and architectural decisions.
Visual/UX Requirements (for front-end heavy work)
- Layout expectations, responsive breakpoints, brand colors, accessibility targets.
Acceptance Criteria
- Always in bullet form and atomic—one condition per bullet.
- Example: “Form validation triggers on blur for all inputs” or “Mobile layout displays cards in a single column.”
Constraints
- Hard limitations like “must run on Node 18+” or “cannot add new dependencies without approval.”
Architecture & Component Structure
- Directory layout, naming conventions, where tests live, which files own business logic vs. UI rendering.
Testing Requirements
- Whether TDD is required, test coverage minimums, or use of specific frameworks.
Embedding PRDs into Windsurf’s Context Strategy
Windsurf’s AI will forget things mid-session. The trick is to treat every session as a cold start, like the “Memento” analogy from experienced Windsurf users: you wake up with amnesia, and the notes you left yourself yesterday are what make you effective today.
Your PRD is that note. And with ChatPRD MCP, it’s not just a static file—you can make sure Windsurf always reads the most up-to-date PRD from your ChatPRD workspace at the start of each session.
Why it matters:
Without loading your PRD into context, Windsurf will make assumptions. These may be correct at first but will drift over time—especially after several rounds of iteration or bug fixing. That’s when you start seeing inconsistent patterns, overwritten types, or completely replaced modules.
How to implement a PRD-driven context loop with MCP:
Store your PRD in ChatPRD under /Docs/ or /PRDs/feature-name.md.
Connect Windsurf to ChatPRD via MCP so it can fetch the PRD on demand.
Initialization Prompt Example:
I'm working on [project name].
Here are the key docs from ChatPRD:
- Main PRD: @[/Docs/01-PRD.md]
- Feature PRD: @[/Docs/prd-dashboard.md]
- Design System: @[/Docs/design.md]Execution: As you work, reference PRD sections explicitly in prompts. MCP will retrieve them in their current state.
Closure: End sessions by updating PRD sections in ChatPRD with what was completed, any deviations from plan, and “gotchas” discovered.
Using PRDs with Windsurf Rules
Windsurf has a Rules system—Markdown files that define coding conventions, stack choices, and architectural guidelines. Think of Rules as the “how” to your PRD’s “what.”
When used with MCP:
- PRD from ChatPRD = what to build (features, constraints, criteria).
- Windsurf Rules = how to build it (patterns, stack, style, do/don’t lists).
Best practice is to:
- Keep general rules in a project-wide file (e.g.,
/windsurf/rules/general.md). - Keep feature-specific rules alongside that feature’s PRD in
/PRDs. - Keep Rules short enough to remain in context alongside the PRD fetched via MCP.
Leveraging Windsurf’s Context-Aware Capabilities
Windsurf can:
- Search and open files by reference.
- Read linked PRDs from MCP and apply them in code generation.
- Run commands, test results, and adjust output.
When working from a PRD:
- Reference sections directly:
“Implement the ‘Team Invitations’ modal from PRD section 4.2, using Tailwind and Shadcn UI modal component.”
- Limit scope: AI output quality drops if you ask for too much at once.
- Reload PRD context often: MCP makes this a one-line operation.
Interactive Refinement Workflow
A disciplined PRD + MCP + Windsurf session might look like this:
Initialize – Windsurf fetches PRD + Rules from ChatPRD via MCP.
Define Session Scope – “Today: Implement authentication flow from PRD section 5.”
Generate Initial Code – Windsurf scaffolds according to PRD.
Test – Run unit and integration tests (or TDD first if that’s your rule).
Refine – Address failing criteria or missed edge cases.
Document – Update PRD in ChatPRD so MCP feeds the updated version next time.
Commit – Keep commits clean and aligned with documented progress.
Step-by-Step Examples
Example 1: Dashboard Feature
- PRD in ChatPRD: Lists KPI cards, chart components, filter panel.
- Rules: Require React + TypeScript, TanStack Query, Tailwind CSS.
- Prompt: “Build dashboard layout per PRD section 3.1.”
- Result: Base layout, fetch hooks, responsive grid.
- Refine: Add loading states and tooltips per PRD.
- Update PRD in ChatPRD: Document final prop shapes, accepted data formats.
Example 2: Authentication Flow
- PRD in ChatPRD: Covers login, signup, reset password; Zod validation rules.
- Rules: Use React Hook Form, no inline CSS.
- Prompt: “Implement password reset flow from PRD section 5.2.”
- Result: Form, validation schema, API integration.
- Refine: Improve error states for invalid/expired tokens.
- Update PRD: Note that reset link expiry is now 30 minutes (change from original 15).
Common Mistakes & How to Avoid Them
Not Initializing with PRD via MCP → Leads to guesswork and stale requirements.
Fix: Always fetch PRD from ChatPRD at the start.
Overloading Context → Knocks PRD out of memory.
Fix: Load only what you need for the current task.
Vague Criteria → AI fills in blanks unpredictably.
Fix: Make acceptance criteria precise and testable.
Skipping PRD Updates → Causes drift in future sessions.
Fix: Treat PRD as a living document in ChatPRD.
One Big Task → Hard for AI to manage.
Fix: Break into small, testable units.
Conflicting PRD & Rules → Windsurf unsure what to follow.
Fix: Keep them synchronized in ChatPRD and Windsurf.
Final Recommendations
- Structure PRDs for easy reference – Headings, bullets, predictable formatting.
- Store PRDs in ChatPRD and use MCP – Keep Windsurf working from the latest version.
- Pair PRDs with scoped Rules – What + How.
- Work incrementally – One discrete feature at a time.
- Update PRDs continuously – Keep AI and human team aligned.
In conclusion:
A well-crafted, actively maintained PRD—delivered into Windsurf’s context via ChatPRD MCP—transforms the editor from a “sometimes useful” AI into a focused, high-context coding partner. You avoid the chaos of unguided AI output, reduce rework, and maintain a clean, consistent codebase aligned with your original product vision.