Application process documentation (flowchart + sequence diagram): the best language for collaboration with Cursor AI

This is not an exaggeration. In the last ten projects I have used Cursor on, those with well-documented processes saved an average of 60% of development time. The reason is simple: when Cursor understands your application flow, it can accurately generate code that meets your expectations instead of repeatedly guessing your intentions.

I have painfully discovered that using Cursor development without process documentation is like playing the "icebreaker" game - every step forward may hit a wall and require constant adjustment of direction. With process documentation, using Cursor is like driving a high-speed train, unimpeded along the preset track.

Throughout the Cursor development journey, we need to prepare these key documents as the "guidebook" for AI:

✅Product  Requirements Document (PRD) - Tells Cursor "what to do" (completed)
✅Application Process Document - Guides Cursor "how to use" (this is it!)
⬜Front -end Guide - Teach Cursor "what to look like"
⬜Back -end Architecture Document - Standardizes Cursor "how to implement"
⬜Technical Stack Document - Clarifies Cursor "what tools to use"
⬜System Prompt - Fine-tune Cursor "interaction rules"
⬜File Structure Document  - Constrain Cursor "code organization"

Next, let me show you the second key to using Cursor well—the secret of creating application process documentation!

AI programming nightmare without process documentation

I recently guided a beginner to develop a community forum application using Cursor. He excitedly told the AI: "Help me write a posting function" and waited for the magic to happen.

What's the result? Cursor does generate code, but problems arise:

• • AI can post directly, while the product requires a three-step process of "draft-preview-publish"
• • AI does not consider the situation where a post fails to be published, resulting in loss of user data
• • The AI-designed interface does not properly guide users to upload pictures, which is a core requirement
• • The worst part is that after posting successfully, users don’t know where to view their posts

This friend had to modify the prompt words repeatedly and correct the AI's understanding over and over again, and it took him three times as long as originally planned to complete the task. The reason was simple: Cursor did not have a clear posting process as a reference.

When working with Cursor, not having a process document is like driving without navigation. Not only will you take a detour, you may also end up in a dead end. I often tell the team: "Preparing a process document for AI is teaching it to think about your product logic."

Multi-dimensional perspectives on process expression: flow charts, sequence diagrams and UML

The core of application process documentation is user process , and the best way to express the process is to combine several powerful visualization tools: flowcharts , sequence diagrams , and various UML diagrams . It is worth mentioning that Cursor has good support for these diagram types, especially the diagrams created by Mermaid.js syntax.

Flowchart: Navigation map in spatial dimension

The flowchart is like a subway map for AI, showing the spatial relationship between the various pages (stations) and user operations (routes) in the application. It allows AI to understand the structure and navigation path of the entire application at a glance.

For example, when I ask Cursor to implement the "user login function", a clear flowchart can help it understand:

Sequence diagram: Interaction script in the time dimension

The sequence diagram is like an interaction script for AI, which shows the message passing and state changes between users, interfaces, and parts of the system in chronological order. This is particularly important for understanding complex asynchronous operations and multi-party interactions.

The same is true for the login function. The timing diagram can clearly show the time sequence of data flow and state changes:

State diagram: clear expression of state transitions

For functions with complex state management, state diagrams can help Cursor understand the transition relationship between states:

This multi-dimensional process expression allows Cursor to understand the application process from different angles, greatly improving the accuracy of code generation.

Choose the right chart type

When working with Cursor, I have summarized the best use cases for these charts:

• •  Flowcharts are suitable for expressing :
• • Page navigation and transition relationships
• • Conditional branches and decision points
• • Overall business process and state transitions
• • Possible user operation paths
• •  Timing diagrams are suitable for expressing :
• • Multi-party system interaction details
• • Asynchronous operations and callback processes
• • Data transfer and conversion process
• • Event triggering and response mechanism
• • Concurrency and race conditions
• •  State diagrams are suitable for expressing :
• • State changes during the object life cycle
• • Triggering conditions for state transitions
• • Allowed operations in each state

Practice shows that providing these charts at the same time for complex functions can increase the accuracy of Cursor code generation from 80% to more than 95%.

How does process documentation improve the Cursor development experience?

After two years of intensive product development with Cursor, I found that process documentation can improve the AI ​​programming experience in many dimensions:

1. Let AI write correctly the first time, without repeated corrections

Remember the friend I mentioned earlier? In the end, he created a detailed forum posting process as I suggested, including a flowchart and a timing diagram of key interactions, and tried to implement it with Cursor again. The result was shocking: the code generated by AI in one go met 95% of the requirements, and only a few lines of fine-tuning were needed to go online.

In another e-commerce project, we first drew a complete order flow chart and payment interaction sequence chart, and then guided Cursor to implement it step by step. The most amazing thing is that AI made almost no mistakes in the entire core process from shopping cart to payment, saving us a lot of debugging time.

2. Communication costs are minimized and team collaboration is more efficient

When using Cursor for team development, process documents become the "common language" between the team and AI. Front-end developers, back-end developers, and designers all refer to the same process document to guide AI to generate the code or design specifications they need.

One time, when implementing an API, our backend developer directly referenced the sequence diagram in the process document and told Cursor: "Please design the order status management API based on this sequence diagram." As a result, AI not only generated accurate code, but also proactively proposed several edge case processing that we had overlooked.

3. AI can automatically identify page relationships and generate consistent components

When there is no process documentation, letting Cursor develop multiple related pages often leads to inconsistent data transfer and state management between pages. With a flowchart as a reference, AI can "see" the structure of the entire application.

For example, when we developed a management system with a "list page-details page-edit page" structure, after providing the AI ​​with a flowchart, it was able to correctly handle navigation and data transfer between pages, and even automatically implement breadcrumb navigation, which might have required additional prompts from us before.

4. Let AI better understand exception handling and edge cases

What surprised me most was that after providing detailed process documentation, especially the timing diagram containing the abnormal path, Cursor's ability to handle abnormal situations was significantly improved. It no longer only focused on the "ideal path" but also actively considered various error situations.

When developing a file upload function, AI not only implemented the basic upload function based on our timing diagram, but also proactively handled a variety of abnormal situations such as network interruption, file size being too large, format errors, etc., which previously required us to clearly prompt before considering them.

How to create Cursor-friendly process documentation?

After repeated experiments, I have summarized a set of methods for creating "AI-friendly" process documents. These tips can make your process document a perfect guide for Cursor:

1. Describe each step using a standardized model

I find that Cursors are particularly good at handling information in a consistent format. Each step works best with a structure like this:

Step X: [Operation Name]
- User action: User clicks/enters/selects...
- System response: System display/processing/jump...
- Status change: [Changes in the status of related data]
- Exception handling: [Possible problems and solutions]

This structure allows AI to precisely understand the logic of each step and generate more accurate code.

2. Add data status annotations to the flowchart

Ordinary flowcharts mainly show the operation steps, but for Cursor, it is more valuable to mark the changes in data status. For example:

Note that I addeduserStatus='loggedIn'anderrorCount++Such status annotation greatly helps Cursor understand data flow and status management.

3. Clearly mark the data transfer content in the timing diagram

The most powerful aspect of sequence diagrams is that they can clearly show the content and format of data transmission. When creating a sequence diagram for a Cursor, the specific content of each message should be clearly marked:

Such a timing diagram not only shows the interaction process, but also clarifies the API request format and various response situations, allowing AI to generate more accurate front-end and back-end codes.

4. Provide pseudo-code examples for complex business logic

For complex business rules, I usually add simple pseudocode to the process document. Cursor is particularly good at converting pseudocode into actual implementation.

For example, when describing a coupon rule:

//Coupon application logic
if  (order contains limited items) {
  if  (order amount > coupon threshold) {
    Applied discount =  min (coupon value, order amount * maximum discount ratio)
  }  else  {
    Display "Discount threshold not reached"
  }
}  else  {
  It shows "No items available in order"
}

Such pseudocode allows AI to accurately understand business rules and generate expected implementations.

5. Clarify interface elements and interaction feedback

The process document clearly points out the key elements on the interface and the feedback after the user's operation, which allows Cursor to generate more complete UI code:

Key elements of the shopping cart page:
- Product list (left 70%)
  - Each product item contains: picture, name, unit price, quantity selector, subtotal, delete button
  - Subtotals and totals update instantly when quantities change
- Settlement area (right 30%)
  - Total price
  - Special offers
  - Checkout button (highlighted and loading animation displayed after clicking)

With these clear UI guidelines, Cursor can generate interface code that is more in line with expectations.

6. Create cross-page state management guidelines

When developing complex applications, state management is the most confusing part of Cursor. I usually add a "State Management Guide" to the process documentation:

Global state:
- userState: {id, name, role, tokens}
- cartState: {items, totalPrice, discount}
- orderState: {current, history}

State persistence strategy:
- userState: localStorage + memory
- cartState: localStorage
- orderState.current: sessionStorage
- orderState.history: only obtained from the API

State transfer between pages:
- Product details → Shopping cart: via global cartState
- Shopping cart → Checkout: pass the order ID via URL parameters

This type of guidance greatly helps Cursor understand how to design a state management system and avoid generating duplicate or contradictory code.

Case Study: Process-Driven Cursor Development

Let me share a complete case to show how to use process documentation to guide efficient Cursor development.

Recently I needed to develop an online examination system for a university in Hong Kong. We first created a flowchart of "students taking an exam":

At the same time, we also created a timing diagram of key interactions, especially the data preservation mechanism during the answering process

Then, I presented Cursor with my first development task:

"According to the flow chart and sequence diagram, implement the front-end interface for students to take the exam, including the exam list, exam instructions, answering interface and result page. Use React and Ant Design component library."

What’s amazing is that Cursor not only generates complete UI components, but also automatically handles a variety of scenarios:

• • Automatically save answers to localStorage when the network is disconnected
• • You can continue the last exam after accidentally closing the page
• • Automatically record the time students spend on each question

We did not explicitly request these features, but Cursor took these user experience details into account by understanding the process documentation, especially the exception handling process in the sequence diagram. More importantly, there was almost no rework during the entire development process because AI understood the complete user process from the beginning.

From Process to Code: Cursor's Thought Journey

When you provide Cursor with process documentation, how does it convert this information into code? Based on my observations, AI generally follows this line of thought:

1. 1.  Overall architecture planning : Understand the page structure and navigation relationship of the entire application through flowcharts
2. 2.  State model design : plan state management solutions based on data requirements in the process
3. 3.  Component hierarchy : Split the UI into a reasonable component hierarchy
4. 4.  Interaction logic implementation : implement specific functions according to the interaction details in the timing diagram
5. 5.  Boundary case handling : Add error handling based on the abnormal situation description in the process document

What impressed me most was that the more detailed the process documentation was, the closer Cursor's code was to our expectations. It not only understood "what to do", but also "why to do it", thus generating code that was more in line with business logic.

Checklist for process documentation: ensuring AI-friendliness

Finally, here is a practical checklist to help you assess whether your process documentation is AI-friendly enough:

• • Use consistent terminology and nomenclature to avoid using different names for the same concept
• • Each user action has a clear starting point, middle and end point
• • All key decision points have clear conditions and branching paths
• • Special processes for handling abnormal situations and boundary conditions
• • Changes in key data status are clearly marked in the process
• • Use flowcharts to show overall structure and navigation relationships
• • Use sequence diagrams to illustrate complex interactions and data flows
• • Use statechart diagrams to illustrate object lifecycles and state transitions
• • Complex business rules have pseudocode or explicit rule descriptions
• • Key UI elements and interactive feedback are clearly explained

This checklist helps me ensure that every process document can be accurately understood by Cursor, greatly improving development efficiency.

Synergy between process documentation and the three-stage work method

In my recent Cursor development practice, I found that application process documentation has a natural fit with the three-stage work method (research, planning, and execution) summarized by the group leader Teacher Daming. In the previous article, I briefly introduced the basic concepts of this methodology. Today I want to share how process documentation plays a core role in this method.

After in-depth understanding, clear plan, research phase, planning phase, execution phase, understanding, demand analysis, process documentation, simulation solution

Research phase: in-depth analysis of process documentation

In the research phase of the three-stage work method, process documentation becomes the core material for us to understand the requirements. At this stage, I usually:

1. 1.  Show the process document to Cursor : Let AI analyze every step of the process in detail
2. 2.  Guide AI to understand state transitions : Pay special attention to decision points and state changes in the process

For example, in an e-commerce project, I provided Cursor with the order process document and asked it to analyze the state changes of the entire order life cycle:

Me: This is our order processing flow. Please analyze the triggering conditions and business rules for each state transition.

AI: According to the process documentation, order status transitions include:
1. created → pending_payment: automatically converted after the user submits the order
2. pending_payment → paid: triggered by payment callback after successful payment
3. Paid → processing: The system automatically processes new payment orders every 10 minutes
...

This in-depth analysis helps Cursor establish an accurate understanding of business processes and lays the foundation for subsequent development.

Planning Phase: Process-Driven Design Decisions

During the planning phase, process documentation directly influences the design of the technical solution. I have found the following practices to be particularly effective:

1. 1.  Design data model based on process status : the status in process documentation is directly mapped to database design and status management
2. 2.  Task decomposition based on process : Each key node of the process becomes a development task

Such planning allows development tasks to be closely aligned with business processes, ensuring that key functional points are not missed.

Execution phase: accurate implementation of process guidance

During the execution phase, the process documentation becomes a direct reference for code implementation:

1. 1.  State management implementation : Design state management logic based on state transitions in the flowchart
2. 2.  Exception handling coverage : Ensure that each exception path in the process document has a corresponding code handling

In this way, Cursor can generate code that is highly consistent with the business process and reduce the number of repeated modifications.

Real case: process-driven project efficiency improvement

As shown in the above case, in the online course system development of a university in Hong Kong that I was responsible for in the past half month, the team applied a three-stage work method driven by process documents:

1. 1.  Research phase : We created a detailed online course process document, including the complete process of course release, student course selection, learning progress tracking, assessment and scoring, covering 15 states and more than 25 state transitions
2. 2.  Planning phase : 42 development tasks were created based on the process documentation, with clear priorities and dependencies
3. 3.  Execution phase : Cursor implements the core code according to the process documentation, especially the complex state system for student course selection and learning progress management

In the end, the project was completed 35% ahead of schedule, especially in the two complex modules of course content management and learning progress tracking, the code quality far exceeded expectations. Although the project is still in iteration and cannot be said to be a complete case process, after applying this method, the efficiency has really been greatly improved.

Key lessons learned from integrating process documentation into development methodology

In addition, I have been working on several projects that I am responsible for, and I have summarized some experiences on how to effectively integrate process documentation into development methodology:

1. 1.  Process documentation first : Before starting the three-stage workflow, complete the process documentation of key functions
2. 2.  Process terminology consistency : Ensure that the terminology in the process documentation is consistent in subsequent development
3. 3.  Frequently refer to the process : In the conversation with the Cursor, often refer to the nodes and states in the process document

Through these practices, process documentation is not only a guide for development, but also a "common language" for communication between the team and AI, greatly improving development efficiency.

Integrating process documentation into development methodology is one of the most valuable discoveries I made in developing Cursor. It allows AI to truly understand product logic, no longer simply "write code", but to think and solve problems in a way that is closer to that of human developers.