Building a Timesheet Tracker Application with Replit AI Agent

In this blog, we’ll explore how to create a web application using Replit AI Agent, an exciting tool that can turn your ideas into working applications with just the help of clear prompts. Wondering what a Replit Agent is and how the whole process works? Let’s break it down! 

What is Replit Agent? 

The Replit Agent is an AI-powered development assistant that can build complete applications based on simple, well-written prompts from users. It supports multiple programming languages, but by default, the Replit Agent is most comfortable using: 

• React for front-end development.

• Express.js for the backend.

• PostgreSQL for the database. 

With just a clear set of instructions, the Replit Agent can set up both the front-end and back-end, creating a solid foundation for modern web applications. 

What Does It Take to Build an Application Using Replit Agent? 

At the heart of any application built with Replit Agent lies one key element: the prompt. 

A good prompt is like a blueprint. It should clearly define the features you want, along with any do’s and don’ts, so the AI can understand your exact requirements. 

A few golden rules for writing effective prompts: 

• Avoid overloading your prompt with too many instructions at once. A crowded or overly complex prompt can cause the Agent to stray from your intended outcome. 

• Break your project down into smaller parts and write feature-specific prompts. This helps the Agent focus on one piece at a time, reducing confusion and improving accuracy. 

• Even though the Replit Agent is highly capable, you should always run tests once the feature is generated. Minor bugs or differences from the expected behavior can occur. 

• If you find any bugs or mismatches, you can create a fixing prompt that clearly explains the difference between the actual and expected behavior, attaching a screenshot if possible, can make it even clearer for the Agent. 

For this Timesheet Tracker project, simple Word documents were used to write out each prompt in the same clear structure, adding screenshots whenever available, to guide the Agent. 

A Quick Note on Tech Stack 

By default, Replit Agent uses React with Tailwind CSS for the front-end, and an in-memory database for storing data during development. However, for real-world applications, you’ll likely need a proper database setup. 

To do that, all you need to do is mention it in your prompt. The Agent will automatically: 

• Set up a serverless PostgreSQL database, 

• Create the necessary scripts and schemas, 

• Push the schema to the database, 

• Migrate your data handling from in-memory storage to PostgreSQL. 

You can even query and view your tables directly in the serverless database environment, making it easy to validate and manage your application data. 

Timesheet Tracker Developments using Replit

Prompt 1: The Initial Requirements and Features

When it comes to building an application using Replit AI Agent, everything starts with the right prompt. Think of the prompt as your project’s blueprint, it tells the Agent exactly what you want to build, how it should behave, and what features you expect. 

A clear and structured prompt will make your development smoother and help the AI Agent understand your goals without confusion. 

Here’s what you should keep in mind while writing a prompt, using the Timesheet Tracker example: 

• Clarity is key 
  The prompt should explain the requirements in a straightforward and easy-to-understand way. Each feature, like user roles, timesheet entry, approval flow, and reporting, should be broken down clearly so the Agent knows exactly what to build. 

• Structure your requirements 
  Just like the Timesheet Tracker prompt, group your features logically. For example, User Management, Timesheet Entry, Leave Management, Reporting, and so on. This helps both you and the AI stay organized. 

• Mention region-specific needs 
  If your app has regional differences (like the USA vs. India workweeks or holidays), specify those in the prompt so the Agent can handle them correctly. 

• Role-Based Access is important 
  Define different user roles clearly (Admin, Manager, Employee, HR/Finance) and mention what each role can and cannot do. This avoids confusion later. 

• Don’t forget reports and exports 
  If you need specific reports or formats (Excel, PDF, date ranges, project-wise, etc.) — mention them upfront. This will help the Agent include these features from the start. 

• User-friendly notifications 
  Features like daily or weekly reminders and approval alerts should be included if you want smooth user interactions. 

• Real-world workflows matter 
  Including approval steps, comments, and reminders ensures your app feels natural and helpful for real users, not just technically functional. 

A Few Extra Tips for Writing a Good Prompt: 

• Keep it detailed but easy to follow, avoid overloading the prompt with too much in one go. 

• When possible, split large features into separate prompts, this keeps the AI Agent focused. 

• Include expected behaviors, user scenarios, or screenshots to give clear context. 

• Be specific about tools and tech stack, like telling the Agent to switch from in-memory to Postgres. 

• Always test the results, even when the Agent completes the build — minor bugs or misinterpretations can happen, and follow-up prompts help fix them. 

A well-crafted initial prompt is the secret to making Replit Agent work for you, not against you. The more precise you are, the closer the Agent’s output will match your vision. 

Below is the screenshot of Timesheet Tracker Application Developed by Replit Agent. 

Prompt 2: Bug Identification and Fixing with Replit Agent 

Even though Replit AI Agent does an excellent job generating full-featured applications from well-structured prompts, like any development process, it’s common to encounter minor bugs or unexpected behaviors. The key is to treat these moments as part of the iterative process. 

Once the initial version of the Timesheet Tracker Application was generated, real-time testing was conducted to make sure all the core features worked as intended. During this phase, a set of common functional bugs was identified which were compiled and addressed by sending the Agent new targeted prompts, clearly mentioning: 

• The Current Behavior (what’s happening).

• The Expected Behavior (what should happen).

• Screenshots (if available) for extra context. 

Here’s a quick snapshot of the Bug List 1 encountered: 

• Bug 1: Timesheet Approval/Rejection Error 
  When a Manager clicks “Confirm Approval/Rejection,” an error occurs — 
  value.toISOString is not a function. 
  → The timesheet should approve successfully and show in the approved list. 

• Bug 2: Adding Team Members to a Project 
  Adding team members accidentally adds the logged-in user instead of the selected one and even creates duplicates. 
  → It should correctly assign only the chosen team member to the project. 

• Bug 3: Timesheet Daily/Weekly Toggle Not Working 
  The toggle between Daily and Weekly views has no effect on the display. 
  → Switching the view should update the timesheet display accordingly. 

• Bug 4: Missing Auto-Refresh in Tables 
  After creating a new entry (timesheet, project, task, user, holiday), the new record doesn’t appear unless the page is manually refreshed. 
  → Newly added records should appear automatically in the table. 

• Bug 5: Incorrect Approval Count Displayed 
  The side menu always shows “3” for pending approvals, even if the actual number is different. 
  → The count should reflect the real number of pending approval requests. 

• Bug 6: View Full Calendar Not Working 
  Clicking “View Full Calendar” results in no action and no calendar is displayed. 
  → The app should show a full calendar with region-specific holidays configured by the Admin. 

Once these bugs were documented, Fixing prompts were used to guide the Agent with clear instructions on what went wrong and what the expected behavior should be. Adding screenshots wherever possible helped the Agent better understand UI-related issues, too. 

This approach — testing, identifying, and fixing bugs through follow-up prompts, highlights the importance of combining human testing with AI-generated builds. While the Replit Agent can save a huge amount of development time, it still benefits from human eyes to ensure everything works just the way you intended. 

Checklist – Key Steps to Build with Replit Agent

• Write clear, structured prompts. 

• Split complex features into separate prompts. 

• Test every feature thoroughly. 

• Use fixing prompts to address bugs. 

• Validate and deploy. 

Conclusion 

Building applications with the Replit AI Agent opens up an entirely new way of approaching software development. One where clear communication, through well-structured prompts, becomes just as important as coding itself. 

Throughout this Timesheet Tracker project, you’ve seen how an idea can turn into a working application simply by guiding the Replit Agent with clear instructions and thoughtful iteration. From defining your core functional requirements to identifying and fixing real-world bugs, the development process with AI still mirrors traditional software development in many ways, especially when it comes to testing and refining. 

The biggest takeaway? 

AI like Replit Agent isn’t here to replace developers, it’s here to accelerate your journey from concept to completion. The quality of the output depends entirely on the clarity of your inputs. If you learn to write structured, specific, and scenario-based prompts, you can dramatically reduce development time while maintaining the flexibility to adjust and correct issues as they arise.

So, whether you’re an experienced developer or someone experimenting with AI-powered app building for the first time, Replit Agent is a valuable companion that can help transform ideas into real, testable, and deployable applications, faster than ever.