How to Use AI Coding Assistants to Build a Portfolio Project in 4 Weeks

As an indie hacker or solo founder, you know the importance of having a strong portfolio project. It showcases your skills and can be a game-changer when applying for jobs or attracting clients. But what if I told you that using AI coding assistants could help you build a solid project in just four weeks? Sounds too good to be true? Let’s break it down.

Week 1: Define Your Project and Get Set Up

Choose the Right Project

Start by picking a project that aligns with your interests and showcases your skills. A simple web application or a tool solving a specific problem is often a good choice. For example, a personal finance tracker or a task management tool can be both useful and demonstrate your coding skills.

Tools Needed

• AI Coding Assistant: Choose from tools like GitHub Copilot, Tabnine, or Codeium.
• Code Editor: Visual Studio Code or JetBrains IDEs.
• Version Control: GitHub for managing your codebase.

Pricing Overview

| Tool | Pricing | Best For | Limitations | |--------------------|----------------------------------|-------------------------------|-----------------------------------------| | GitHub Copilot | $10/mo, free trial available | JavaScript, Python, TypeScript| Limited to supported languages | | Tabnine | Free tier + $12/mo pro | Multiple languages | Pro version needed for advanced features| | Codeium | Free | Quick code suggestions | Less mature than competitors |

Our Take

We started with GitHub Copilot and found it particularly helpful for JavaScript projects. Tabnine is great for broader language support but requires a pro subscription for the best features.

Week 2: Build the Core Functionality

Start Coding

Using your chosen AI coding assistant, begin building the core functionalities of your project. For instance, if you’re building a personal finance tracker, start with user authentication and input forms.

Troubleshooting

• What Could Go Wrong: You might run into issues with AI-generated code not being optimal.
• Solution: Always review and test the AI-generated code thoroughly. Use tools like ESLint for JavaScript to catch errors.

Expected Outputs

By the end of Week 2, you should have a basic version of your project running locally. This will give you a solid foundation to build upon in the next weeks.

Week 3: Enhance Your Project

Add Features

In this week, focus on enhancing your project with additional features. Consider integrating APIs for added functionality, like a currency converter for your personal finance tracker.

Decision Framework

• Choose GitHub Copilot if you want seamless integration with GitHub and are working in supported languages.
• Choose Tabnine if you need multi-language support and prefer a more customizable experience.

Pricing Comparison

| Tool | Pricing | Best For | Limitations | |--------------------|----------------------------------|-------------------------------|-----------------------------------------| | GitHub Copilot | $10/mo, free trial available | JavaScript, Python, TypeScript| Limited to supported languages | | Tabnine | Free tier + $12/mo pro | Multiple languages | Pro version needed for advanced features| | Codeium | Free | Quick code suggestions | Less mature than competitors |

Our Experience

We used APIs to pull in live data for our project. It was straightforward with Copilot suggesting the right code snippets, speeding up our development process significantly.

Week 4: Polish and Deploy

Final Touches

This week is all about polishing your project. Focus on UI/UX improvements, documentation, and testing.

Deployment

Deploy your project using platforms like Vercel, Netlify, or Heroku. These services are user-friendly and allow for easy deployment of web applications.

What's Next

Once deployed, share your project on platforms like Product Hunt or Twitter. Collect feedback and iterate on your project based on user input.

Conclusion: Start Here

To build a portfolio project using AI coding assistants, start by choosing a project that excites you. Use an AI tool that fits your coding needs and budget, and follow the four-week timeline to create a polished product.

What we actually use: GitHub Copilot for code generation, Vercel for deployment, and GitHub for version control. This combination has worked well for us, balancing functionality and cost.