Experimenting with Replit and AI Code Generation – Part One

JTS

After watching Shawn Kanungo’s latest video, I decided to explore Replit and see how quickly I could build an AI-powered application. Since most of my work is in eCommerce, I chose to create a chatbot that could answer FAQ-style questions for an online store.

Getting started was simple—I created a free Replit account and asked it to generate the code for an eCommerce chatbot. Within minutes, I had a functional codebase. After a bit of tuning, I quickly hit the OpenAI credit limit and upgraded to a paid plan.

Key Takeaways on AI Code Generation

  1. Python and TypeScript have clearly emerged as the standard languages.
  2. Traditional developers will need to adapt. My chatbot’s entire codebase was generated automatically.
  3. Some technical knowledge is still required. For example, knowing the basics of Python and PostgreSQL helps in guiding the agent.
  4. Cost monitoring matters. Even with crashes and debugging, my total spend was under $0.001. In production, tracking AI costs will be as important as managing cloud costs.
  5. Debugging through the AI agent is a game changer. As a Python novice, having the agent read logs, find the issue, and attempt fixes was incredible.

Example: Me: “The app crashed.” AI: “Let me check the logs and make some fixes.”

Observations on Replit

The Replit code generator is groundbreaking, but not flawless. For instance, when I added user/password authentication, the app crashed several times because the password hashing didn’t work correctly. That’s a basic function I would have expected to run smoothly out of the box.

Each debugging attempt consumed credits, which pushed me from the free plan to the paid version. While this reminded me of the old consulting time-and-materials model (suspiciously profitable for the platform), the total cost was only $2—so worth it for the results.

Once login was working, extending the app was seamless. I added analytics, FAQs, export features, and admin-only navigation in seconds.

What’s Next

My next step is to try running the chatbot locally on my Windows workstation. Replit can host it, but I’d like to package it in Docker for portability.

Overall, the experience showed me how far AI code generation has come—and how much it will reshape the way we approach software development.

About the author

During his twenty-five professional years, Mr. Silva has had experience in nearly every facet of the Information Technology industry. Ranging from advanced data mining / data visualization systems to running multi-state small business IT infrastructures, Mr. Silva has always provided precise and cost-effective strategies to meet any client’s needs. With his tremendous work ethic and “Can-Do” attitude, Mr. Silva has always met every challenge head-on and with intelligent determination. Mr. Silva is also a certified NAUI Advanced/Nitrox Diver, hoping to get a few more wrecks under his belt in the Atlantic.