Languages

Situation:

• Faced a choice between Django and React for the platform.

• ChatGPT recommended Django** due to its lower learning curve and ability to rapidly generate backend logic.

Obstacle:

• No prior experience with Django or React, so I had to take a leap of faith.

Action:

• Early on, ChatGPT generated large code snippets, which I copied, tested, and debugged iteratively.

• Created diagrams in Lucidchart to visualize system architecture and track the evolving stack.

Result:

• {“Over time, I gained deep familiarity with Django’s core components”=>[“URLs, Views, Models, APIs, Forms, Admin, Middleware, and Tables**.”]}

• Began optimizing code structure, error handling, logging, and DB pooling for efficiency.

Learning:

• AI-augmented coding requires riding the wave**—at first, you don’t understand everything, but persistence pays off.

• Learned to critique AI-generated code, demanding better abstractions and cleaner architecture.

• Code generators became a key AI strength—ChatGPT was far more effective at **generating abstract, reusable patterns rather than long, repetitive logic.

Situation:

• Required HTML & CSS for structuring layouts.

• {“Used JavaScript and Ajax for”=>[“Asynchronous data fetching.”, “Multi-tab navigation.”, “Embedded charts and AI-driven UI elements**.”]}

Situation:

• Initially, the website was embedded in Django but was later separated to reduce hosting costs.

Obstacle:

• Managing a fully dynamic website was overkill for simple content.

Action:

• Migrated to Jekyll (static site generator), reducing server load.

• Dockerized Nginx, making deployment **fast and repeatable.

Result:

• Static site runs separately from the platform, ensuring **better security and lower costs.

Learning:

• Re-evaluating tech choices mid-project is critical—migrating to Jekyll saved **time, cost, and complexity.

• New doesn’t always mean hard—the static site migration took just **a few hours, making me wish I had done it from the start.