Introduction
With the advent of advanced language models, coding has never been easier. But is it really a good thing? LLMs (large language models) can generate functional code in the blink of an eye, but that doesn't mean the work is done once the code is in place. In reality, failing to take the time to write maintainable code can lead to long-term issues that even LLMs can't solve.
The Trap of Ease
One of the biggest mistakes we make is giving in to the ease these tools provide. Imagine you're working on a project where you need to check user access in multiple places: a route handler, a background job, an API endpoint, etc. Instead of creating a shared helper function, it can be tempting to let the AI generate similar conditions each time.
However, each duplicated piece of code adds unnecessary complexity. According to a Stripe study, 42% of developers' time is wasted on repetitive technical tasks and spaghetti code. By not properly structuring your code from the start, you contribute to this problem.
LLMs Learn from You
Just because LLMs can handle many tasks doesn't mean they do so in a vacuum. They rely on the patterns and structures you have already implemented. If you consistently provide them with messy code, you're training them to replicate those same bad practices.
Imagine asking your LLM to generate a new endpoint with the same access rules. It will rely on previous examples and replicate the same errors, making future maintenance even more challenging.
The Hidden Cost of Bad Practices
"Code smells" or bad practices accumulate quickly. A report from the Institute of Electrical and Electronics Engineers (IEEE) showed that resolving a code issue after delivery costs up to 100 times more than fixing it during the development phase. By not adhering to best practices, you risk ending up with code that is difficult to maintain and evolve.
Code for Tomorrow
To avoid these pitfalls, it's crucial to write code as if another developer will maintain it. This means:
- Using shared functions and modules: Reduce code duplication by creating reusable functions.
- Clearly naming variables and functions: This makes understanding and maintenance easier.
- Documenting your code: Even if the code is generated by an LLM, good documentation is essential.
Conclusion
Technology evolves, but some basic practices remain timeless. Writing clean and maintainable code is a skill that transcends technological generations. By focusing on solid practices today, you ensure that your code remains robust tomorrow.
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