LLM Instructions as Part of Web Frameworks

The rise of artificial intelligence in software development brings many benefits, but also some challenges. One problem is that AI models sometimes slow down the use of new and better technologies. This happens because AI tools are trained with data that stops at a certain point, and they follow system prompts that affect their responses.

How AI Influences Technology Choices

Many AI tools are built with system prompts that encourage the use of popular technologies such as React or Tailwind. Because these tools appear frequently in the training data, they are often suggested even when newer technologies might be better. This bias is explained in the essay AI is Stifling Tech Adoption.

Given this bias, it is important to explore solutions that address these limitations.

A Possible Solution: LLM Instructions in Web Frameworks

One way to solve this problem is to update the AI tools with new guidelines. By "LLM instructions" we mean a set of updated guidelines that tell the Large Language Model (LLM) how to behave using the most up-to-date information available. Encore.ts is a framework that includes these guidelines as part of its system^1. The content can be updated as the framework evolves, so that the LLM is always working with the latest data. This approach can help encourage the use of new and promising technologies that might otherwise be ignored.

Conclusion

AI models help many developers, but they can also slow down the adoption of new technologies because they rely on old training data and fixed system prompts. Using updated LLM instructions provided by web frameworks—such as the approach taken by Encore.ts—offers a possible solution. With up-to-date guidelines, developers can receive more accurate support from LLMs, which can lead to increased adoption of new technologies.