Generating web apps with AI agents like Replit is incredibly powerful, enabling rapid prototyping and deployment. My experience building tldr.express, a personalized RSS feed summarizer, highlighted the importance of a detailed specification. While initial prompts yielded impressive results, I iteratively refined the app through configuration and additional prompts to address issues like email integration, AI model selection, output formatting, spam prevention, and bot mitigation. This iterative process reinforced that while AI agents excel at rapid generation, a well-defined specification upfront is crucial for a successful outcome.
I created a simple countdown timer web app that lets you track time until important events. It's built with a focus on no-code using Replit, including a cool integration with Black Forrest Labs' image API via Replit's Agent feature. Check out the live app and source code!
Building apps with LLMs and agents like Replit has been incredibly productive. The generated code is often vanilla and repetitive, raising questions about the future of frameworks. While frameworks offer abstractions and accelerate development, LLMs seem to disregard these patterns, focusing on implementation. This shift in software development driven by agents may lead to a world where direct code manipulation is unnecessary. It remains to be seen if frameworks and existing architectural patterns will still be relevant in this LLM-driven future or if new patterns will emerge.
