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've made a couple of small changes to the blog. I removed the personal journal section and added my projects to the RSS feed so you can see what I've been working on with Generative AI. Happy New Year!
I built Ask Paul, a generative AI demo that answers front-end web dev questions using my content. It leverages Polymath-AI to index content, find related concepts, and generate summaries by creating embedding vectors, using cosine-similarity, and querying OpenAI. The implementation has a UI, a Polymath Client, and a Polymath Host. It's super cool how accessible this tech is now!
I presented "Aiming for the Future" at Bangor University, exploring computing's evolution from the Difference Engine to the modern era, focusing on content/data delivery shifts. I proposed that Machine Learning, especially Generative AI, is the next major computing wave, akin to the Web's rise in the early 2000s, potentially mechanizing mental labor. The Student Expo showcased many final-year projects incorporating AI, from creative tools to practical problem-solving, indicating the growing importance of AI in various fields.
