Exploring the intersection of software development, AI, and the cloud. From the depths of C# to the frontier of AI, and the cloud, this is where ideas take shape and technology evolves.
Last year I wrote a basic blog post about using AI in software development (https://rocketsoftware.tech/blog/post/using-ai-to-help-with-code-writing). Over the last few months, I took on a project that would alter how I used AI for my projects.
In years past, I would always use Google to help me find answers to my questions when it came to how perform a specific task in C#, which was always effective but was also much more time consuming. For this project, I used Google's Gemini and my locally hosted Ollama server as my assistants. Both assistants were considerably more helpful than in years past. The project took just under 500 hours from conception to a fairly usable product (the product is SynapseKeep, a AI enhanced personal knowledge base). I build the project using .Net Aspire, which was fairly new to me.
Writing code isn't the hardest part, it's writing efficient code that's the hardest. When you're integrating with some many different third-party products (like external AI engines such as Gemini or Ollama Server and using a tool like Searxng and Firecrawler to get outside information), code execution efficiency is paramount, and that's where the assistants helped me the most, showing me best practices, helping set the right context windows, making sure my embedding vector sizes were right for my environment, all of that matters. The math involved on vector sizes and context windows alone is crazy.
The biggest thing that I learned throughout this project is that I still need to be able to piece it all together, AI still misses on some of the integration needs (outdated endpoints, etc.), and building and testing is even more critical than ever before.