Back in May of 2019 my LLC partner and I started exploring how artificial intelligence could impact education. Unfortunately tools for building AI driven applications were almost nonexistent at the time [this was two years after the Attention is All You Need paper, Large Language Models had yet to become commercially available].
Fast forward to February of 2024. By then OpenAI's GPT3 models had been released; LLM inference hosting providers were emerging with well documented APIs, and open source models were meeting or exceeding commercial models. As the R&D lead at Last Myle this was the breakthrough we needed to start building more complex AI experiments.
At the same time I was eager to leave LinkedIn; it was a legacy professional network model that didn't fit how I wanted to express my career and passions.
So with LLM inference APIs and multi-model routers, and modern web frameworks I was able to start building and running experiments for a new personal site experience.
The first experiment was focused on evaluating different large language models. Search for Intelligence was built as a evaluation workflow to score text and image responses from different LLMs. I also built a rudimentary memory system to store chats and evaluation scores.
The next experiment applied scoring analysis of LLMs from Search for Intelligence, to build a personal RAG pipeline. This enabled people to chat with a hybrid of my curriculum vitae. It was also an excuse to test Google's NotebookLM and the quality of podcast output.
From there I started experimenting with agents; first with Microsoft Research's AutoGen, then CrewAI, then Vercel's AI SDK. Simultaneously I started experimenting with Terminal UIs running in the browser; then building a hosted service to test multi-tenant performance. The summation of these experiments lead to my agents terminal system which has now been running continuously for weeks.
My agents terminal system has multiple [what I refer to as] 'network outcome' agents. The agent I'm most excited about is desgined for matching; where it converses with you to assess if we're a good match to work and build AI systems together. Go throught it; let's build agentic systems together.
Back at this site; it's also been updated to experiment with primitive agentic system visualization. If these become popular then I might pipeline them into sandbox environments; and leverage what I built for sandbox hosting.