Llm

A few months ago, I wrote about vibe coding and the challenge of shipping quickly-created prototypes. I ended that post suggesting we could “teach” coding agents about our platform primitives through instruction files and MCP servers. At my day job (League), we’ve been putting this idea into practice, and the results have been very encouraging.

AI-assisted coding tools and agents have unlocked an unprecedented level of functional prototyping. Not just for developers. Product managers, Designers, even the C-suite are building functional prototypes of their ideas in a matter of days, or even hours.

I’ve been using Copilot in VS Code to help build several different projects. I’ve also used Claude, Gemini, and ChatGPT to help start and evolve projects. I find the tools to be very helpful and I feel more productive using them. I also find myself having more fun when using the tools.

I had a lot of fun working through my “Exploring LLMs as Agent” series. I’m starting to dive a little deeper into some specific Agent use cases, so I’ll move away from “exploring” and start “building” agents.

Up to this point, I have been experimenting with my own home-grown agent framework, based on Simon Willison’s great LLM project to handle wrapping the different LLMs. Armed with some experience, I want to start looking at real frameworks. Google released an Agent Development Kit at Google Next. It supports many of the features I have been playing with, including tool calling, planning, MCP, and local models. It also supports some advanced concepts like agent orchestration.

I finally got around to exploring local models, which is surprisingly simple to set up. I wanted to see how well a local model would perform in ToolAgent compared to the remote models (mostly Gemini) I have been using.

I will likely run out of topics to cover in the “LLMs as Agents” series, eventually. I wanted to explore creating a chat UI and what I could do with embeddings but I didn’t do that. For more context , checkout the previous posts: Minimalist Approach, Taking Action, Planning via Prompting, Tools & Benchmarking, and WebAgent Gets a Refactor. Take a look at the repository to see the code.