Agents

For years, we’ve been told that software is eating the world. Big, cloud-hosted platforms — Salesforce, Notion, Slack, Jira, Airtable — working to solve every problem for every team, at any scale. And mostly, they delivered. SaaS transformed how businesses work.

I moved my 20+ year old WordPress blog off Bluehost and onto a modern static site setup with Hugo and Cloudflare Workers. What I expected to be a painful, multi-week project turned into a surprisingly smooth 4-day migration, largely thanks to working with Claude as a coding agent throughout the process.

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.