Leo Huang · one-person company + an AI agent team I built myself
I have a multi-agent system of my own, and I use it to operate a few live products: scheduling, pulling data together, producing content, watching customer support, monitoring service health. Most of the time it runs without me watching it.
You want to turn your team's SOPs, processes and decision trees into agents that really work, which is close to what I do every day. So what I hand you is something already running, with people using it, not just a plan.
Here are the five agents from your post, matched against what I have actually built and still have running:
I use all of these in practice, so they are the ground I know best.
These are all live right now, so you can open them directly:
NaLi Match is a nail and lash artist matching platform I built on my own with my AI team. It has over five hundred verified artists today, with real requests and real bookings happening every day, and matching, notifications, support and the back office are mostly automated. claude-real-video came out of a blocker I hit in my own work: an open source tool that lets AI read what is inside a video. One command installs it, and people outside Taiwan use it too.
I work with these every day. When I build an agent I habitually add checkpoints: have a second agent review it, test it for real before it goes live, compute numbers in code against the database. Agents built that way hold up better, and that is the only reason I am comfortable handing daily operations to them.
This can be flexible, freelance or project based. If it works for you, I suggest starting with the one process you most want automated, turning it into a single agent and getting it running. Once you see what it does, you decide whether to carry on with the rest. That keeps your commitment small and confirms the thing really works first.
Tell me the one thing you most want automated first, and I'll walk you through how I would build it
cortexos.main@gmail.com