Original post: https://www.skool.com/ai-automation-society/agency-owner-building-aios-as-a-service?p=4de9cf74 A while back I posted about building an AIOS as a service for my marketing agency clients, and about wanting an autonomous agent that holds your hand through setup and then becomes your ongoing assistant. Quick progress report: The agent does both jobs now. - Setup: it runs a conversational onboarding that builds your folder structure and business context for you. No manual interview, and you get comfortable with the agent from the first message because you watch it work. - Day to day: the same agent is your AIOS assistant. It teaches you the system lesson by lesson, builds and updates your skills, runs them on demand or on a schedule, and pulls from your connected tools. Everything is text-first, so you just ask. A few design choices that paid off: - Everything lives in plain files you download and own, not a vendor's cloud or a vector DB. It's portable, and any model can reason over it. (I am combining ICM, OKF and LLM-Wiki) - Capabilities are skills you build and run, not a fixed roster of agents. Much easier to grow and maintain. - It's provider-agnostic, so you can point it at whatever model you want and it isn't locked to one AI provider. - I added a simple dashboard you can preview before you stand it up, so you see your command center before committing to it. - I also ended up taking it past agencies. It now adapts to a few other kinds of local and online business, which was a nice validation that the method generalizes. Right now it's a working prototype I'm rolling out to a couple of clients and using it to run my agency, which is awesome. I'd really value feedback from this group on where the gaps are and what would push it further. Happy to connect, compare notes, or give anyone a walkthrough. Current stage: