Most multi-agent demos stop at "look, two agents can talk." In a client business, the hard part is knowing who owns the work, whether it was actually done, and what happens when an agent stalls. For Episode 3 of Agent Operators, I sat down with Jason Myers of AppLayer. He built Tango after realizing he had become the human copy-paste layer between his agents. We connected Hermes to a shared task list, watched workers claim jobs, and dug into audit trails, task leases, and recovery. Then I showed how Orgo cloud computers let you see and control the work when an agent needs a real desktop. In the conversation: • 04:19 — Hermes creates a task in Tango • 19:56 — Preventing two agents from doing the same job • 21:16 — Recovering stalled tasks • 30:25 — Agents working on Orgo cloud computers Watch the full 36-minute episode: https://youtu.be/LKCZXIGmrY4 If you’re deploying agents for clients, where do your handoffs still depend on you?

The new Agent Operators episode with Karsten Stinis is live. Karsten installs managed AI agents for businesses in Belgium. His offer is €2,750 for the setup, then €250 a month for support. The part I'd pay attention to is what happens during the installation: he watches the client work, finds a recurring task, and aims to have something useful waiting for them the next morning. Before you install the agent, decide what it will finish. A morning briefing is a good example: meetings, open tasks, and unanswered emails worth following up on. The person can open it, check the sources, and decide whether it helps. Whether you're building for yourself or a client, try scoping one overnight job: 1. The job: choose one recurring task. 2. The inputs: name the inbox, calendar, or task list it needs. Connect the accounts and check access. 3. The result: decide where the output should appear and when it should be ready. Make it easy to trace back to its sources. 4. The review: choose who checks it. Keep outgoing messages as drafts for the first run, and have a person approve them. Run it once. Read the output with the person who will use it. Use their corrections to improve the next run before adding another job. In the episode, Karsten walks through Hermes on Orgo, Composio for connecting business tools, Honcho for memory, and how he monitors usage and incidents. Keeping the workflow working is part of the service. He also reports one client's agent setup being built in 22 minutes. Humans still handle the tool and account connections. Watch the full conversation: How He Sells AI Agents for €2,750 + Monthly Support https://www.youtube.com/watch?v=Y8MJG3iDtSo What would you want your agent to have ready tomorrow morning? Share the job below.

Most AI agencies stop at $3K–$5K/month. Corey Ganim thinks that might be the smallest version of the opportunity. His math: If an agent creates $10K/month of value, that’s $120K/year. At a 4× multiple, the business may be worth ~$480K more. Why collect only the retainer when you could earn a piece of the upside? In Episode 1 of Agent Operators, Corey and I break down: 1. Grok Bot vs. Hermes: disposable specialist vs. persistent co-founder 2. Revenue agents that find leads and draft replies every hour 3. The managed-agent model: build, deploy, and keep the agents running 4. The next model: install the growth system for $0 upfront and earn equity only after profit grows The agents aren’t the business. The upside they create is. Watch the full 29-minute episode below. Which model are you building toward: AI concierge, managed agents, or an equity-aligned growth partnership?

Your clients already know how to text. What changes when their AI employee becomes a contact in their phone? I sat down with Manav Modi, CEO and co-founder of AgentPhone, for Episode 2 of Agent Operators. We try a live iMessage exchange and talk about connecting Hermes or OpenClaw on Orgo to a business phone number—so people can reach their agent through a familiar interface. In the conversation: • 05:06 — Live iMessage demo • 05:49 — Connecting agents through APIs and skills • 09:56 — Files, reactions, polls, and location • 15:33 — The opportunity for AI agencies For those building managed agents for clients, the question is: which specific workflow becomes more useful when someone can simply text their agent? Watch the full 19-minute conversation below: https://www.youtube.com/watch?v=DlILpW2FRNE What’s the first job you’d give an AI employee with its own phone number?