Become an agent manager: build, run, and supervise your AI agents

An agent manager is someone who directs AI agents instead of doing every task by hand: they decide what the agents work on, review the output, and step in only when judgment is needed. Somodus is built for exactly this role — you describe each agent in plain language, and then manage a small team of them from one dashboard, with no coding required.

What managing agents looks like on Somodus

Brief them like a manager, not a programmer

Each agent starts from a plain-language description of the job — "every weekday, summarize new client emails and update the tracker." You review the generated plan before it goes live, the same way you'd approve a new hire's first project.

See exactly what your agents did

Every agent keeps an execution history: when it ran, what it produced, and whether anything went wrong. Reports arrive by email or Telegram, so reviewing your agents' work fits into the tools you already check.

Steer without a dashboard visit

From Telegram chat — text or voice — you can ask an agent questions, run its actions, adjust or pause its schedule, and update its standing instructions. Management by conversation.

Guardrails are built in

Agents pause automatically on critical errors and alert you instead of failing silently. Costs are metered per run in plan credits, so you always know what each agent consumes. Actions that publish or send from chat confirm with you first.

Why this role is emerging

As agents take over recurring "read, think, write" work, the human job shifts from doing the task to directing and reviewing it — business publications now describe "agent manager" as one of the defining roles of the AI era. You don't need an enterprise platform to work this way: a solo founder or a small team can run a handful of Somodus agents — a digest agent, a monitoring agent, a publishing agent — and spend minutes a day supervising instead of hours doing.

Start small, then delegate more

A practical path: treat your first agent like an intern — give it one well-defined recurring task and review its output for a week. As it proves reliable, add agents and widen their scope. Because every agent's plan is approved by you and every run is logged, the trust builds on evidence, not hope.

Frequently asked questions

What is an AI agent manager?

An agent manager is a person who supervises AI agents: they define the work in plain language, review plans and outputs, adjust schedules, and intervene only when judgment is needed — managing a team of software workers rather than performing each task by hand.

How do I manage AI agents without coding?

On Somodus, entirely in plain language: describe each agent's job, approve the generated plan, and pick a schedule. After that, management happens through reports, an execution history, and two-way Telegram chat — you can ask questions, run actions, and pause or reschedule agents by message or voice.

How many agents can one person manage?

A solo operator can comfortably supervise several Somodus agents, because supervision is lightweight: agents report on schedule, pause themselves on critical errors, and show estimated credits per run before you install them. Plans include multiple custom agents per month (3 on Starter, 8 on Pro, 22 on Elite).

How do I know what my agents actually did?

Every agent keeps a full execution history — when it ran, what it produced, and any errors — and delivers its output by email or Telegram. You review evidence, not promises.

What happens when an agent makes a mistake?

Agents pause automatically on critical errors and alert you, and chat-triggered actions that publish or send confirm with you before acting. You fix the instruction or adjust the plan, and the agent resumes — the same loop a manager runs with a new team member.

Related

What you can automate with a Claude AI agent — jobs worth delegating first, and the Telegram AI assistant — manage your agents from chat, including by voice.