Made for Swiss self-employed & SMEsAn agent acts, a chatbot talks
If a chatbot is a colleague who gives you an answer when you ask, an agent is a colleague who handles the whole request.
Ask a chatbot "summarise this email thread" and it will produce a summary. Ask an agent the same thing and it will read the thread itself, write the summary, and — if you've asked — draft a reply and file both where they belong. The agent does the reading, deciding and doing; you review the result.
That shift — from answering to acting — is what makes agents useful for the repetitive admin that fills a self-employed person's week: inbox triage, meeting notes, client follow-ups, document drafts.
Agents vs chatbots, copilots and automation
| Concept | What it does | Who's in charge |
|---|---|---|
| Chatbot | Answers questions and generates text | You — every step |
| Copilot | Suggests and assists while you work | You — it augments |
| Automation / RPA | Repeats fixed, rule-based steps (no AI) | Rules you predefined |
| AI agent | Plans and executes multi-step tasks with tools & memory | It acts, you approve |
The key word is autonomy with oversight: an agent can decide the steps, but a well-configured one still checks in with you before anything irreversible.
How an agent actually works
Under the hood, an agent runs a loop — it keeps repeating these steps until the goal is met or it hands control back to you:
- Understand — parse your request into a goal.
- Plan — break the goal into concrete steps.
- Act — call a tool (search the web, read an email, update a record).
- Observe — look at the result and decide the next step.
- Report — show you what it did, and wait for approval where needed.
The three building blocks
Tool calling
Agents can only do things because they can call tools: the model emits a structured instruction ("read this email", "create this calendar event"), and the agent's runtime executes it. That's the difference between a model that imagines a task and software that performs it.
Memory
Agents keep memory so they don't start from zero every time. Short-term memory holds the current task; long-term memory stores your preferences, people, projects and past decisions. OpenClaw and Hermes both keep this on your own machine, which is why they know you better the longer you use them.
Skills
A skill is a reusable how-to — a packaged procedure the agent loads and follows. Hermes is notable for creating its own skills from experience: when it solves something well once, it saves the approach and reuses it next time. That self-improving loop is its signature strength.
What that means for your workday
Large companies have whole departments for AI. Self-employed people and small teams usually get vague advice and a to-do list they never finish. An agent is different: it's one tool that quietly absorbs the repetitive admin that eats your week — so you can spend it on clients instead of the inbox.