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This page walks through the whole path from a blank bot to a working AI agent: turning the system on, creating a named agent with its own instructions and knowledge, and switching it on so it can actually reply to customers.

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Turn on AI Agents

Chatbot Manager tab bar with AI selected, the AI Configuration sub-tab active, the AI Agent toggle enabled with Create Agent and Refresh buttons, and an Agent Routing table with an Add Rule button
1

Open Chatbot Manager

Select Chatbot Manager.
2

Open the AI tab

Select AI, then the AI Configuration sub-tab.
3

Turn it on

Turn on the AI Agent toggle — “AI agents are active and ready to assist.”
The AI Assistant Overview card on the right summarizes the setup at a glance: Active Agents, Agent Routing rule count, Response Mode, Contextual Memory, Restricted Topics count, and AI Reasoning Level.
Turning the toggle on doesn’t make anything reply yet — you still need to create an agent (next section) and then activate it. Think of this toggle as the master power switch, and the steps below as building and plugging in the actual worker.

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Create your first AI agent

Agents tab with the AI Agents list — columns for Agent, Knowledge Sources, Status, and Actions — and a Create Agent button; shown here with no agents created yet
1

Open the Agents tab

In Chatbot Manager → AI, select the Agents sub-tab. Every agent you’ve built appears here with its knowledge source count and status.
2

Click Create Agent

Opens the Create AI Agent form.
Create AI Agent form with Name, Slug (placeholder sales-agent, auto-generated from name if empty), and Status set to Active
3

Name it

Give it a clear Name, e.g. Sales Advisor Agent. The Slug auto-generates from the name if you leave it empty (e.g. sales-agent) — this is the internal identifier used when referencing the agent elsewhere (like transferring a conversation to it).
4

Describe what it does (optional)

Description field with placeholder text: e.g., Helps customers with product information and purchases
A short internal note, e.g. “Helps customers with product information and purchases.” — this doesn’t affect behavior, it’s just for your own reference in the Agents list.
5

Write the System Prompt

System Prompt field with placeholder text: You are the Sales AI Agent. Help customers purchase products, and a note that typing ## autocompletes actions
The System Prompt is the agent’s core instructions — its role, tone, and boundaries. A vague prompt like “You are a sales agent, help customers buy things” produces a mediocre agent. A strong one is specific about the role, what information to collect, the conversation rules, and exactly which actions to run and when.Full example, for the Sales Advisor Agent created above:
The pattern to notice: plain instruction, then the ##action## it triggers, right below it. That’s what turns a passive chatbot into a digital worker that actually completes tasks.Two more patterns, so you can see how the shape of a prompt changes with the job:A Support Agent — simpler, focused entirely on answer-or-escalate:
A Media Agent — no data collection at all, just conditional photo delivery:
Because the Support Agent collects context before escalating, the human teammate who picks up the conversation already has what they need — no re-asking the customer to explain the issue again.
Only one confirmed way to send images from an agent: upload them under Knowledge Sources → Media, in the next step below, with a description for each — not by typing image URLs into the System Prompt. This is what ChatSyncs’ own System Prompt Actions reference confirms.
One agent per job is the pattern here — see How Do I Build a Multi-Agent AI Workforce? for how these three agents work together with Knowledge Sources, Agent Routing, and a testing checklist once you’re ready to go beyond a single agent.While typing, you don’t have to remember the exact ##action_name## syntax — type ## in the box to autocomplete an action, then pick a label/sequence/etc. from the list that appears:
How to write actions in System Prompt popup, listing add_label, remove_label, assign_sequence, remove_sequence, save_custom_field, call_http_api, and the Shopify actions with their ##action_name##: id format
How to write actions in System Prompt popup continued, listing the WooCommerce actions, assign_human_member, assign_human_role, trigger_bot_flow, transfer_agent, mark_as_solved, block_subscriber, and skip_reply
This is only a quick reference while you’re typing — see AI Agent Actions for the full list with examples and how each one behaves.
6

Add Knowledge Sources

Right now, your agent can only work from the System Prompt you just wrote — it has no real business knowledge yet. If a customer asks something specific, like “are you open on Sunday?” or “do you have this in red?”, it has nothing to answer from. Knowledge Sources fix that: they’re where you feed the agent your actual business information, so it answers from real facts instead of guessing.Scroll down on the same Create AI Agent form to the Knowledge Sources panel:
Knowledge Sources panel with a Knowledge Set dropdown and six source type buttons: Content, URL, File, Media, Google Sheet, and API
First, give this knowledge a home: open Knowledge Set and either pick one you already made, or create a new one by typing a name for it — think of a Knowledge Set as a folder that can hold several pieces of training material at once. Everything you add below gets saved into whichever Knowledge Set is selected, and the agent reads all of it together when it answers.Once you have a Knowledge Set, there are six buttons for the six ways to fill it — use as many as you need:Content is the simplest one: a plain text box where you type or paste information directly, like your business hours or return policy.
Content panel with a single text box: Write the content your agent should learn from...
URL lets you point at a page you’ve already written — an FAQ page, a pricing page — and ChatSyncs reads its content instead of you retyping it. Paste the link in Campaign URL:
URL panel with a Campaign URL field, Fetch Content Configuration selectors, and Remove Content Configuration selectors, plus Generate Raw Response and Generate FAQ buttons
If the page has content you don’t want included — a header, footer, or ad banner — two optional settings let you fine-tune what gets read. Fetch Content Configuration pulls in only one part of the page (pick ID or Class as the Selector Type, then enter that exact ID or class name from the page’s code):
Selector Type dropdown open showing ID and Class options
Remove Content Configuration does the opposite — it excludes sections you list, and you can click + Add Remove Selector to exclude more than one:
Remove Content Configuration with two Selector Type / Selector Name rows and an Add Remove Selector button
Once the page loads, choose Generate Raw Response to keep it as one detailed block, or Generate FAQ to automatically split it into short question-and-answer pairs instead.File works the same way, but from a document instead of a webpage — upload a PDF, Word (.doc/.docx), Excel (.xls/.xlsx), CSV, OpenDocument (.ods/.odt), or TXT file, like a product catalog or a training manual:
File panel with an Upload button, and accepted formats listed: PDF, Word (.doc, .docx), Excel (.xls, .xlsx), CSV, OpenDocument (.ods, .odt), TXT
Media is how the agent learns to send photos, not just text. Add an Image URL (or click Upload) and write a short Description — this description is what tells the agent when to send that exact photo, so be specific about what makes it recognizable:
Media panel with an Image URL field, an Upload button, and a Description field with placeholder text: e.g. Red cotton kurti, size M, price 1200 BDT
With that saved, a customer asking “do you have this in red?” gets sent that exact photo automatically. Click + Add more image to attach as many as you need:
Media panel with the Add more image button highlighted
Google Sheet connects a spreadsheet you’ve already linked under How to Connect Google to ChatSyncs — pick it from the dropdown, which lists every sheet available to your connected Google account:
Select a Sheet dropdown open, showing a connected Google account and its available sheets
Google Sheet panel with a sheet selected under Import From Google Sheet, and a Save button
API, the last option, isn’t shown as a screenshot here since it’s just a dropdown — pick one of your already-configured HTTP APIs, and the agent pulls fresh data straight from that endpoint’s response each time, instead of storing anything static.
You don’t have to pick just one type. A single Knowledge Set can hold Content, a URL, a File, and Media all together — the agent uses everything in it to answer.
See How to Train Your AI Chatbot for the full reference page on every source type, including its own FAQ and troubleshooting.
7

Save

The agent now appears in the Agents list and in the Active Agents dropdown back on AI Configuration.

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Turn your new agent on

Creating an agent doesn’t make it start replying — it still needs to be switched on for this bot, back on the AI Configuration sub-tab.
Active Agents multi-select dropdown listing Order Status Agent, Sales Advisor Agent, and WhatsApp Marketing Agent
1

Go back to AI Configuration

Select the AI Configuration sub-tab again.
2

Open Active Agents

Click the Active Agents field — it’s a multi-select, so you can turn on more than one agent for the same bot.
3

Pick your new agent

Select the agent you just created. If it’s not in the list, click Refresh.
Only agents added here can actually reply to customers — everything you did in the previous section just built the agent, this step is what switches it on for this bot. If you activate more than one agent, Agent Routing is what decides which one answers a given customer message.

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Frequently asked

Name is what you see in the UI. Slug is the internal identifier (auto-generated from the name if left empty) used to reference this agent elsewhere, like in a transfer_agent action — see AI Agent Actions.
Check three things: it’s added to Active Agents on the AI Configuration tab, the AI Agent toggle is on, and it has at least one knowledge source attached — see How to Train Your AI Chatbot — if it’s meant to answer from trained content rather than just its System Prompt.
No — a single agent with a broad System Prompt and one Knowledge Set works fine for most bots. Multiple agents are worth it once different types of questions need very different instructions or actions — see How Do I Build a Multi-Agent AI Workforce?.