HighLevel: Super Agents - Build AI Agents With a Conversation

HighLevel introduced Super Agents, an AI-first way to build agents inside Agent Studio. Instead of dragging through a map builder, you describe what you want the agent to do in plain English and the platform generates a working agent tailored to your business - one that can talk, pull answers from your knowledge base, and run CRM actions in the background.

What changed

Agent creation moves from a map-builder workflow to a conversational one. You write the use case in plain language and Agent Studio constructs the agent's logic behind the scenes, then lets you adjust it by chatting (for example, make the tone more casual and do not offer discounts) rather than rebuilding from scratch.

The agents are positioned as more than chatbots: they read your native Knowledge Base for hyper-accurate answers and act on the CRM - updating fields, handling data routing, and firing background automations. A built-in interactive sandbox lets you validate conversational style, parameters, and background actions before pushing to production.

Ready-to-build use cases

• Social Media Assistant - brainstorms, drafts, and schedules on-brand posts with tailored images per network.
• Knowledge Base Assistant - a frontline support desk answering technical or product questions from documentation.
• Email Campaign Manager - outlines, writes, and dispatches targeted email campaigns to contact segments.
• Community Moderator - greets new members, fields onboarding questions, and flags content violations by your rules.
• Day-to-Day Task Automation - handles administrative overhead, data scrubbing, and routine lead nurturing in the background.

How to get started

1. Navigate to your Agency Dashboard, then Settings, then Labs.
2. Locate and enable the Super Agents feature toggle.
3. Open Agent Studio and start chatting to build your first agent.

Why it matters for agencies and VAs

This lowers the build cost of an AI employee, which is the part agencies usually sell. The leverage is in the Knowledge Base grounding and the CRM actions - an agent that only chats is a demo, but one that updates fields, applies tags, and triggers automations is a fulfillment asset. Because it is a Labs feature, treat it as beta: build in the sandbox, prove the conversational behavior and the background actions on a test sub-account, and watch the knowledge base for stale or wrong answers before you put it in front of a client's leads.

Certified GHL Admin operator take

As a Certified GHL Admin, the make-or-break is the Knowledge Base, not the prompt. A natural-language builder will happily generate a confident agent on top of thin or outdated documentation, and that is how you ship wrong answers at scale. Lock the source docs first, sandbox every CRM action the agent can take, and only then wire the event triggers. The Labs label means do not put it on a client's live inbound flow until you have watched it behave.