ChatGPT is a conversational AI that generates text in a chat window. An AI agent uses that same kind of intelligence but connects to your business tools to actually complete tasks — publishing, emailing, scheduling, and updating your systems.
A chatbot responds to your messages inside a conversation window. An AI agent connects to your business tools and completes tasks — sending emails, publishing content, updating records — without you handling each step manually.
AI agents connect to external tools through MCP (Model Context Protocol), a standard that creates secure bridges between the AI and your platforms like WordPress, FluentCRM, Google Calendar, and more. Each connection gives the agent specific capabilities.
Agent memory is how an AI agent retains context between tasks and sessions. It includes short-term memory (within a single workflow) and long-term memory (stored preferences, past decisions, and accumulated knowledge about your business).
Not in the way humans learn, but yes in a practical sense. AI agents can use memory systems and logs to build context over time, remembering past decisions, user preferences, and what worked before to improve their performance.
Scripts and macros follow fixed steps every time with no variation. AI agents understand context, make judgment calls, and adapt their approach based on what they find. Scripts are rigid; agents are flexible and intelligent.
When an AI takes action, it goes beyond generating text and actually does something in your business systems — publishing a post, sending an email, updating a database, or scheduling an event through connected tools.
Yes. Building an AI agent today means writing clear instructions in plain English, not writing code. If you can explain a task step by step to a new hire, you can create an agent skill that handles that task automatically.
Every AI agent has four core components: a language model (the brain), tools (connections to your software), instructions (what to do), and memory (context from previous steps). Together, these let the agent understand, decide, and act.
A sub-agent is a specialist AI agent that gets called by a parent agent to handle a specific part of a larger task. It focuses on one job — like writing an email or analyzing a transcript — then returns its result to the parent.