10 AI Agent Terms You Need to Know
(Even If You're Not a Developer)
If you've heard terms like “agentic workflows” or “planner-executor architecture” tossed around lately and nodded along nervously—don’t worry. You’re not alone.
AI agents are reshaping how teams work, and understanding a few key terms can help you sound smarter in meetings and build smarter systems.
Whether you're a marketer automating outreach or a RevOps pro building customer journey agents, here are the top 10 AI agent concepts to keep in your back pocket:
1. Autonomous Agent
An AI system that can make decisions and take actions without someone constantly clicking buttons. It acts independently (within guardrails), like your own tireless digital assistant.
2. Goal-Oriented Behavior
Unlike a traditional script, agents don’t just follow a checklist—they work toward an end goal. Think: “Find top leads from this messy CRM” rather than “run query X.”
3. LLM-Powered Agent
These agents are powered by large language models (LLMs) like GPT. That means they understand language, write responses, and even reason through complex steps using text. Basically, they think in words.
4. Action Space
This is the playground. It’s everything the agent can do—like sending emails, querying databases, or updating a field in Salesforce. You design the space; the agent decides what to play with.
5. Tool Use / Tool Augmentation
Agents get exponentially more powerful when they use tools. Instead of just thinking, they can do—like look up live data, run a script, or update your Notion board.
6. Memory / Long-Term Context
Agents with memory don’t start from scratch every time. They remember what they did yesterday, who they’re working for, or that you hate being emailed on Fridays.
7. Planner vs Executor
This is a common setup where one agent (the planner) breaks a task into steps, and another (the executor) carries them out. It’s like a project manager and a doer working in sync.
8. Reflection / Self-Critique
The best agents check their own work. They might say, “Wait, that answer doesn’t look right—let me double-check.” It’s how agents go from okay to damn impressive.
9. Multi-Agent Systems
Why stop at one? Multi-agent setups let you assign different parts of a job to specialized agents—like a sales agent, a research agent, and a reporting agent working together.
10. Agentic Workflow
This is the new frontier. Instead of building dashboards or workflows with if/then rules, you create smart agents that handle the entire flow—from identifying a lead to writing a personalized follow-up and logging the result.
An agent for everyone
Agents aren’t just for engineers anymore. If you work in GTM, ops, CX, marketing, or product, knowing these concepts can help you automate smarter, communicate better with your AI team, and actually use agents—not just talk about them.
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