AI isn’t just one thing anymore. It’s not just a chatbot, a content generator, or a tool that answers questions. It’s starting to show up in your inbox, your dashboards, your workflows and if you’re not sure what the difference is between LLMs, copilots, and agents, you’re not alone.

Here’s a breakdown to help you understand how they work, how they’re different, and how they might fit into your business.

1. Large Language Models (LLMs) — The Brain

Think of an LLM as the engine that powers most modern AI tools. ChatGPT, Claude, Gemini, and Grok are all examples of LLMs. These are massive language models trained on huge datasets that can generate human-like text, summarize information, translate languages, and more.

What they’re good at:

• Answering questions

• Writing or rewriting content

• Summarizing long documents

• Brainstorming ideas

• Acting like a super-powered autocomplete

What they’re not great at:

• Understanding your company’s tools or data

• Taking action across software

• Running repeatable tasks automatically

LLMs are smart, but they don’t do anything unless you tell them to.

2. Copilots — The Assistant Sitting Beside You

Copilots (like Microsoft Copilot, GitHub Copilot, or Notion AI) are LLMs embedded inside your existing tools. They’re built to help you get more out of the software you already use—by writing emails, creating slide decks, summarizing meetings, generating code, and more.

They help you:

• Speed up work inside specific platforms

• Auto-complete or draft content

• Stay in the flow of your current tasks

But they still rely on you to:

• Guide the task

• Press the buttons

• Review and approve the output

Copilots are helpful, but they’re reactive. They’re only there when you’re working and while you’re using that tool.

3. AI Agents — The Worker That Runs in the Background

Agents take it one step further. They don’t just generate ideas or assist with content—they actually do work on your behalf.

Agents are built with rules, triggers, and workflows that let them operate independently. They can watch your CRM, wait for a new lead to arrive, enrich the data, assign a follow-up, and send a Slack message—all without you doing a thing.

Agents can:

• Take actions across platforms (email, CRM, project tools)

• Handle repeatable workflows (daily reports, lead routing, quote generation)

• Run on triggers (like “when a new deal is created” or “every Friday at 8am”)

They’re especially powerful for:

• Small businesses trying to reduce busywork

• Teams who need better follow-through

• Companies tired of running operations out of spreadsheets and inboxes

So… Which One Do You Need?

It depends on where your business is at. Chances are all of them at some point in time.

• If you’re just exploring AI, start by experimenting with LLMs in tools like ChatGPT or Claude.

• If you want to boost productivity inside tools like Google Docs, Notion, or Microsoft 365, try a copilot.

• But if your team is buried in manual admin, chasing updates, or repeating steps then it’s time to think about agents.

The Bottom Line

You don’t have to jump straight to full automation. The smart move is to start where you are and level up over time.

• Begin with LLMs to explore ideas, write faster, and get comfortable with AI’s capabilities.

• Move into copilots once you’re ready to boost productivity inside your existing tools.

• Graduate to agents when you’re ready to eliminate repeatable work and free up your team’s time.

This is the natural path. Crawl, walk, automate.

If you’re unsure where to begin or how to move to the next step, I’d be happy to walk you through it.