A quick note before we start: I use Claude as my primary AI platform, so most of the examples and features I describe here come from that experience. Other platforms — ChatGPT, Gemini, Copilot — offer similar capabilities. The levels I describe below apply across all of them.
When I talk about AI to local business owners and employees across North Georgia I run into two common sticking points.
The first is that they haven’t tried AI at all. The options feel overwhelming to them, and it’s not obvious where to begin.
The second is that they’ve tried it — usually the free chat version — and walked away unimpressed. It answered a question or two but didn’t feel like something that would actually change how they work.
Both reactions make sense. But both usually come from seeing only one part of a much bigger picture.
Understanding the different levels of AI tools is a good place to start.
Understanding How the Tools Work — AI Models vs. Harnesses
One concept worth understanding first is the difference between an AI Model and a Harness.
AI companies develop models — the underlying intelligence — at different levels of capability and cost. But when you use a web app or a desktop app to interact with AI, you’re not talking directly to the model. You’re using a harness: an interface built on top of the model that gives you a place to type, a way to choose which model you’re using, and a growing set of features that make the model more useful.
Claude, ChatGPT, Gemini — these are all harnesses. The model is the engine. The harness is the car.
AI companies keep building more functionality into their harnesses. I find it helpful to think of it as a ladder — each rung not as a different AI, but as more of what the harness can do.
Each rung builds on the one below it. You don’t have to climb to the top. Most businesses get real value from the first two rungs. But a lot of people either feel too overwhelmed to take the first step, or try Level 1 and conclude it’s not for them — before they’ve seen what’s above it.
Level 1: Chat
This is the most familiar form of AI. You type a question or a request, the AI responds. Back and forth, like a text conversation.
Chat is useful for one-off tasks — brainstorming, drafting an email, summarizing a document, answering a quick question. It’s fast and requires no setup.
For example: say you run a landscaping company in Alpharetta and you want to see why a competitor is outranking you for a certain term. Paste their URL and your URL into Claude and ask it to analyze the pages for SEO — the title tag, headings, content structure, what keywords it seems to be targeting. Tell it the format you want: “Give me a comparison, followed by three quick-win recommendations.” It’ll do exactly that.
The catch is that you have to re-explain what you want every time. The format, the focus, the level of detail — none of that carries over to your next conversation. Sure, you can continue using this single chat session for your SEO comparison, but at some point you’ll start to get less benefit. That’s because every AI model has what’s called a context window — the amount of text it can hold in mind at once. In a long, sprawling conversation, the earliest parts start to fall out of view. The AI isn’t forgetting on purpose; it just can’t see that far back anymore.
Additionally, a Chat session has limited information about you. It may pick up facts about you over time. But it’s passive and limited. It won’t know your business goals, your preferred format, how you like things worded, or the specific work you’re trying to get done. That’s what the next level is for.
Level 2: AI Assistants — With Context
Note: basic Chat is generally available on free plans. Projects — and everything at Level 2 and above — typically require a paid subscription. More on that in the Takeaway.
The next level is where AI starts to feel like a real working tool. Platforms like Claude call these Projects. ChatGPT calls them Custom GPTs. Gemini calls them Gems.
The idea is the same: you give the AI standing instructions and reference materials that persist across every conversation. It knows them every time you start, without you having to repeat yourself.
I have one set up for this blog. It knows who I’m writing for, how I like things framed, and a few of the people I have in mind as readers. I don’t re-explain any of that. I just start writing and my AI Assistant helps me refine and edit, knowing my objectives and audience.
For example: take that same Alpharetta landscaper. They’re not analyzing just one competitor — they want to work through a list of them. In a Project, they write the instructions once: “When I drop in a URL, analyze the page for SEO. Return a prioritized list of issues followed by three quick-win recommendations. Use the same format as the template in the knowledge base so I can paste it directly into a report.” From that point on, they paste a URL. That’s it. The AI already knows the job, the format, and the standard. What used to take a few setup messages now takes seconds.
This is the level that pays off for repetitive tasks. Think about what tasks you or your team do that could use an AI Assistant — writing proposals, responding to reviews, creating social posts, drafting follow-up emails. An assistant with context will save you real time and produce better “first drafts” than starting from scratch each time.
Level 3: Agents
Agents are AI that can do things, not just say things.
A basic AI assistant responds to what you ask. An agent can go further — it can take actions, use tools, pull from data sources, and string tasks together without you managing every step.
For example: extend that SEO workflow one more time. In a Project, you paste the URL and the AI analyzes it. With an agent, the landscaper writes the instructions once and steps back entirely: “On the first of each month, pull traffic and keyword data from Google Analytics and Google Search Console. Pull local rankings and competitor positions in Alpharetta and surrounding areas from BrightLocal. Compile it into a performance report using the template in my files. Give some recommendations for improved rankings. Email the report to me when it’s done.”
You’re not pasting anything. You’re not running anything. The agent has what it needs — the connections, the instructions, the template — and it does the work. You’re reading the report over coffee on the second of the month.
Automation and the connections are what make agents powerful. An agent on its own isn’t much. An agent connected to the tools and data your business already runs on — that’s where it starts to feel like you have an extra set of hands.
Because agents typically have access to documents in a designated folder, they will often use desktop apps. Claude’s CoWork feature, for example, is currently only available on the desktop. It gives the AI direct access to documents, spreadsheets, PDFs, and folders on your computer, so you can say things like “summarize all the proposals in this folder” or “find every client who expressed an interest in our new product” — and it actually goes and looks.
Keep in mind that agents still need humans. Someone has to set up the instructions — give it direction, the right context, a clear goal. And someone has to read what comes out and decide what’s useful. Agents can be improved by adjusting the instructions and knowledge base. That’s a skill, and it’s where the real advantage gets built. Remember — AI handles the middle. You handle everything else.
Skills
One more thing worth knowing about agents: many platforms let you add skills — pre-built capabilities that give the agent expertise in a specific area. Think of a skill like a specialist you call in.
A base agent is good at general tasks. Add a skill for local SEO, and it knows how to audit your Google Business Profile. Add a skill for writing proposals, and it already knows the structure and the language. You’re not starting from scratch; you’re activating something that’s already been built.
Here’s an example of a skill built for local SEO. (Click on the SKILL.md section to read the actual skill.)
Skills are one of the things that make agents genuinely useful for small businesses — even without a technical background.
Takeaway
Chat, Assistants, and Agents are the three levels most relevant to local business owners. Most AI harnesses also include an area for coding — they help developers write, review, and debug code. We’ll cover that in a separate post.
You don’t need to start with agents. Most businesses I know get real value from Level 2 alone. But understanding the whole ladder helps you know what’s possible — and where to go when you’re ready for more.
One of the best places to start is to make a list of tasks that take you and your team a long time. Perhaps there’s a pattern hiding in it — something you do repeatedly that follows the same basic structure. A few questions to help you find it:
- What do you or your team write regularly that follows the same format? Proposals, estimates, follow-up emails, review responses?
- What research or competitive analysis do you wish you had time to do — but it never makes it to the top of the list?
- What data is already sitting in your tools — your CRM, Google Analytics, your inbox — that you never have time to make sense of?
- If you could hand one recurring task to an assistant who already knew your business, what would it be?
If any of those have an obvious answer, that’s your starting point.
A good first action: subscribe to Claude Pro (or the paid tier on whichever platform you prefer). Basic Chat is available for free, but Assistants and Agents require a paid plan — and that’s where the real value is. Claude Pro runs $20/month. You can have a working assistant set up in an hour.
