Adviserry vs. ChatGPT: Why a Generic AI Isn't a Business Advisor
Adviserry vs. ChatGPT: Why a Generic AI Isn't a Business Advisor
I've done it. I'm guessing you've done it. You have a real business question — something specific, something that matters — and you open a chat window and type it in. You get back something that sounds smart, cites some statistics, uses the word "leverage" at least twice, and is completely devoid of any actual opinion.
That's not bad AI. That's the wrong tool.
[Image suggestion: A person staring at a laptop with a generic AI response on screen, looking unimpressed — maybe a light comic-style illustration]
ChatGPT, Claude, Gemini — these are general-purpose AI assistants. They're incredible at a lot of things. Summarizing, drafting, coding, explaining. But when you ask a general-purpose AI "should I raise prices on my SaaS product?", it gives you the Wikipedia version of the answer. Here are the considerations. Here are the tradeoffs. Here is what the research generally suggests. Here is your homework.
It doesn't know what Alex Hormozi actually said about this — specifically, in the context of service businesses with existing customer bases. It doesn't know what Lenny Rachitsky benchmarks suggest for your product category. It doesn't know your pricing history, your churn curve, or your ICP.
So it gives you something that's technically correct and functionally useless.
The difference between a library and an advisor.
A library has all the books. It doesn't tell you which ones to read, or how they apply to your specific situation. It doesn't say, "given what you told me about your positioning and your churn rate, here's the most relevant thing Hormozi said about this, and here's where I'd push back on his framework for your context."
An AI advisory board built on your specific sources — the newsletters you actually subscribe to, the experts you actually trust, uploaded in the context of your actual business — is the advisor, not the library.
When you ask Adviserry "should I raise prices?", it draws on what your curated board of experts has written about pricing. It knows you've added Hormozi, Lenny, and maybe Jason Lemkin. It has context about your business from whatever you've uploaded. It synthesizes their perspectives and gives you a sourced, specific answer — not a framework, an answer.
Generic inputs get generic outputs. Always.
This is the part that frustrates me about the "just use ChatGPT" crowd. Yes, a skilled prompter can get useful answers out of a general-purpose AI. But you have to supply all the context yourself, every single time. There's no memory of your business. There's no curated source set. There's no way to say "what does my board think about this?" because there is no board.
The people who get the most out of general AI tools spend enormous amounts of time on prompting. Good for them. But that's a skill most SMB founders don't have, don't want to develop, and shouldn't have to.
Your advisory board should already know the context. That's what makes it a board and not a search engine.
Keep Reading:
- Adviserry vs. Notion AI vs. Obsidian — comparing Adviserry to other knowledge tools
- How to Set Up Your First Adviserry Board in 5 Minutes — try the difference yourself
- How to Cross-Reference Advice From Multiple Experts — the power of synthesized expert perspectives
Image Prompts:
- Side-by-side chat windows: on the left, a generic AI chat with a vague, bullet-pointed response; on the right, an Adviserry-style interface showing a response with specific expert names, source callouts, and a crisp recommendation. Modern UI mockup style, clean and editorial.
- A visual metaphor: a library with infinite rows of books (labeled "Generic AI") vs. a small round boardroom table with 5 named chairs and a whiteboard (labeled "AI Advisory Board"). Simple, warm illustration style.
