Helping solo marketers & small teams do the work of a bigger team. AI, content & distribution. 20 years in marketing. Free newsletter twice a week ↓
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Joined August 2007
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Brian Carl retweeted
i think we've reached the point where the cracked marketer is more in demand than the cracked engineer
Even "visibility" needs a clearer goal.
You can get cited for explaining a topic while a competitor gets recommended as the company to buy from.
Those are different outcomes.
A higher score doesn't automatically mean better recommendations or more customers.
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Before installing a skill, read its files and ask:
What job does it do?
What does it reward?
What evidence supports its advice?
Is that evidence current?
How will I verify the findings and measure the outcome I actually want?
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A skill can help you make better decisions. You still need to decide whether its advice makes sense for your business.
Read the full comparison of all five skills, plus my recommendation. You can subscribe there for future explainers:
briancarl.com/blog/five-aeo-…
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But take llms.txt.
In the versions I reviewed:
Zubair Trabzada: missing file = high-priority issue, included in scoring.
Daniel Agrici: no citation weight.
Aaron He Zhu: optional resource.
The same website will get different recommendations.
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The five skills agree on some basics:
Keep each question close to its answer. Use descriptive headings. Write sections so they can stand on their own.
Core technical SEO still matters, too. Your content needs to be accessible before AI can use it.
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I analyzed five AEO skills on GitHub.
They cover the same topic, but optimize for very different things.
Here's what I'd check before installing one:
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You can rank #1 on Google and still lose the customer to a competitor ChatGPT recommends.
For small marketing teams, that changes what “being found” means.
4 changes to make for AI search:
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4. Build a useful FAQ.
Answer the questions customers ask about your product and category in plain language.
An FAQ gives you a practical place to start. Use the same question-and-answer structure on other pages where it fits.
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I wrote the full breakdown for small marketing teams.
Read it and subscribe for practical plays twice a week:
briancarl.com/blog/will-aeo-…
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The best product decision @Muse made was having one continuous chat, instead of new chats per conversation.
Individual chats work well for deep work use cases but make no sense for a personal assistant
To the average consumer, there's no difference between an AI chatbot and a "personal agent"; it's just an implementation detail
Trying to turn it into a separate category and marketing it as such makes no sense
The 1.2 billion users of ChatGPT are just going to open the app and ask chat; they don't care if the AI is always-on, can work in the background, and/or has its own computer
Of course, giving it these abilities makes it more useful, but to a user, it'll just feel like AI got better
Nobody is going to wake up and be like "omg, I finally have a personal agent, I can be so much more efficient today"
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I think this is a mistake.
Muse was the first ai app I could see becoming a general assistant for people who aren't early adopters.
As soon as it becomes the "everything" ai app, it begins losing what made it special and what made adoption easy.
1/ muse for small businesses 📊
we found lots of people using muse to run their small business. plumbing businesses, grocery stores, farms, restaurants, and shops.
today we're launching a bunch of connectors to make that easier!
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