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Almost Timely News: 🗞️ Setting the Record Straight on AI Optimization (2025-06-22)
Lies, damn lies, and snake oil
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Almost Timely News: 🗞️ Setting the Record Straight on AI Optimization (2025-06-22) :: View in Browser
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95% of this week's newsletter was generated by me, the human. You will see bountiful AI outputs in the video, and you will see an output from Anthropic Claude in the text. Learn why this kind of disclosure is a good idea and might be required for anyone doing business in any capacity with the EU in the near future.
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What's On My Mind: Setting the Record Straight on AI Optimization
Okay, let's clear the air on this whole AI optimization and the twisted, contorted, crazy space of AI optimization. There are so many weird, confusing names for all of this that it sounds like either a child's nursery rhyme or IKEA furniture names - GAIO, GEO, AIO, AEO, CSEO (conversational search/SEO), etc.
We need to lay down some basics so it's clear what's real and what's not, something you can take to your stakeholders when they ask - and a way to cut through a lot of the snake oil.
Part 1: Definitions
First, let's be clear what we're talking about. Fundamentally, what everyone wants to know is this:
Can we tell how much traffic (and therefore prospects, leads, opportunities, sales, and ultimately revenue) generative AI in all its incarnations is sending us, directly or indirectly?
From that blanket statement, we decompose into three major areas.
What do LLMs/generative AI models know about us? How do they talk about us when asked? How are we being recommended by AI models themselves?
How do AI-enabled search tools like Google AI Overviews and Google AI Mode recommend us and send traffic to us?
How do AI replacements for search like ChatGPT, Claude, Perplexity, Gemini, etc. recommend us and send traffic to us?
And from there, we ask the logical question: how can we get these different systems to recommend us more?
When we talk about whatever the heck we're calling this - for the rest of this newsletter I'm sticking with AI optimziation - we're really talking about the three whats.
What is it?
So what? Why do we care?
Now what? What do we do about it?
You'll note something really important. The three major areas all tend to get lumped together: AI models, AI-enabled search, AI replacements for search.
They should not be. They are not the same. This will become apparent in part 3.
Part 2: What You Cannot Know
This is a fundamental principle:
AI is not search.
Let's repeat that for the folks in the back who weren't paying attention.
AI IS NOT SEARCH.
When was the last time you fired up ChatGPT (or the AI tool of your choice) and typed in something barely coherent like "best marketing firm boston"?
Probably never. That's how we Googled for things in the past. That's not how most people use AI. Hell, a fair number of people have almost-human relationships with their chat tools of choice, giving them pet names, talking to them as if they were real people.
What this means is that it's nearly impossible to predict with any meaningful accuracy what someone's likely to type in a chat with an AI model. Let's look at an example. Using OpenAI's Platform - which allows you direct, nearly uncensored access to the models that power tools like ChatGPT, let's ask about PR firms in Boston.
I asked it this prompt:
"Let's talk about PR firms in Boston. My company needs a new PR firm to grow our share of mind. We're an AI consulting firm. What PR firms in Boston would be a good fit for us?"
o4-mini
Racepoint Global
LaunchSquad
Inkhouse
Sutherland Weston
Hotwire
Finn Partners
Sloane & Company
GPT-4.1
SHIFT Communications
PAN Communications
Rally Point Public Relations
INK Communications Co.
March Communications
Denterlein
Walker Sands
GPT-4o
PAN Communications
Matter Communications
March Communications
Racepoint Global
Velir
SHIFT Communications
You can see just within OpenAI's own family of models, via the API, I get wildly different results. The most powerful reasoning model available by API, the thinking model, comes up with very, very different results - but even GPT-4o and GPT-4.1 come up with different results.
This is what the models themselves know. When you use any tool that connects to OpenAI's APIs, you are using this version of their AI (as opposed to the ChatGPT web interface, which we'll talk about in a bit).
Now, suppose I change just a couple of words in the prompt, something reasonable but semantically identical. What if I chop off the first sentence, for a more direct prompt:
"My company needs a new PR firm to grow our share of mind. We're an AI consulting firm. What PR firms in Boston would be a good fit for us?"
What do we get?
o4-mini
Salt Communications
PAN Communications
SHIFT Communications
Matter Communications
Racepoint Global
Highwire
Argyle PR
GPT-4.1
Inkhouse
SHIFT Communications
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