What The Matrix Can Teach Us About Asking Better Questions
We live in strange times where information is not only a Google search away, but often summarized for us in an AI Overview before we even click a link. AI search and research can now collapse what once took several searches and a dozen open tabs into a single response.
It reminds me of a scene from The Matrix where Neo downloads a program and suddenly knows kung fu. He has all the moves without the experience of learning them through repetition and hard work. It makes me wonder: does information that's easily found have the same weight as information we had to uncover through hours of research?
Just over 10 years ago, I spent hours combing the library at RIT, sifting through books about mass communication, radio, and diffusion of innovation theory in preparation for my thesis defense. I still have the portfolio folder I used to store dozens of online articles that I printed for reference.
I lived on Code Red Mountain Dew, Skittles, and bi-weekly breakdowns as I juggled thesis research, writing, and editing drafts of my background material before I could even start the active research portion. I learned a lot during that process that never made it into the final thesis, and I'm eternally grateful to my thesis advisors, Rudy Pugliese and Mike Saffran, for helping me through it. I may even revisit the topic one day to see whether the evidence I found still aligns with current practices.
So back to the original question: if I can get information through a one-click Google search, ChatGPT, Claude, Perplexity, or whatever your AI of choice happens to be, does it have the same value as if I'd done the research myself?
I suppose that depends on the value and depth of the information I need.
If I'm trying to find the hours for a local play café, like I did yesterday, I don't need a research project. I just need to know how long my toddler can run and slide to his heart's content before the franchise owners start giving us looks. Most of that information is readily available through a Google Business Profile or the company's website.
If I want to know how much rain my town received yesterday, the question is also relatively shallow. I probably need one or two data points. They may be slightly harder to find, but they're available if I know where to look. Neither question requires me to understand the subject particularly deeply.
What Do You Search When You Don't Know the Words?
Finding information isn't equivalent to genuine research when the depth of the question isn't equivalent. One of the biggest differences is that at the beginning of a research process, you often don't even know what to ask.
It's like searching for a product or concept you know exists but can't name. You can describe what you need. You can try different phrases. You can scroll through results hoping something looks familiar. Then you finally discover the right term, and suddenly everything opens up.
Knowing the keyword changes what you're capable of finding.
My CEO at Mingo Smart Factory understood this very well. Some of the paid-search keywords he bid on were terms that only a manufacturer who knew exactly what they were looking for would search.
We weren't fishing for everyone who had just started trying to understand a manufacturing problem. Those searches represented people much further into their research. They knew the terminology. They understood enough about the problem to ask a much more specific question, and that specificity often meant stronger conversion intent.
What Happens When AI Search Gives Us the Answer First?
That's one reason answer engine optimization (AEO) interests me. Search used to require more work from the person searching. You typed something into Google, looked through the results, opened a few pages, changed your search terms, learned some terminology, and searched again. The process of searching could actually change your understanding of what you were looking for.
Now AI search and research tools can potentially synthesize that information before you've visited the first website. An AI Overview, ChatGPT, Claude, or Perplexity can answer the initial question and introduce terminology you didn't know well enough to search for yourself.
That's incredibly useful, but it also changes the research journey. The marketing funnel starts looking less like a neat progression and more like a loop. Someone might ask a shallow question, encounter a new concept, go considerably deeper, return later with a very specific question, compare alternatives, leave, and come back again. The depth of the information they need changes at every point.
That means answer engine optimization isn't simply about making sure your company appears when someone asks a question. We also have to understand what questions people are capable of asking at different stages of their research.
Someone searching a broad question may not know your industry's terminology yet. Someone searching one of those highly specific Mingo keywords probably does. Those two people don't need the same answer, even if they're ultimately trying to solve the same problem.
The Story Behind the Strategy
Maybe the important distinction isn't that easy information has less value and difficult information has more. Sometimes I really do just need to know when the play café closes.
The difference is what I'm trying to do with the answer.
Quick retrieval is fantastic when the question is simple and the answer is factual. Deeper research requires context, connections, skepticism, follow-up questions, and sometimes the frustrating experience of discovering that the question you started with wasn't actually the question you needed to answer.
AI search can dramatically shorten the distance between a question and an answer. Answer engine optimization can help businesses make sure useful information is there when people ask.
But there's still something that happens during the messy part of research: you learn enough to ask a better question.
Neo could download kung fu because someone already knew which program to load. Most of us aren't starting there. Sometimes the hardest part is figuring out what we should be asking in the first place.
