The Answer Wasn’t Wrong. The Question Was.
How a forgotten seahorse revealed a much bigger lesson about inquiry, systems, and why smart people still miss what matters
A Small Question That Wouldn’t Settle
I recently went down what looked, on the surface, like a trivial rabbit hole. The kind of question you expect the internet to answer quickly and then forget about five minutes later.
I had a clear memory of seahorse imagery being used in early messaging platforms: Messenger, Skype, BlackBerry Messenger. Not once or twice, but often enough that it felt familiar and settled. So I asked where it came from, assuming there would be a straightforward answer (and I wanted to get to the bottom of all the fuss surrounding the discussion).
The responses from the internet and LLMs were clean, confident, and technically correct. No operating system had ever used a seahorse as an icon. No messaging platform had branded itself with one. There was no such thing as an official Unicode seahorse emoji. The only officially documented use anyone could point to was GNOME’s Seahorse security tool for encryption and key management (which I couldn’t find on line).
From a factual standpoint, the case was closed. And yet, the answers didn’t resolve the discomfort. Something still felt unfinished and I couldn’t let it go. Why? Because I remembered seahorses. That’s when it became clear that the issue wasn’t memory. It was my question.
When Correct Answers Don’t Satisfy
Looking back, the original question was framed narrowly and precisely:
Which operating systems or services used a seahorse icon or emoji?
On its face, that seems like a perfectly reasonable question. But embedded within it were several quiet constraints that I hadn’t noticed at the time. It assumed the symbol was official. It assumed it was formally classified as an icon or an emoji. It assumed the relevant layer was operating system or service identity. Within those boundaries, the answers I received were accurate. They were also incomplete (and wholly unsatisfying). What I was remembering didn’t live at the level of system icons or Unicode standards. It lived somewhere else entirely, in the interaction layer.
Specifically, in stickers.
Seahorse stickers existed. They were used frequently. They were socially meaningful. They showed up repeatedly in everyday conversation. They, however, functioned like emojis, even though they were not emojis in the technical sense.
Once that layer was acknowledged, the cognitive tension disappeared almost instantly. Nothing about the facts had changed. The explanation had simply moved to where the experience actually lived.
Was This Confirmation Bias?
At that point, a reasonable self-challenge emerged. Was I simply searching for an answer that fit my memory? Was this confirmation bias at work: was I unwilling to let go of a belief once it had formed? It’s a fair question, and one worth asking any time memory and evidence seem misaligned. It also forced me to dig deeper.
The honest answer is partially, but not in the way that term is usually applied.
This wasn’t a case of ignoring evidence or rejecting inconvenient facts. Every technically correct answer I received was accepted without resistance. What remained unresolved for me was not truth, but the explanation. And that distinction matters more than I or we often admit.
Memory vs Category Error
What I was holding was a phenomenological memory — a memory of experience:
“I encountered seahorse imagery repeatedly in messaging.”
What I misidentified was the category it belonged to. I assumed it had to be an emoji. Or a system icon. Or an official service Unicode symbol. Once that assumption was in place, every answer that said “no such emoji or icon existed” felt wrong, not because it contradicted facts, but because it failed to explain my lived experience (how often does that happen to us?).
That’s not how classic confirmation bias works. Confirmation bias usually sounds like this:
“Which facts support what I already believe?”
What was actually happening here to me in this cases sounded more like this:
“Why does this explanation fail to account for what I experienced?”
That’s not narrowing the search space. It’s expanding it until the explanation finally fits the phenomenon.
Anchoring to the Wrong Layer
The real issue I had to discover was anchoring to the wrong abstraction layer. The answers I was receiving were operating at the level of formal system design: standards, branding, and official artifacts. The memory, however, lived at the level of daily interaction artifacts: the things people actually see, use, and repeat in practice.
Once the question shifted from “emoji or icon?” to “where did users encounter this imagery in practice?”, the issue resolved itself immediately. There was no defensiveness, no argument, no need to persuade anyone.
That shift is an important diagnostic signal:
When tension disappears immediately after reframing the question, the problem was not bias — it was scope.
Why This Happens So Often
This kind of confusion is more common than we realize, largely because modern systems are layered while our questions rarely are.
Digital platforms deliberately blur boundaries. Emojis and stickers share the same picker. Both replace text. Both convey emotion. Both are reused habitually. From a user’s perspective, the distinction barely matters (until it does).
Memory doesn’t store file formats or standards. Memory stores function.
But when we ask questions that privilege taxonomy over experience, we end up with answers that are technically correct and practically unsatisfying. The system answers the question we asked, not the one we actually needed answered.
This Pattern Shows Up Everywhere
For me, this isn’t really about emojis. The same failure mode shows up constantly in organizational life. We ask questions like:
Is this a policy problem or a culture problem?
Is this a performance issue or a capability gap?
Is the board aligned?
Often, the answers are reasonable within the frame. And often, they still miss what’s actually going on.
In each case, the debate happens inside a structure that quietly excludes the real explanation. The organization argues about categories while the system behavior continues unchanged.
When Technically Correct Answers Become Governance Failures
This pattern, receiving correct answers that fail to explain, is not confined to digital interfaces. It is one of the most common and costly failure modes in governance, risk, and assurance.
Boards and executives routinely receive answers that are factually accurate, methodologically sound, and professionally delivered, yet leave a persistent sense that something important is being missed. When this happens, the instinct is often to question the data, the competence of management, or the quality of the analysis.
More often than not, the issue lies elsewhere. The question itself is aimed at the wrong layer of the system. Boardroom conversations are frequently framed this way:
Is this a strategy problem or an execution problem?
A people issue or a process issue?
A culture problem or a controls problem?
Each of these frames forces a binary choice onto phenomena that are inherently multi-layered. Within the imposed frame, the answers can be perfectly correct - and still dangerously incomplete (that’s where our sense of unease comes from). This is how boards end up governing shadows.
Risk reports describe control effectiveness while ignoring incentive structures. Strategy updates report progress against milestones while ignoring erosion of adaptive capacity. Culture surveys show “strong engagement” while decision-making quality quietly degrades. None of these reports are wrong. They are simply answering the wrong question.
How Boards Quietly Constrain Their Own Insight
The governance failure doesn’t occur because management is misleading the board. It occurs because the board has unconsciously constrained the answer space. By anchoring inquiry to formal categories - strategy, risk, culture, performance - directors filter out the interaction-level dynamics where real system behavior emerges. The result is familiar:
High alignment and low coherence.
Strong controls and weak judgment.
Clear accountability and poor sense-making.
The lesson mirrors the seahorse example exactly. When an answer feels correct but unsatisfying, the problem is rarely bias or bad faith. It is almost always question architecture.
Boards that learn to surface this early, by asking “what layer are we actually governing right now?”, and move from oversight to stewardship. Those that don’t often find themselves repeatedly fixing the wrong thing, with increasing precision and diminishing effect.
A Boardroom Vignette: All the Right Answers, None of the Relief (Part 1)
The board is forty minutes into the agenda and already behind. A slide titled “Root Cause Analysis” sits on the screen as the CEO finishes speaking.
“So,” the Chair says, glancing down the table, “is this fundamentally a strategy issue or an execution issue?”
The COO leans forward. “Execution,” she says. “The strategy is sound. The teams struggled to land it consistently.”
A director nods. “That aligns with what I’m seeing. This feels like a performance issue, not a strategy reset.”
Another director jumps in. “But is this really about performance? Or is it a capability gap? Do we actually have the skills to execute what we’re asking for?”
The CHRO responds smoothly. Engagement scores are strong. Capability assessments are improving. From a people standpoint, things look fine.
The frame shifts again. Process. Decision rights. Controls. Audit confirmation. Clean slides. Reassuring answers.
No one disagrees. No one challenges the data. Everything being said is reasonable. And yet, something still doesn’t sit right.
The Chair finally says it out loud. “So just to be clear, we don’t have a strategy problem, an execution problem, a people problem, a process problem, or a controls problem.”
A pause.
“But results are deteriorating,” he continues, “decision-making feels slower, and management seems increasingly cautious in moments that matter.”
One director finally says what everyone is thinking. “All the answers make sense. But none of them explain what it feels like is happening in the system.”
The Chair nods. “Exactly.” The categories are exhausted. The reports are accurate. What’s missing isn’t information. It’s the right question.
A Boardroom Vignette: The Question That Changes the Room (Part 2)
After the break, the slides haven’t changed. The data hasn’t changed. The agenda hasn’t changed.
But the Chair doesn’t go back to the deck.
“I want to pause the categorization,” they say. “We’ve spent an hour deciding which bucket this fits into. Before we continue, I want to ask something simpler.”
They turn to the CEO.
“When was the last time the organization made a confident decision under uncertainty — and stuck with it long enough to learn from it?”
The room shifts.
“Probably eighteen months ago,” the CEO admits. “Since then, we’ve optimized and de-risked, but we haven’t really committed.”
Suddenly, the earlier answers make sense. Not as explanations, but as symptoms.
The issue was never alignment. It was whether the system still had the capacity to decide, absorb uncertainty, and move. What it talk was expanding the category of questioning..
A Note for Chairs: Interrupting “Correct but Hollow” Conversations
When answers start to feel simultaneously correct and unsatisfying, our instinct is to push harder for clarity, more data, or sharper accountability. And that usually makes things worse. What is needed is not more information, but a shift in the question.
Here are five interventions Chairs can use in the moment to shift the conversation without escalating tension:
Name the discomfort
“Everything we’re hearing makes sense—and yet I don’t feel clearer. Does anyone else feel that?”Pause categorization
“Let’s stop deciding what bucket this belongs in for a moment.”Shift the layer
“Instead of asking what this is, let’s ask where in the system it’s showing up.”Ask for lived experience
“When did this first become noticeable in day-to-day decisions?”Test coherence, not alignment
“Do these answers, taken together, explain how the organization is actually behaving?”
None of these questions accuse management. None challenge competence or integrity. They simply reopen the answer space. That is often all that is required.
A Simple Diagnostic for Directors
When a board feels busy, aligned, and informed, but oddly ineffective, a simple test helps.
Did today’s discussion explain why the organization is behaving the way it is?
Did it surface interaction-level dynamics like confidence, risk posture, or learning speed?
Did it change how the board will govern differently next quarter?
If not, the issue is rarely performance or information quality. The issue is that the board is governing at the wrong layer.
The Real Takeaway
This wasn’t a lesson about emojis, stickers, or seahorses. It was a reminder that precision without scope is a liability. You can have correct facts, credible experts, and clean answers, and still miss the truth if the question is aimed at the wrong layer of the system. Sometimes the answer has been there all along. You just didn’t ask it where it lived.
Postscript: Why This Is Not A Case of the Mandela Effect
One thing I noted as I went down the seahorse sticker rabbit hole, was how often the Mandela Effect was used to explain my experience away. The Mandela Effect refers to a collective false memory: a large group of people confidently remembering something that verifiably never occurred. The key features are:
The memory is factually incorrect
It persists despite clear disconfirming evidence
It is often collectively reinforced
The correction produces resistance or rationalization
Classic examples are misremembered brand spellings or famous quotes that never existed in the form people recall. The seahorse example fails every one of those tests.
My Memory Was Not False
At no point did my memory assert something that definitively never happened. I did not insist that:
A specific app used a seahorse as its logo
A particular OS shipped with a seahorse icon
A documented emoji standard included a seahorse at a specific time
What I remembered was encountering seahorse imagery repeatedly in messaging contexts. That memory was accurate. The imagery existed. It was encountered. It was reused. It was socially meaningful. What I was initially unclear about stating was how it was implemented, not whether it existed. That alone disqualifies the case of the seahorse sticker from being a Mandela Effect case.
The Error Was Categorical, Not Factual
Mandela Effect errors are errors of fact. This was an error of classification. I placed a real phenomenon into the wrong category:
I assumed “emoji” instead of “sticker”
I assumed “official icon” instead of “interaction artifact”
I assumed “system layer” instead of “user-experience layer”
Once the category shifted, the memory snapped cleanly into place (and as we all know, assuming makes an ass out of you and me. But it this case it was me ;-). That is the opposite of how false memories behave. False memories tend to collapse under scrutiny. My memory clarified under scrutiny.
Why Mandela Effect Gets Over-Applied
The Mandela Effect has become a cultural shortcut for explaining any moment where memory and documentation don’t line up (and its mostly applied incorrectly). But that shortcut hides several more common, and more interesting, phenomena:
Layer confusion (system vs interaction)
Taxonomy drift (emoji vs sticker)
Function-based memory (what something did, not what it was called)
UX-induced conflation (design intentionally blurring categories)
My memory sits squarely in this territory. Modern digital systems encourage this kind of conflation. Emojis, stickers, GIFs, and reactions live in the same UI space and serve the same communicative purpose. Expecting users to maintain strict categorical boundaries is unrealistic. Calling this Mandela Effect would be blaming memory for a design choice.
A Key Diagnostic Difference
Here’s a simple test that separates Mandela Effect from what happened here:
Mandela Effect: “Even after seeing proof, I still believe it happened.”
What happened here: “Once the category shifted, everything made sense immediately.”
The moment I reframed the question, there was no defensiveness, no clinging to belief, no alternate rationalization. I didn’t protect the memory. I updated the model. That’s not a cognitive failure. That’s healthy sense-making.
The Deeper Insight (And Why This Matters)
Labeling this as the Mandela Effect would actually obscure the real lesson. The lesson isn’t about unreliable memory. It’s about how systems shape recall by collapsing distinctions that only matter to designers, not users.
My experience demonstrates:
Memory tracks interaction and meaning
Systems are layered, but memory is not
Misalignment arises when we ask questions at the wrong layer
This is the same mechanism that causes boards to misdiagnose problems, organizations to chase symptoms, and audits to certify compliance while missing risk.
In other words, this wasn’t a glitch in my memory. It was a signal that the question architecture was misaligned with lived experience.
Bottom Line
This was not the Mandela Effect.
The memory was real
The phenomenon existed
The correction was immediate once the category changed
The discomfort came from explanatory failure, not cognitive distortion
What failed was not not my recall. What failed, briefly, was the frame I used to interrogate it. And recognizing that difference is exactly the kind of systems-level insight I am trying to develop with SuperCoolandHyperCritical.
I immediately thought, Oh, he must be talking about the Mandela Effect, and then you promptly put me in my place 😂 Really great piece that clearly differentiates the two experiences.