By Hiran de Silva
Scroll through LinkedIn and you’ll see a familiar pattern.
Shocking revelations.
Confident claims.
Bold assertions with far-reaching implications.
Posts designed to provoke agreement, outrage, or applause — and comments that amplify the effect. The platform rewards engagement, not resolution. Reaction, not understanding.
And here’s the thing that almost nobody notices:
Very little of it is ever proved.
And almost none of it is placed in context.
Assertion Has Replaced Proof
We’ve quietly slipped into a world where saying something forcefully is treated as equivalent to demonstrating that it is true.
Imagine if mathematics worked this way.
Suppose Pythagoras had simply announced:
“The square of the hypotenuse equals the sum of the squares of the other two sides.”
No proof.
No geometric reasoning.
No demonstration.
Just… confidence.
Do we seriously believe that, 2,000 years later, engineers would still be using that relationship to design bridges, aircraft, and buildings — without anyone ever having verified it?
Of course not.
Proof is the entire reason the statement matters.
Yet in modern business and technology discourse, we routinely accept sweeping claims without proof — and often without even an attempt to provide one.
The Missing Ingredient: Context
There’s a second failure that’s just as damaging: the absence of context.
Many posts show a way of doing something and quietly allow the audience to infer that it is the way.
To be fair, most authors would say, if pressed, “There are many ways to do this.”
But that statement is meaningless unless followed by the real question:
In what circumstances should this approach be used — and when should it absolutely not?
Without that, what’s being presented is not guidance. It’s theatre.
The Nairobi Problem
Let’s use a deliberately absurd example.
You need to get from London to Nairobi.
How many ways are there to make that journey?
- London → Nairobi (direct)
- London → Tokyo → Nairobi
- London → Sydney → Tokyo → Nairobi
- London → Greenland → South America → Nairobi
All of these are technically valid routes.
But here’s the crucial point:
Without a use case, the list is meaningless.
If you need to be in Nairobi tomorrow afternoon for a meeting, only one of those routes is rational.
If you need to pick something up in Sydney, deliver it to Tokyo, and then go to Nairobi — suddenly a very strange route becomes logical.
The route only makes sense in context.
Explaining how to get to Nairobi via Sydney, without stating why anyone would ever want to, is not helpful. It’s misleading.
Why This Matters in Excel (and Beyond)
This is where the problem becomes serious.
Take account reconciliation demonstrations as an example.
Someone shows a clear, elegant method. It works. It’s well presented.
And yet, nowhere is it stated:
- What scale this works at
- What organisational conditions it assumes
- When it breaks down
- When a fundamentally different architecture is required
This is not a criticism of skill or intent.
It’s a critique of incompleteness.
For instance, Mark Proctor has shown one valid way of reconciling accounts. He even acknowledges there are many ways to do it.
But without saying when his demonstrated method is appropriate — and when it is not — viewers are left to assume universality where none exists.
That’s how naïve conclusions propagate.
Engagement Is Not the Same as Truth
Here’s the uncomfortable reality:
Most of these posts are not designed to lead to proof.
They are designed to attract people who already agree.
The sharpness of the rhetoric matters more than the robustness of the reasoning.
The confidence of the delivery matters more than the completeness of the model.
And when someone builds something that demonstrates the opposite — that shows the original claim only holds if you ignore scale, architecture, collaboration, or time — the response is often silence, not debate.
Because debate requires proof.
And proof requires work.
Thought Leadership, Properly Understood
Real thought leadership does not end with:
“Here is a way of doing something.”
It begins with:
- Here is the problem
- Here are the constraints
- Here are the conditions under which this approach works
- And here are the conditions under which it fails
Without that, we are not advancing understanding.
We are merely optimising for clicks.
And no amount of engagement can turn an unproven, context-free assertion into truth.
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