[D’s Market #188] Don’t Rewrite the Rules After Entry

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When is someone truly updating their thesis, and when are they just looking for a smarter way to avoid admitting they’re wrong?

Here, the ‘original rules’ aren’t anything too complex. They are the reasons I entered a position, what could make that reason wrong, and what I promised to do if that fault point occurs.

The problem in crypto is that many mistakes don’t stem from ignorance of the rules.

I can know I need a plan before entering a trade. I know not to let a position get too large relative to my account. I know if my thesis is wrong, I must exit.

But knowing the rules when there’s no money on the line is very different from maintaining those rules when a position is in the account.

Before buying, I see the market like an observer. After buying, I see it like someone with something to protect.

What needs protection isn’t just money. It could be old decisions, research efforts, my reputation, or the feeling that I’ve seen something others haven’t.

Thus, the same bad news may not be read the same way as before.

Before buying a token, that bad news could be a sign to avoid it. After buying, it can easily be labeled as short-term noise, fear-inducing news, market misunderstanding, or even an opportunity to buy more.

It’s not because I’m losing my edge after hitting the trade button.

It’s just that from the moment I have a position, the narrative starts to add another task. It’s not just about understanding the market; it also can protect my past decisions.

The boundary lies here: real updates clarify the fault points; self-narration obscures them while actions remain unchanged.

One can start off very sharp.

I bought this project because I believe that after the incentive rewards decrease, there will still be a group of real users remaining. If rewards drop and activity falls too, it means demand isn’t strong enough. At that point, I will reduce my position or exit.

That’s the original rule.

Then rewards decrease. Active wallet numbers drop. Fees don’t increase. Trading volume also weakens. Previous users of the product start to disappear.

At this point, if there’s a real update, I need to ask: is my initial assumption still valid?

But new narratives often creep in very quickly.

The project is still early. Can’t see user return numbers yet. The community remains strong. The team is still building. The next cycle will be when this product is truly understood.

Individual statements may not be wrong.

But if after each adverse data point, the fault is pushed further away, while the action remains to hold the position, then I may not be updating my thesis anymore. I’m holding my position with a new version of the story.

This doesn’t mean that every time the thesis changes it’s wrong.

There’s new data that really strengthens the thesis. There are early-stage projects that can’t be assessed immediately by revenue, fees, or user retention. There are long-term positions built to withstand large volatility from the get-go.

The difference lies in the fact that real updates make me articulate more specifically. What has strengthened? What has weakened? What is the new fault point? If that point happens, what will I do?

Self-narration often does the opposite. It keeps the old actions intact but wraps them in a new layer of language.

This is where those who understand the market better can encounter a unique trap.

It’s not because they don’t see the risks. Sometimes they see more risks than newbies. But they also have more frameworks, more data, and more historical examples to make risks feel like temporary matters.

A new data point. A large wallet that hasn’t sold. A post from the founder. A user metric still on the rise. A story about a project that once revived after being forgotten by the market.

Individual pieces may not be wrong.

But the question to ask is: what are they doing?

Are they helping me test my thesis, or are they prolonging the feeling that my thesis is still alive?

Psychology calls part of this mechanism reason being dragged along by what one wants to believe. Ziva Kunda refers to this as motivated reasoning: when people want to reach a certain conclusion, they tend to seek, build, and evaluate beliefs that make that conclusion seem more reasonable. She also emphasizes that people can’t believe anything they want; they often need to create a seemingly rational justification for that conclusion.

Bringing it into crypto, my conclusions often aren’t just ‘this token will go up.’

It’s also: I wasn’t wrong. I didn’t buy out of fear of missing out. I didn’t ignore the rules I set for myself. I didn’t let a good story pull me in too deep.

When those needs arise, reason still operates. But it can be misallocated.

The easiest question at that point is: ‘Can I still find a reason to hold?’

With tokens that are still alive largely by expectation, community, roadmap, and incomplete data, it’s often not hard to find another reason.

The harder question is: ‘Does this new reason clarify the original thesis, or just make it easier to procrastinate exiting the position?’

If the new reason clarifies my thesis, I can often rewrite it in more specific language. What has changed? Why is it important? What is the new fault point? If that point happens, what will I do?

If the new reason only helps delay, the language often becomes fuzzier.

Need more time. The market doesn’t understand yet. The team is still building. The story remains intact. The large wallet hasn’t sold.

Those statements can be true. But they don’t, by themselves, answer the core question: has the condition that would make me wrong occurred yet?

The narrative isn’t inherently bad.

In crypto, especially in early networks, the narrative can help users, developers, liquidity, and capital all look towards a possibility that hasn’t yet accumulated enough complete data.

But for someone holding a position, the narrative is only safe when it doesn’t replace reading adverse data.

When it continuously helps me dodge the fault point, it has switched roles. It’s no longer part of the thesis. It has become an emotional cushion for the position.

The danger here isn’t listening to the story. Nor is it changing my mind after entering the trade.

The real danger is not recognizing when the narrative starts rewriting the rules I set before entering the trade.

A solid update could force me into tougher decisions: reducing my position, cutting losses, admitting I’m wrong, or rewriting my thesis with clearer conditions.

A defensive narrative often gives me the feeling that I’ve thought more deeply, while the actual action is just procrastination.

Real updates make the rules clearer.

Self-narration softens the rules at the moment the market forces me to look straight ahead.