Time preference seems to be forgotten on Bitcoin twitter.
Where's the BEAR?
Evidence attached for those who understand.
As a long term investor 4 year CAGR above 10% is absolutely fine
OpenClaw ecosystem bans mention of bitcoin
If you want the operational reason in one line: **crypto discussion has a high spam/scam coefficient relative to everything else, so banning it is cheaper than policing it.**
As of 1 Feb 2026, Bitcoin is about $78,082.
The most widely reported recent ATH was $125,835.92 on 6 Oct 2025.
That implies a current drawdown of:
(78,082 / 125,835.92 − 1) = −37.95% (≈ −38%) from the latest ATH.
Today’s −38% is nowhere near historical cycle bear-market depth (−77% to −83%).
It is roughly half of a typical full-cycle drawdown.
Big bull-market / mid-cycle corrections can still be savage:
Apr 2021 correction: about −53% drawdown (mid-cycle).
There are also many −20% to −30% corrections even in strong uptrends.
Today’s −38% is deeper than a routine bull pullback, but shallower than the big mid-cycle capitulations like 2021’s ~−53%.
7. Assessment culture that punishes original thought
In both arts and sciences, students learn:
Marks come from agreeing with the expected line.
Deviance from the mark scheme is dangerous.
That marks-driven pedagogy produces:
Deep suspicion of anything that does not yet have an “approved” answer.
A habit of quoting institutional scepticism (regulators, big newspapers) as proof.
So:
When mainstream econ labelled Bitcoin a bubble, that became the “mark scheme answer”.
When institutional reports fret about AI risks, that becomes the safe stance.
Genuine independent evaluation of these systems is never practised, so never developed.
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8. No meta-training in “how to explore a new tool”
Very few people are ever taught:
How to approach a new domain cold.
How to run small experiments, log results, iterate.
Instead, pedagogy assumes:
A syllabus, a textbook, a tutor, a set of worked examples.
The blank box of a wallet or chatbot is therefore terrifying. You need:
Problem-finding skills.
Tolerance for initial floundering.
Without those, the person blames the tool: “It is confusing / pointless”, rather than noticing that they never learned how to explore anything unscripted.
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9. Ideological framing delivered as catechism, not inquiry
In some humanities and social-science environments, technology, markets, and capital are introduced in a pre-framed way:
Tech = instrument of oppression.
Markets = extraction.
Corporations = enemies.
That does not make the critiques false; it makes them non-optional. You are not invited to interrogate where they apply and where they do not.
Bitcoin and AI then slot neatly into the template:
BTC = capitalist scam / climate vandalism.
AI = tool to automate exploitation / erase labour.
The judgement precedes the evidence, and the classroom rewarded that habit.
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10. Lack of cross-disciplinary stitching
Bitcoin lives at the junction of:
Computer science, cryptography, monetary history, macro, game theory, energy.
AI lives at the junction of:
Statistics, optimisation, software engineering, cognitive science, ethics, labour economics.
Most education is siloed. People are:
Good at one discipline’s stories.
I am forming a private group of UK HNWs who hold more than 10% bitcoin in their portfolio. My DMs are open. I have been seeking to influence government departments discretely since late 2020 and already help a number of HNWs on an informal and not for fee basis
It's funny how a paper loss of this scale (for a HODLer in a degree of scale since Sep 2020) no longer generates the cold sweats at night. We got over all that in the past 5 years. Now it's cerebral planning - do we move the bitcoin, equities, gold mix or not. Do we increase borrowing? Real grown up fund management for a volatile but conviction asset holder.