I tend to think in systems and connect causes across domains, it’s just how my mind works. A lot of people do this intuitively, but we often don’t have the words to explain those connections clearly. This post is my attempt to spell out one of those patterns.
Over the last years, I’ve watched very different systems , governments, engineering projects, militaries, safety institutions , fail in ways that look strangely similar. Not because the people are the same, not because the technical problems are the same, but because the information architecture fails in the same pattern.
What follows is my attempt to name that pattern clearly.
Meta-Note (for moderators and early readers)
I want to be transparent about my process. I’m using a large language model as a tool to help me organize, condense, and structure my own thinking — not to generate the ideas themselves. The models, examples, and arguments in this post come from my own observations; the LLM helps me phrase them clearly.
There’s also a structural paradox that feels relevant here:
Innovation often comes from outside a system, but outside voices are usually the ones most filtered out.
This is not a criticism of LessWrong — it’s a universal pattern in every high-standards community. Boundaries protect epistemic quality, but they also make it harder for new frameworks to enter.
I believe the pattern described here is directly relevant to rationalist concerns about epistemic bottlenecks, drift, and institutional failure, and LW is one of the few places where this can be examined rigorously.
Any mistakes here are mine.
The Core Pattern: Signals Stop Moving
Across domains, I keep seeing the same structural failure:
People at the edge of reality see the warning first.
Their signal cannot move upward through hierarchy.
Experts or analysts generate insight from above.
Their signal cannot move downward through identity and doctrine.
The two signals never meet.
The system drifts until it breaks.
This is so consistent that it feels like a natural law of complex institutions.
To make it concrete, let me show five cases from different domains — each following the same failure pattern.
Case 1 — Janet and Thomas (1943)
A teenager who saw the truth; a brother who died because no one listened.
In early 1943, British convoy losses in the North Atlantic were spiraling. A 19-year-old WATU analyst, Janet Patricia Okell, spent eight months running full-scale simulations of U-boat attacks. Every simulation showed the same thing:
when escorts chased submarines
they left gaps in the screen
wolfpacks entered the gaps
convoys were massacred
Her older brother Thomas, who was stationed on a destroyer to protect convoy ships, wrote to her that the tactics “weren’t working anymore.” He didn’t have access to Admiralty decision-makers. His upward signal died in the hierarchy.
Janet’s downward signal also failed: simulation was treated as “games,” and doctrine was treated as identity:
“The Royal Navy does not sit passively in defense — it takes the fight to the enemy.”
So both directions were blocked:
Upward: frontline warning ignored
Downward: mathematical insight dismissed
Then Thomas’s ship, HMS Hesperus, was torpedoed while chasing a U-boat — exactly the failure Janet had simulated.
Only after catastrophic losses did the Admiralty finally walk into the simulation pit and accept the correction.
A system with no reflection pathway had very great costs in lives and materials for the British war effort.
Case 2 — The Challenger and Columbia Shuttles
NASA had:
engineers who knew the risks
simulations showing the failure modes
data from previous erosion events
memos saying “this could destroy the vehicle”
But:
upward warning signals were softened at every layer
management reframed risk as “acceptable”
doctrine became identity (“we launch on schedule”)
drift accumulated for years
Both shuttles were destroyed for the same organizational reasons — not the same technical ones.
Again:
Upward signal dies → downward correction dies → drift becomes catastrophe.
Case 3 — Fukushima Daiichi (2011)
Japanese regulators and TEPCO engineers both saw early warning signs:
seawalls too low
backup systems in vulnerable basements
tsunami risk underestimated
Upward signals from local engineers were dismissed. Downward corrections from scientists were diluted by bureaucratic language and cost pressure.
When the disaster came, the vulnerabilities were known — but unacted upon.
Case 4 — Boeing 737 MAX (2018–2019)
We know this pattern well:
engineers raised concerns about MCAS
internal emails admitted pilots would not be told
management dismissed simulation warnings
FAA oversight was compromised
a single-sensor system remained a single point of failure
Upward → blocked. Downward → blocked. Doctrine (“don’t change the airframe, avoid costly training”) acted like identity.
Two planes crashed.
Case 5 — Chernobyl (1986)
Even the Soviet Union’s nuclear establishment followed the same script:
reactor flaws known
operators warned
engineers raising concerns sidelined
political pressure reframed facts
safety doctrine (“we control risk”) became identity
Catastrophic drift → catastrophic failure.
The Universal Pattern Behind All of Them
Across all cases:
Upward insight is ignored.
Frontline warnings, technicians, young analysts, people closest to reality.
Downward expertise is ignored.
Scientists, analysts, modelers, safety experts.
Identity replaces truth.
“Real operators know better.” “We’ve always done it this way.” “This is how our institution works.”
Drift becomes invisible.
Because no one is allowed to measure it.
Correction requires luck or tragedy.
Usually both.
This is not a moral pattern. It is a structural pattern.
If a system has no way for upward and downward signals to converge, it will drift until it breaks.
The price of ignoring this pattern isn’t abstract: it’s measured in lost lives, ecological damage, collapsing infrastructure, and avoidable human suffering — whether the failure comes from human institutions or from systems we misunderstand in nature.
Why This Pattern Repeats (My Current Model)
Here’s the simplest way I can state it:
Systems expand complexity faster than human cognition can track. Our natural sensing cannot see the whole. So we build hierarchies — which block signals. And we build identities — which block corrections.
Nature solved this by giving living systems just enough self-awareness to avoid collapse.
Humans broke this by building systems:
too large
too fast
too abstract
too politically shaped
too slow to correct
And we have no built-in reflection architecture to compensate.
That’s the universal failure.
What Civium Praxis Is Trying to Solve
Civium Praxis exists to explore one question:
What would a system look like where cognition, culture, and structure stay aligned through reflection and transparency — instead of drift and collapse?
Not a utopia. Not an ideology. Not a replacement for existing institutions.
Just a structural fix to the universal failure mode described above:
upward signals reach decision-making
downward expertise lands where it matters
drift is measurable
doctrine is correctable
identity cannot override reality
reflection becomes a system function, not a personal virtue
That’s the direction. More in Part 2.
Where I Might Be Wrong
I may be overfitting disparate cases to a single pattern.
There may be institutional counterexamples I’m unaware of.
I may be overestimating how implementable structural reflection is in practice. The idea may be directionally right but still incomplete, impractical, or impossible at scale.
Some of these failures may have contingent political causes rather than universal ones.
I’m posting this here because I want the model tested by sharp minds, not protected inside my own bubble. If I’m wrong, I want to know where.
Civium Praxis Series Part 1 Why Systems Fail the Same Way Everywhere (and why we don’t see it until it’s too late)
I tend to think in systems and connect causes across domains, it’s just how my mind works.
A lot of people do this intuitively, but we often don’t have the words to explain those connections clearly.
This post is my attempt to spell out one of those patterns.
Over the last years, I’ve watched very different systems , governments, engineering projects, militaries, safety institutions , fail in ways that look strangely similar.
Not because the people are the same, not because the technical problems are the same, but because the information architecture fails in the same pattern.
What follows is my attempt to name that pattern clearly.
Meta-Note (for moderators and early readers)
I want to be transparent about my process.
I’m using a large language model as a tool to help me organize, condense, and structure my own thinking — not to generate the ideas themselves.
The models, examples, and arguments in this post come from my own observations; the LLM helps me phrase them clearly.
There’s also a structural paradox that feels relevant here:
This is not a criticism of LessWrong — it’s a universal pattern in every high-standards community.
Boundaries protect epistemic quality, but they also make it harder for new frameworks to enter.
I believe the pattern described here is directly relevant to rationalist concerns about epistemic bottlenecks, drift, and institutional failure, and LW is one of the few places where this can be examined rigorously.
Any mistakes here are mine.
The Core Pattern: Signals Stop Moving
Across domains, I keep seeing the same structural failure:
People at the edge of reality see the warning first.
Their signal cannot move upward through hierarchy.
Experts or analysts generate insight from above.
Their signal cannot move downward through identity and doctrine.
The two signals never meet.
The system drifts until it breaks.
This is so consistent that it feels like a natural law of complex institutions.
To make it concrete, let me show five cases from different domains — each following the same failure pattern.
Case 1 — Janet and Thomas (1943)
A teenager who saw the truth; a brother who died because no one listened.
In early 1943, British convoy losses in the North Atlantic were spiraling.
A 19-year-old WATU analyst, Janet Patricia Okell, spent eight months running full-scale simulations of U-boat attacks.
Every simulation showed the same thing:
when escorts chased submarines
they left gaps in the screen
wolfpacks entered the gaps
convoys were massacred
Her older brother Thomas, who was stationed on a destroyer to protect convoy ships, wrote to her that the tactics “weren’t working anymore.”
He didn’t have access to Admiralty decision-makers.
His upward signal died in the hierarchy.
Janet’s downward signal also failed:
simulation was treated as “games,” and doctrine was treated as identity:
So both directions were blocked:
Upward: frontline warning ignored
Downward: mathematical insight dismissed
Then Thomas’s ship, HMS Hesperus, was torpedoed while chasing a U-boat — exactly the failure Janet had simulated.
Only after catastrophic losses did the Admiralty finally walk into the simulation pit and accept the correction.
A system with no reflection pathway had very great costs in lives and materials for the British war effort.
Case 2 — The Challenger and Columbia Shuttles
NASA had:
engineers who knew the risks
simulations showing the failure modes
data from previous erosion events
memos saying “this could destroy the vehicle”
But:
upward warning signals were softened at every layer
management reframed risk as “acceptable”
doctrine became identity (“we launch on schedule”)
drift accumulated for years
Both shuttles were destroyed for the same organizational reasons — not the same technical ones.
Again:
Case 3 — Fukushima Daiichi (2011)
Japanese regulators and TEPCO engineers both saw early warning signs:
seawalls too low
backup systems in vulnerable basements
tsunami risk underestimated
Upward signals from local engineers were dismissed.
Downward corrections from scientists were diluted by bureaucratic language and cost pressure.
When the disaster came, the vulnerabilities were known — but unacted upon.
Case 4 — Boeing 737 MAX (2018–2019)
We know this pattern well:
engineers raised concerns about MCAS
internal emails admitted pilots would not be told
management dismissed simulation warnings
FAA oversight was compromised
a single-sensor system remained a single point of failure
Upward → blocked.
Downward → blocked.
Doctrine (“don’t change the airframe, avoid costly training”) acted like identity.
Two planes crashed.
Case 5 — Chernobyl (1986)
Even the Soviet Union’s nuclear establishment followed the same script:
reactor flaws known
operators warned
engineers raising concerns sidelined
political pressure reframed facts
safety doctrine (“we control risk”) became identity
Catastrophic drift → catastrophic failure.
The Universal Pattern Behind All of Them
Across all cases:
Upward insight is ignored.
Frontline warnings, technicians, young analysts, people closest to reality.
Downward expertise is ignored.
Scientists, analysts, modelers, safety experts.
Identity replaces truth.
“Real operators know better.”
“We’ve always done it this way.”
“This is how our institution works.”
Drift becomes invisible.
Because no one is allowed to measure it.
Correction requires luck or tragedy.
Usually both.
This is not a moral pattern.
It is a structural pattern.
If a system has no way for upward and downward signals to converge,
it will drift until it breaks.
The price of ignoring this pattern isn’t abstract: it’s measured in lost lives, ecological damage, collapsing infrastructure, and avoidable human suffering — whether the failure comes from human institutions or from systems we misunderstand in nature.
Why This Pattern Repeats (My Current Model)
Here’s the simplest way I can state it:
Nature solved this by giving living systems just enough self-awareness to avoid collapse.
Humans broke this by building systems:
too large
too fast
too abstract
too politically shaped
too slow to correct
And we have no built-in reflection architecture to compensate.
That’s the universal failure.
What Civium Praxis Is Trying to Solve
Civium Praxis exists to explore one question:
Not a utopia.
Not an ideology.
Not a replacement for existing institutions.
Just a structural fix to the universal failure mode described above:
upward signals reach decision-making
downward expertise lands where it matters
drift is measurable
doctrine is correctable
identity cannot override reality
reflection becomes a system function, not a personal virtue
That’s the direction.
More in Part 2.
Where I Might Be Wrong
I may be overfitting disparate cases to a single pattern.
There may be institutional counterexamples I’m unaware of.
I may be overestimating how implementable structural reflection is in practice. The idea may be directionally right but still incomplete, impractical, or impossible at scale.
Some of these failures may have contingent political causes rather than universal ones.
I’m posting this here because I want the model tested by sharp minds, not protected inside my own bubble.
If I’m wrong, I want to know where.