Thanks António José Rodrigues Rebelo

Actually, this is exactly where CDA comes in.

In Lagun’s Law, I pointed out that theories like SDT explain why motivation exists but they do not model how the internal structure needs to align for action to ignite and hold.

CDA treats motivation as necessary but not enough.

Even strong motivation can fail if internal resistance (Grain) rises or attention tethering (Anchory) weakens, which matches the hidden tensions you mentioned.

Where SDT focuses on motivation quality, CDA models whether the system itself can structurally ignite and sustain Drive.

It is not about pure or impure motivation, it is about whether the system can hold under pressure.

That is why CDA had to be built as a new field, to model effort as an emergent system output, not just as a result of motivation or emotion.

Really appreciate your comment, it points right at the structural gap CDA tries to fill.

That's a really thoughtful question, António José Rodrigues Rebelo

This is where CDA starts to move in a different direction from theories like SDT. While SDT gives us a strong understanding of why someone might care about a task or want to act, CDA asks a more structural question. It looks at whether the internal conditions are actually aligned well enough for action to begin and continue. So even when motivation is present, the action might still not launch if the structure is out of sync.

Cognitive errors like misjudging urgency or focusing attention in the wrong place can disrupt that alignment. A person may feel ready, but the system may not be. That can lead to situations where effort fails to take hold or breaks down quickly.

In some of my ongoing work, I have been looking at how unresolved tasks that sit quietly in the background of the mind can distort the way the system evaluates readiness. These tasks are not front and center, but they still affect attention, resistance, and urgency in subtle ways. This is still a developing idea, but it helps explain how mental clutter can interfere with Drive, even when motivation looks intact on the surface.

So yes, I think introducing cognitive error brings us closer to understanding how fragile and sensitive this internal system really is. Your question points right to the core of what makes this kind of structural modeling both necessary and promising.

Nikesh, I agree with the need for what you call a cognitive drive model. As you say, motivation and goals are not enough.

However, introducing cognitive error into the discussion opens another problem: How do we judge whether a decision was an error? If we base this judgement on us as observers using rational thought and reasoning, then we can all too easily fall into seeing only what we see and know, and this does not include the much more important aspect of the long term need for organisms to learn from experience. In this case, being right or wrong is secondary.

The most reliable methods of learning often come from trial and error. This is not completely true for modern day academic studies, but it is especially valid when considering the thousands of years men and women have been learning new skills.

I have read studies that claim that people are influenced by unconscious biases that lead them to make clear errors, and they back these conclusions up with experiments that take place in labs, where the results do seem clear. But in the real world, the results are different because there are so many more influences involved. Then the lab-based judgements seem to miss what matters most. Being able to learn from errors is generally a more important ability than being right.

My own thoughts on these things have changed recently after studying the two distinctive processes at the heart of quantum mechanics. This takes the discussion far afield, but I will share it briefly because I think it is in some ways relevant to your discussion.

The first process is when quantum states are in a "pure quantum state," which means there are many possibilities that all influence the outcome at the same time. This process cannot be seen directly through objective methods. In this regard, all of the influences seem similar to what we might call unconscious influences.

The second process is when one of the possibilities is selected and the "wave function" appears to collapse down to one actual event. How exactly the selection is made is still up for debate, but the results are not: the outcome of any single choice is NOT decided by outer influences alone. However, when all of the influences are known, then the pure quantum state can be described well enough to make accurate statistical predictions.

I am now wondering if cognitive choices could be following a similar process. It is a crazy idea, but I only raise it here because it has made me wonder if a cognitive drive model could be simpler than we thought.

Aside from this diversion into quantum mechanics, the process of learning through trial and error can be included as a feedback method to a simplified model for cognitive drive. Making judgements on whether choices are right or wrong should never be based on objective analysis alone because learning through trial and error is generally more important in the long run.

Hopefully this helps in some way.

Doug Marman, thanks a lot for jumping into the conversation. I really appreciate the way you laid out your thoughts. You brought up some great points, and the connection to quantum processes is honestly really interesting.

I think you’re absolutely right that we shouldn’t look at errors or missteps in a task as purely “wrong” in a rigid sense. A lot of learning does happen through trial and error, and I agree that in the real world, what counts as an “error” can be a lot more complex than what shows up in controlled lab studies.

That said, where my Cognitive Drive Architecture (CDA) model comes in is at a different level. I’m not trying to judge decisions as right or wrong, but more to look at whether the internal system is actually set up in a way that allows effort to launch and hold together. You can be motivated and care about the outcome, but if attention slips or internal resistance builds up, things still fall apart. So CDA looks at those internal conditions, what needs to line up for effort to work, and tries to model when that structure breaks down.

So I don’t see it as either-or. Learning from failure is part of the picture, but CDA is asking, “Why did the effort collapse right then?” even when motivation was there. It's more about understanding the setup behind the outcome.

I really appreciate the way you framed things. Your comment definitely added something valuable to this discussion.

Nikesh, thanks for your reply.

Your response makes sense. There are clearly lots of reasons that human beings give up too soon. One of those reasons is one I have focused my study on: Confusion.

When people are confused, they often give up. However, I have shown through my own studies that the feeling of confusion is a sign that our unconscious is learning, and if we trust the process and have patience, we will have that aha! moment when we get it. Then we can see what we need to do.

That should fit with what you are talking about.

I have found that when people learn how to accept confusion as an opportunity to learn something new, they are more willing to give it time until it makes sense to them and the what they should do becomes clear.

I once had a boss, when I was young, who said he never makes rash decisions because he learned how to wait until it was clear what to do.

To me, the way this fits into the model of cognitive drive is that until we have a way to make sense of what we are facing, we feel confused because our unconscious is sorting through all the possibilities. This process of learning how to learn new things, however, is rarely taught in schools.

Thanks for the interesting topic and the dialogue.

Doug Marman, thank you again for such a thoughtful and generous message. I really appreciate the way you look at confusion, not as a problem, but as something meaningful in the learning process. The idea that confusion can signal unconscious learning or restructuring is incredibly insightful, and I agree with you completely. Most of us are never really taught how to sit with confusion long enough to let it turn into understanding.

This actually lines up really well with how Cognitive Drive Architecture (CDA) works. In CDA, two of the core variables involved in this kind of struggle are called Flexion and Grain. Flexion is about how well a task fits with the way your mind is currently set up. During confusion, Flexion tends to be low because the task just doesn’t match your current mental structure yet. At the same time, Grain rises. That’s the internal resistance you feel—things like frustration, pressure, anxiety, or mental friction. When Flexion is low and Grain is high, the system feels unstable, and that’s often when people feel like giving up.

But what you said about trusting the unconscious really hits home. If someone is able to stay with the confusion for a little longer, without panicking or walking away, there’s often a shift. Flexion starts to improve as the mind adapts to the task. Grain starts to settle down. And that’s when people often have that “aha” moment. In CDA, we’d describe this as a realignment—when the internal system finally lines up well enough for effort to become smooth and sustainable again.

Of course, not everyone has the room to let that realignment happen. Take a student in a timed exam. They come across a hard question, and confusion sets in. Even if they understand that it's okay to be confused, their internal resistance climbs quickly because of the ticking clock. If their attention starts drifting and Flexion doesn’t recover fast enough, their Drive breaks down. They either skip the question or make a wild guess, not because they don’t care or aren’t smart, but because their system couldn’t hold together under that pressure.

Or think about someone in a creative field trying to solve a design problem. Their ideas aren't clicking, and the frustration builds. If they can stay with it, and the pressure isn't too overwhelming, they might eventually land on something brilliant. But if they’re already stretched thin with multiple unfinished tasks, which in Latent Task Architecture we call latent load, their mental bandwidth starts to break apart. In that state, confusion doesn’t feel like a gateway to insight—it just feels like one more thing pulling them under.

So yes, I absolutely agree with you. Confusion can be a powerful and even necessary part of learning. But CDA helps explain why it sometimes leads to progress and sometimes doesn’t. It all depends on how those inner variables—like Flexion, Grain, attention, and even hidden background tasks—are aligned in that moment. It’s not about right or wrong thinking. It’s about whether the system is able to stay stable long enough to make sense of what’s happening.

Thanks again for bringing your perspective into this conversation. You’re helping bring out the deeper, more human side of what this theory is really trying to model. I’m glad we’re having this dialogue.

Nikesh, I enjoyed your reply.

I like the way you show how external pressure can break the natural learning process. I've seen this as well.

When people feel threatened, they often hang onto old ideas and fight to defend them. They sound overconfident because some part of them realizes that speaking louder and more forcefully is an attempt to drown out their own concerns.

Here is another interesting thing that is related to this: When it comes to learning new things beyond our understanding, objectively thinking about the process we are going through actually gets in the way of the unconscious process that leads to breakthroughs. This surprised me when I discovered this.

And when we feel defensive, we often resort to objectivity because we place a higher priority on facing a threat that is happening right now. The unconscious learning process, on the other hand, is a process of dealing with possibilities that needs time to evolve to when it clicks for us.

This is why, when facing confusion, it is almost always best to walk away from it to let the process work unconsciously. So, the test taker, when hitting a question he can't answer, it is best to skip it and come back to that question later.

Fun stuff.

Doug Marman, your insights on confusion, unconscious learning, and the pressure to resolve things too quickly really align with how Cognitive Drive Architecture (CDA) is structured as a field.

At its core, CDA uses Lagunian Dynamics to model Drive as the outcome of internal variable alignment, especially Flexion (task fit) and Grain (resistance). During confusion, Flexion is usually low and Grain is high. If the person steps away and comes back later with more clarity, that shift is a structural reconfiguration, not just a change in mindset.

This is where Cognitive Thermostat Theory (CTT) fits in. It models the ignition moment as a control loop and explains why action might not start even when motivation is present. I’ve also been working on a completed but unpublished draft called Latent Task Architecture (LTA). It extends this by modeling how unresolved background tasks raise internal resistance or distort attention, even before ignition begins.

What you described maps closely to these dynamics. Trusting the process, letting alignment build over time, and avoiding premature forcing are all structurally valid responses. Really appreciate the depth you’re bringing to this discussion.

Nikesh, I've enjoyed the dialogue as well.

Here is another interesting parallel between quantum mechanics and what you said: There is a process called "spontaneous symmetry breaking" that describes when a change in a field happens suddenly. Just as motivation isn't enough to create cognitive ignition, as you said, the same thing is true with spontaneous symmetry breaking.

Physicists have proven that even if you know all of the influences that both attract and press in on a field, none of these things by themselves is enough to break the symmetry. In other words, the break must come from within the field. Outer forces are not enough to create a break.

A quantum wave collapse follows this same process. The wave function cannot collapse due to outer forces alone. It must come from within the relationships that exist, and it only happens when those in the relationship all come to a mutual agreement. It is sometimes called a "handshake."

This is how the physical world crosses over from the level of invisible quantum interactions, to become part of the visible world all around us. This parallels the way all of the interactions happening at the unconscious level before they cross over into cognition.

I find that fascinating.

Thanks again, Doug Marman. I really appreciate the thought you’re putting into this. What you’re describing with spontaneous symmetry breaking and quantum collapse is a powerful metaphor. But I’d argue that metaphor is where most existing analogies stop. What Cognitive Drive Architecture (CDA) does is actually complete the picture.

CDA doesn’t just say, “internal alignment is needed.” It formally defines what that alignment consists of. It splits cognitive effort into three domains:

• Ignition: whether a task starts (Primode, CAP)
• Tension: whether it sustains (Flexion, Anchory, Grain)
• Flux: whether it remains stable or breaks down moment-to-moment (Slip)

So where your analogy helps reveal the “collapse into action”, CDA provides the architecture that explains not just ignition, but how resistance builds (Grain), attention destabilizes (Anchory), and performance fluctuates (Slip). All in real time, with testable predictions and control-theoretic structure.

In fact, most motivational and cognitive models stop at ignition. They have no language for what happens after intention forms. Or why it fails mid-task even after successful ignition. CDA covers this structurally.

So yes. I think your physics analogy beautifully maps to the ignition threshold. But CDA goes further. It doesn't just describe the event of action, it models the entire lifecycle of cognitive effort, from latent hesitation to sustained work, to burnout or dropout.

Would love your thoughts on whether this kind of full system modeling feels compatible with the layered transitions you’re seeing in quantum fields. Especially how phase stability and collapse might relate to CDA’s tension/flux architecture.