Episode Summary:
In episode 60, Peter Joseph continues his module-by-module exploration of Integral with a walkthrough of the Open Access Design System (OAD) — one of Integral’s five subsystems and the network’s collective engineering, architectural, and creative intelligence.
OAD replaces the R&D function of private enterprise with a global design commons, where every design is open, every improvement benefits everyone, and ecological, lifecycle, and labor implications are made computable upfront.
Walking through all ten modules of the OAD pipeline — from structured submission through collaborative refinement, material and ecological coefficient analysis, lifecycle and maintainability modeling, feasibility simulation, labor decomposition, systems integration, optimization, certification, and global commons archival — the episode also shows how OAD generates the structured design intelligence that COS and ITC depend on for non-market production coordination and access valuation, and how the entire pipeline functions as a self-correcting design organism that learns from real-world deployment feedback over time.

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TRANSCRIPT:

Good afternoon, good evening, good morning everybody. This is Peter Joseph and welcome to Revolution Now, episode 60.

In the last podcast, we talked a great deal about the collaborative design system, one of Integral’s five systems, which had to do with decision making in the system. By the way, if you’re new here, please note that what I’m speaking of can be found at integralcollective.io, which is a parallel economy project based on the conclusion that we can no longer trust the traditional mechanics of activism to adapt society in a positive way, and we need to build our way out. Literally.

Gandhi once said, “Become the change you wish to see in the world.” Well, this is it. Buckminster Fuller once said, “You never change things by fighting the existing reality to change something, build a new model that makes the existing model obsolete.” Well, as far as I’m concerned, this is it.

I don’t mean to sound dramatic or demeaning to all those people out there once again that are in the activist community pushing for regulation as usual, policy change as usual, which is again, essentially what everyone is doing. But the forces of power are against you. And I mean that in the most technical way.

Some may be familiar with comments recently coming out of Silicon Valley by massive billionaire tech degenerates, such as Palantir, the Palantir manifesto, which you’ll find a statement that was put out, almost like a troll in a way, but I think they’re very serious. Quote: “Public servants need not be our priests. Any business that compensates its employees in the way that the federal government compensates public servants would struggle to survive.”

What is implied here? Amongst many other dark techno-fascistic ideas in the commentary, there’s an implication, an old one, a repetition of what has been occurring and oscillating by those of great wealth and power, that the world should be run like a business and only like a business. And what is business? Business is a fascistic structure.

And as the world continues to adapt itself with accelerating technological noise and various contradictions within the market economy, such as human labor being replaced by artificial intelligence and robotics. I can assure everyone none of this stuff is going to be positive in the end. Why? Because in part of who gravitates to the top of the hierarchy in this kind of economic system and the psychological distortion they inevitably embrace. On average, the system produces and amplifies sociopaths and psychopaths, and they become your leaders in the corporate government sphere.

If I was to distill all of this down, you basically have two feedback forces that will continue to reinforce everything that is negative, pushing the death spiral. The inherent endogenous needs of the market economy to reproduce itself, which means infinite growth, vast inequity in order to fuel the imbalance required to continue the patterns of market exploitation and needed scarcity, which translates as a direct result of the actions of business itself, make no mistake, into poverty, severe levels of damaging socioeconomic stress, class-linked mortality. The lower, in fact, you get on the hierarchy, it just gets worse and worse.

And when you put those two things together, what you have is a condition of constant, societal oppression as a matter of systemic economic unfolding compounded by increased ecological decline, which, rest assured, will continue to harm the poor much, much faster than the rich, even though everyone will be vulnerable in the end. The economic root of our civilization will still proceed to collapse the entire ecosystem or blow itself up on the way due to competitive requirements of markets.

Now beyond that, we have this powerful cultural loop rooted in those that hold all the cards and continue to hold more and more. Again, the billionaire ownership government class. They’re one entity and their job is also to reproduce themselves. They are conditioned to believe everything that has benefited them is what should benefit the rest of the world. And therefore, business and business alone should be the governing apparatus for everything.

This is the old world, Orthodox libertarian delusion once again. It’s nothing new, even though it is full of vast downstream contradictions, which should have debunked it years ago, which elevate everything into a far more rigid mechanism than anything people could call free market in traditional terms, which is precisely why there’s no such thing as a free market, nor could there be. The free market as terminology “decoded” is just a gateway concept into fascistic hierarchical behavior, which is precisely what the core logic associated with free enterprise produces without exception. And if you’re wondering why some countries do better than others, it’s because they’re on a different tier of the global hierarchy reality. Gravitation is still universally the same.

And so, while activists should be out there trying to take out these tumors, what integral attempts to do is go after the actual cancer. We are going to begin replacement of the existing socioeconomic structure with one that actually makes environmental and social sense. One that is not related to business at all. The dynamics of what we understand as business today have absolutely no place in the vocabulary of a sustainable, humane economic system. They are not even in the same universe.

Our misguided existence in the world today, as of the early 20th century, is premised on a dramatic mistake in our cultural evolution put forward roughly 10,000 years ago. We took the wrong path when we began to settle with agriculture and incorporate specialized labor, trying to figure out how to make that work. We did not understand the dynamics we were putting forward through scarcity exploitation in market trade as it is an unavoidable factor, while paradoxically pushing infinite growth to keep jobs.

Please understand, these flaws have been with us in fact, for 1000s of years. Permutations such as feudalism had just been variations on a theme, but it took the modern era to bring these latent flaws to the surface, particularly on the environmental front. And the predicament we are in now is truly catastrophic.

So make no mistake, business is the problem. Markets are the problem. Market trade, money, this is the problem. You can call it capitalism or whatever, but that’s more of a fragmented institutional perspective. Anyone that debases capitalism without debasing the actual technical mechanics, which is scarcity-exploiting competitive market trade, is wrong. And it’s truly tragic because 99% of the people out there that claim they’re anti-capitalist don’t even know what they are against. You’re looking at legions of people that are talking about how much they oppose capitalism, and they build up this cognitive dissonance, or not even a cognitive dissonance, ’cause they’re not even aware of the actual problem. They talk about the greed of corporations, but what about your own incentive towards personal gain, which over the course of a certain perspective, looks like greed.

So anyway, you get the point; enough of that, but I have to always remind people of this.

Let’s go back now to what we did in the prior podcast and talk about in summation, the CDS, which we covered in detail. What was module one through 10?

Module one was structured intake from both people of the node and system alerts that need attention. These can be problems recognized that need resolution or proposals for possible implementation. The former applies to human intake and system alert intake while the latter proposals are initiated by people.

And then module two takes this information, runs analysis to try and get a handle on any overlapping submissions to see how they relate. If need be filtering and parsing module one submissions into a structured data object or objects when dealing with multiple novel submissions over the given course of time.

And then it goes to module three, which takes that output and uses it to extract data from all the other systems. In the interest to figure out the general landscape or ecosystem of the problem or proposal at hand, such as related history, repairs, schematics, dependencies, and so forth. And with that knowledge, the orchestrator of the module runs a bridge process that then outputs novel automated proposals based on the existing information so far, assuming the issue in question is indeed a problem that needs resolution.

In turn, those suggestions along with the data extracted from module three move to module four, which examines everything in order to find potential constraints that pertain to the solutions or proposals that have been put forward thus far. Both human generated input into module one, along with solution proposals that have been automated in the bridge step after module three, which brings everything now to module five.

This is the core deliberation space for people of the node to engage in the effort to find resolution or development. Various analytical tools are utilized in this process, as covered in the last podcast in detail, and debate efforts coalesce into a series of preference gradients and objection maps, which form the components of the calculation to be run by module six.

Module six then does its processing, and again, I talked about this in great deal in the prior podcast, sorry for this rundown, but I think it’s important, and outputs one of three directives, module six. Approve, revised, or escalate to Module 9. Module 6 may have one scenario to deal with, or multiple scenarios, that need to be eliminated, so to speak, for the final decision, whittling it all down for the proper decision. It is at the discretion of people in Module 5 to figure out what moves forward after attempting variety reduction through discussion in regard to scenarios.

And if something is approved, assuming it’s a singular scenario, it gets documented by Module 7 after approval, which puts it on the record, and then Module 8 facilitates its implementation, incorporating data flows to the other worst systems. If there are multiple scenarios approved, the orchestrator comes in as an intermediary step once again and takes the highest quality of those scenarios by the rank that Module 6 produced and decides the winning scenario.

Various other combinations can play out such as with revisions, where all forms of revision go back to Module 5 to be addressed by everyone, to either be dropped, further debated, or improved in order to hopefully pass requirements of Module 6 in the next cycle.

In the event of a deadlock, so to speak, things are escalated to Module 9, which incorporates a more manual process. Potentially Stafford Beer’s “Syntegrity” method, which again was talked about in the prior podcast, while a second type of escalation is triggered from a more manual appeal process due to value conflicts, which is contingent on the node’s constitutional development in the effort to make sure heavy disagreement by any part of the node is respectfully taken into account.

And notice folks heat those nuanced caveats and tend to hone in on those, but I really think for the most part, those highly conditional outcomes we just spoke about are really edge cases because the purpose of the CDS is not to debate the merits of things like abortion or trans rights or other complex cultural issues. The CDS has a primary function and that has to do with economic organization and thought.

It’s important to note that people that come into integral, by the way, which once again starts small as a project and then scales in terms of application and complexity, will do so with a shared intent. Meaning everybody is far more on the same page than we would see in the case of common democratic imposition, where a system is just imposed on a population and some of the population might not like it. That’s not what we’re doing, obviously. Which is a massive strength, by the way, not just in the focus of the CDS, but also in our ability to get things done in the total system, keeping focus.

People often forget that the core problem is really the terrible frame of reference that’s been conditioned upon people as they try to decide what is important to them as a democratic agent. Loaded with misinformation and misdirection, which of course is the essential nature of the political game being played out there. While this is fundamental to representative democracy, it’s important to remember that honesty is nothing to do with communication occurring from political parties or special interests. They are there to manipulate for the sake of power wealth, and this is just what a competitive ecosystem produces on the administrative level. Political communication is manipulative communication and nothing more.

The CDS, on the other hand, does not have vested interests, as there is no point to it. And with a fundamentally economic focus once again, we remove so much of the noise that plagues modern consensus making in the world today.

All that said, let’s now explore Integral’s OAD, the Open Access Design System.

So, of all the aspects of Integral that really have the capacity to fundamentally make market economics obsolete, this is the heart. The OAD replaces the research and development function of private enterprise, eliminating intellectual property and restrictive patents. It is the engineering backbone of Integral. A continuously improving design commons where every design, specification, and technical breakdown is openly shared, version controlled, and recursively refined.

Put another way, this is where an Integral node and by extension the entire global Integral network designs and refines its economic creations: goods and services.

Broadly, the OAD does three things at once. It is a design workflow: intake, refinement, certification. It is a knowledge commons, a searchable archive of every certified item and supporting data to be shared. And it is a critical data source, computational input for two downstream economic subsystems, cooperative organization system, the COS, which plans and executes production, and Integral time credits, the ITC, which calculates access values.

So to be clear, it’s not just about the designs, it’s also about the critical data that pertain to those designs.

Okay, so now I’m going to walk through all 10 modules of the OAD. However, before we begin, I want to spend a moment on why the OAD is the way it is as far as broad focus, because the architecture makes the most sense once you understand what it’s trying to correct.

And this gets to something I’ve talked about at length before, true economic context of design and production. It’s not enough to simply design a good with common sense parameters such as longevity and recyclability in some vague sense. True economic design has to absolutely account for the larger order ecosystem it is being brought into and the effect it has on it.

This is the great failure of market-based production with all of its backward incentives. Except, of course, for the metric scarcity, vaguely – wildly distorted, and with no real utility except for price manipulation when you really, really think about it. Sure, if something gets scarce due to physical pressure, it will raise price so it becomes more restrictive for continued consumption. But by the time that happens, it’s already too late, right? It means the ecological problem one seeks to avoid is actually materialized, with, of course, the inherent moral hazard, since scarcity is precisely what industry wants to create and preserve. Nothing in market economics seeks to alleviate scarcity. Nothing because it’s based on exploiting it, once again. The Shadow Incentive.

So what the OAD does is work to account for the real world, by which every single creation of an economy must be considerate of a kind of cybernetic design organism, if you will, in an ecosystem that must be self-aware of the ecosystem it depends on. It is inside of this chain of causality, and it must account for it. All this to say that there is no such thing as isolated development of any single good, but rather it is and can only be an ecosystem of overall interdependence and development. And all input factors and downstream considerations must be brought into the design equation for the sake of long-term efficiency.

What defines efficiency? That grand question. Well, from a certain angle, it’s about optimization strategy, right? Thinking down the line, like a pool game, where you’re setting up for other shots. If a particular product made is composed of unique resources, how far down the line can those resources potentially be recycled to maximize their lifespan? How do you create design conditions that maximize this when you’re thinking five, six, seven shots down the line, sorry for the terrible pool game metaphor.

Hence, this is about broad calculation, true economic calculation by which an individual good or service is optimized in ways that not only account for efficacy and general durability, but also the overall efficacy, sustainability, and efficiency of the entire economy as a single system to the best degree that we can.

And if there is any singular realization that the so-called economists of the world seem to absolutely miss, it is this. It’s not even thought about. How can anyone claim to have or promote an economic system if that economic system does not account for the environment it operates within or the relationships existing between everything that has been created thus far, meaning the entire footprint, the entire architecture of what humans have created and how they interrelate with resources?

That’s the singular realization that the true focus of any economy can only be a systems level sense of holism and accounting by which literally everything the human population produces in the world can be thought of as a single interdependent process. One single deeply intertwined process accounting for the factors that will enable the total process to continue without failure. That is the most important economic realization there is and the true focus of what an economy is supposed to do.

So, you can take modern conceptions of recycling and all that and throw it in the trash. We need direct design built in by which a truly circular economy can be created. Where all of those piles in the landfill just waste ultimately. It’s not even garbage, it’s waste — dissolve because we are working to actually reuse and and it has to happen at the design level. If something cannot be reused for whatever chemical or technical reason, then the question becomes, how do we engineer something to replace that so we can avoid that problem in general, reducing waste and pollution? Again, I will not even comment on how nothing like that happens in market economics.

Okay, now that said, and before I get to the OAD modules themselves, one more thing to address because I’ve gotten some criticism on this. And remember, none of this is set in stone as per the white paper.

Creative ideation inside the OAD is not ITC rewarded. Creative ideation, thinking and toying with ideas. Not rewarded in the same way that people working through the CDS to resolve basic node level governance problems are not rewarded by ITCs either. What is reciprocated through the ITC system has to do with tangible physical labor or labor that is a response to an immediate need or concern.

In other words, if a node member is helping to assist with general governance through the CDS in a common routine, periodic unfolding, as a duty which we all engage such as participating in some kind of local council debate in your hometown. You don’t get paid for that kind of thing. This is just people in society respecting society. Common sense.

However, on the other hand, let’s imagine the CDS has a massive problem come in, its intake, that requires an immediate creative technological fix. Something has to be designed and fabricated to resolve the problem, and it has to be done immediately. That distinction in alignment with the node’s predefined constitution, as we talked about last time, is brought into the realm of priority, and it engages the ITC system then. Hence, if a team is now using the OAD to design the solution ITCs are made available. I hope that makes sense.

Is there a gray area in all of this? Of course there is, which is why the node’s constitutional rules need to come to terms with what kind of threshold moves things from one to the other, or how people come together and make single decisions on that issue when need be.

Likewise, we can also understand a creative designer just popping into the OAD to play around with certain designs they’ve been working with, perhaps remotely, then they wanna have community involvement online. Something that might help the note in the future, but it’s not pressing. As I will discuss, the OAD can be accessed by anyone. It does not require a decree from the CDS, even though that pipeline will be common, as is implied in the white paper as being kind of the form of operation throughout the five systems.

And context of any kind of ideation can be anything furniture-improved tools, small technologies, a new vertical farm system, solar microgrid, phone hack for regional communication using mesh networks to circumvent all corporate telecom, whatever. These are pushes for improvement, but not pressing concerns. And hence, we can all understand the difference between that and a major emergency or something that requires of immediate development.

And let’s also remember the core philosophy here. Integral is designed to move toward post-scarcity. The ramification of the move toward post-scarcity, whatever the standard of living might be, is that we are realizing a system level benefit to everyone in the node. And it’s this attribute, and ultimately trend, which I’ll talk a lot more about in future podcasts, that creates the incentive structure by which the more efficient a node becomes, the less reliant it becomes on the ITC system.

If you live in a house and something is breaking down, you don’t need to consult with somebody to decide if you have the motivation to repair the house that supports you, or being compensated in some third party way. You fix the house because it’s part of you. And that, my friends, is the true realization of the human species in our house of planet Earth. And it’s that ethic and incentive that needs to be consciously developed.

People are not going to make things because they’re going to get ITCs in this kind of classic market system reward, they’re going to make things because they want to feel the satisfaction of their own contribution and service. It is just what we do as the social beings and problem solvers that we are. Personal interest becomes social interest and vice versa. This isn’t collectivism, this is actually a harmonized state, which is the only way it can be as difficult as that is because so much antisocial propaganda that supports market capitalism has been so prolific out there. When people even hear the idea of working together, they get this flash imagery of gulags. It’s incredible how distorted people have become when it comes to these simple, rational ideas of human collaboration, isn’t it?

But I honestly think the kind of satisfaction people will draw from contributing will create a satisfaction not in the sense of status signaling. Someone will say, “Hey, look, there’s Amy. That badass just completely redesigned the lighting array of our vertical farm system downtown, increasing efficiency by 90 percent.” People will appreciate others for what they have done for the community, and people are going to respect themselves even more for their ability to contribute, regardless of any praise. The praise is built into the appreciation of the function of what people create.

And sorry for this tangent, but culture has really messed people up. If you dig deep inside yourself, I think you’ll find that what makes you feel human and of value has to do with contribution. It’s a sense of service, dependency, trust, reliance, and inclusion, a reciprocal kind to feel. That’s what’s actually missing for many people in life and why people will go insane and feel isolated and feel no value and they do drugs. They are absorbed into this pattern of self-interest and selfishness that is part of the incentive structure of markets, of course. Gaining at the expense of others is really a sociopathic quality and yet it’s so heavily rewarded in the system. And once again, we wonder why our leaders are completely insane as the success stories of what’s happening.

So an integral, the value structure and incentives seeks to reverse all of that sickness. The true meaning of our lives is not just how much we better ourselves, even though true personal development enlightened self-interest is certainly important, but beyond personal integrity and success in the development of one’s skills, beyond enlightened self-interest, we seek to foster a sense of relationship and understanding with everything else around this, pulling meaning from that sense of relationship and the integrity of it.

And not to get annoyingly philosophical, but you really kind of have to ask yourself what the purpose of any of this is. Yeah, you can get really good at playing the piano or get really fast at running a mile or something, but those are fleeting phenomenon. There’s got to be something deeper, and that is the self-perpetuation of ourselves and our species, and not in just a raw, Darwinistic sense, but in what it means to actually survive, what it means to actually live in a harmonic balance with things. That appears to be the ultimate goal of existence, if you will, a kind of sense of holism where there’s an elegance in your relationship to nature, in this dance and, of course, to the world around you, including society.

And the more you calibrate yourself in that way, the more disturbing everything around you actually becomes. Because everything is kind of performative in the way people operate in their own misguided self-interest under economic pressure. You go to a restaurant and the person waiting on you, being nice, are they actually nice? Or are they just putting on a show for tips? You can’t trust anybody, right? You talk to a salesperson. Are they recommending what is best for you? Or what moves their inventory or gets them a bonus? If some brand posts a heartfelt message about community or some environmental issue, is that a true moral position? Or are they just marketing?

The tragedy is that none of this means people are fake necessarily at their core. It means the system forces people to constantly simulate kind of relationship to others that is actually not honest. It’s a false sincerity for their own survival and people wonder then why trust is so scarce in the world today and why we have such a nasty view of “human nature” which people like to throw in there to try and explain this deceptive reality we exist in.

Trust is scarce because the way we live – business – it is a con an artistry game. And if you choose to do things honestly out there day to day, you will get screwed over. And I know people hate hearing them, because we lie to ourselves. We exist in a giant global architecture of everyone bullshitting everyone else at all times, and then we wonder why everyone’s addicted to drugs and alcohol and on antidepressant medications.

Anyway, so that’s what integral attempts to do is recreate (I think recreate in a proper term actually) a true sense of community, eliminating this disgusting, extractive, competitive aspect. I think the more that takes hold, the more incredibly wonderful society could become.

Enough tangents, let’s now walk through the 10 OAD modules. This is going to be an overview just to start, and then we’re going to go back after this overview and go through each module in more clarity. And I think it’s helpful to think of it all into four groups. Intake, analysis, optimization, and approval and archive. So keep that in mind as we proceed.

All right, module one, design, submission, and structured specification. This is the input module. Where do inputs come from? Two areas from individual creative ideation, meaning someone has an idea, bring it into the OAD without any other process, start working with it. Or the origin is from the CDS because there’s something that does need to be developed to solve a given problem or bring a proposal to life.

It’s worth commenting that many people, when they see the full integral five system architecture, as I mentioned before, imagine it as a strict linear flow going from the CDS to the OAD, the COS, to the ITC, to the FRS. But that’s not really true. There’s tons of circularity between the systems and the systems modules in particular. If someone wants to work on an idea that they think has promise, nothing stops them from opening up the OAD instance themselves in general, making that idea publicly known after submission. Some others may collaborate as well. Does not need to be pre-decided by the CDS in other words.

That said, Module 1 can be thought of as a variation of a common open source programming engagement, but instead what’s being presented and uploaded are schematics, details about the idea, assumptions about what’s required, certain metrics, and essentially whatever can be initially input forward to get the base sense of the good or service to be created.

Module Level 2 is the collaborative design workspace. This is the design space where contributors experiment and collaborate to refine the idea. A multi-user version-controlled branch and merge style workflow for each user can fork the design and work on it separately, online or offline, etc. Teams, in fact, could be formed for this. If you’re familiar with any kind of GitHub-style open-source code collaboration, this is just material development built around CAD system interfaces primarily. And while we’re dealing with high-level complexity to develop this in terms of exact programming, there are a handful of open-source, collaborative CAD system software programs out there already.

So that’s module 1 and 2, the intake group, getting ideas into structured form.

Now we enter the analytical group, the second group as previously commented on, there’s four groups for all of this. This is module 3 through 7, modules 3 through 7, where design gets measured against reality from five different angles, one per module.

Module 3, the material and ecological coefficient engine. Module 3 produces a materials profile for the design, along with an ecological assessment, including an ecological score measurement, which is exactly what it sounds like. And this is a critical module, and we’re going to talk a lot more about this in a moment.

Module four. This module analyzes life cycle attributes of the good in question, including assumed future service needs, potential component failures after extended use, and what is a kind of wide net as per the white paper that tries to generalize what to expect as time takes its toll. It’s very important to note that this kind of assessment also influences access value calculations absorbed by the ITC as touched upon before.

Module five. Module five is feasibility and constraint simulation. This is about the integrity of its operation. Some goods will clearly be simple enough that an intuitive process would be sufficient, such as taking a prototype if they do chair design, making sure when you sit at it, doesn’t immediately collapse. But the more complex the item, the more testing will be required, needless to say.

This is challenging territory because the ideal scenario is that digital simulations with physics and other advanced properties will be utilized and be sufficient in the case of something that needs to be checked for such complex functionality for safety and so forth. For example, a grid installation system to support something, like on a house. Obviously, delicate industrial design territory and it needs to be adequately tested.

Furthermore, module five has thresholds that pertain to various constraints in this way that are agreed upon in advance as part of the constitutional constraints but forward through the CDS as commented before. These include informative feedback parameters coming from the FRS, calibrated to make sure things are in line, which we’ll talk more so about in a moment as it’s fairly in-depth territory.

On to module six, skill and labor decomposition. This is the core bridge from design to economic calculation and physical production. It converts an optimized design into a sequenced labor profile, production steps and maintenance steps with estimated hours, assumed skill tiers, tool requirements, safety notes, and so on. Again, this is what the COS uses to form or engage existing cooperatives and schedule work, setup work. It’s also what ITC uses to help compute access values.

Module 7. Systems integration and architectural coordination. This module protects against something being put forward that is systemically incompatible with the existing state of node infrastructure. What’s already been built. Going back to what I said earlier about the need to account for the larger order design environment, which is ever present on the environmental level, but in this specific case, it’s about how the design fits into the specific technical arrangement of the node itself. In other words, does the part fit? Is it compatible with existing infrastructure?

So for example, let’s imagine we have something that was designed and it has a specific voltage need. Is it compatible with the power arrangement currently in place in the area where we’re going to utilize that new tool? So you can understand the chess game in this kind of approach, especially if the node is suffering from limited means in its earliest stages.

And as an aside, and in stark contrast to the way society works now, deliberate strategic standardization can go such a long way to reduce complexity if it was really focused on. So much waste is created by competitive duplication with slight variation put forward most often as a form of strategic planned obsolescence, of course, or market differentiation for branding.

So anyway, going back to module seven, there’s no point in designing something if the node can’t implement it because of technical incompatibility. Hence the need for a kind of calibration of the design itself to fit the existing technological ecosystem of the node.

Now, so that’s category two. So stepping back, there’s the five analytical models. As mentioned prior, this category module three measures the design against ecology, module four against time, module five against physics, module six against human labor, and module seven against context. Five lenses, same design.

And then we have module eight, third category of its own. The optimization and efficiency engine. And you could think of this as the final stage of that analysis. How can we optimize the design now? The methods utilized in this are both algorithmic and human centric. We have already gone through systemic constraints, environmental constraints, basic design integrity in terms of safety and so forth. Now it’s time to consider everything we have so far and figure out how to make this the best in those conditions and constraints, which we’ll talk about much more in a moment.

And then we have the final set, the fourth category set, modules nine and 10, approval and archive, making it real and remembering it.

Module 9 is the Validation, Certification, and Release Manager. This is the Certification Gate. Module 9 runs an array of checks on the state of the design from ecology to safety to feasibility, the life cycle to labor needs to integration and so forth. And all of this is aggregated into an overall risk index to reach final approval.

Then it goes to module 10, knowledge commons, and reuse repository. And once certified, the design enters this universally accessible collective memory of not only individual designs that can be used and built by and changed, but also the data and processes and everything that went into them as a educational foundation, that’s a data set. Setting the stage for exponential design advancement in a pure open source data friendly global access nature.

Module 10 also interfaces with the FRS, as the broad monitoring mechanism. And if issues arise with use of the item, a trigger is set forward and things flow back to module three to review everything, revise, start again, if need be to improve things in the loop.

So what we have in summation, a design enters the OAD, it gets refined in the collaborative space, it gets evaluated against ecological with node constraints, it gets optimized, It gets certified, meaning it conforms to the existing requirements and it’s placed in this global repository to be utilized by everyone and improved upon, etc. I think it’s a very powerful process. This is a cybernetic design organism, self-aware self-correcting and always learning from what it’s already built. That’s the idea.

And okay, now with all of that understood, let’s now bore everyone to tears and go through it all again in much finer detail.

Back to module one, design submission and structured specification. As stated, there are two broad points of origin for what enters here. First is individual creative ideation. Someone has an idea and wants to begin developing it inside the system. Second is a CDS-routed issue, meaning the community has identified a problem, need a proposal, and OAD is being used to help produce a viable design response.

As touched upon in the overview, creative ideation would generally be treated as community engagement, not automatically as compensated labor, but a CDS-routed priority design may indeed be treated as recognized work in that way, where that threshold sits has to be defined by the node’s constitution and ITC rules, which we’ll return to when we cover the ITC system in another podcast. Or people can read the white paper, but it’s generally vague on this issue still.

Technically, module one transforms a raw idea into a structured object. It requires structured fields to be filled in, functional goals of the item, proposed components, preliminary CAD files or sketches, materials list, environmental assumptions, performance criteria assumed, safety considerations, maintenance expectations, metadata, and so on.

As noted in the white paper pseudo code, the module then runs a simple completeness check, and if the submitter fails to pass a particular threshold, the submission is not advanced yet and is returned for more information.

And what could happen with OAD submissions is the formulation of essentially templates for different kinds of submissions, along with checks, of course, to see if something has already been submitted to this nature, already exists in the database, and so forth.

And then the same line of thinking, sort of jump around here a bit, one could also imagine a kind of sandbox process where anyone could go into the OAD and use the tools privately, experimenting with ideas before submitting to module one. In fact, that would almost be ideal because they could begin to run some checks themselves to have more faith that when they submit to module one, it will satisfy the threshold.

For many that are creatively inclined, you want a circumstance where people can peruse what’s being developed in the OAD in their local node, or in time it could be the entire network, right? (There could be literally something being developed in the network. Network sees it and everyone comes in from around the world. And I think that would be the most advanced stage of this.) But they’re looking around for something to contribute to because they like doing it. And they want to be able to find something that has already been thought about, not just a bunch of half baked ideas that are thrown into the system.

Now, the output of Module 1 is two objects. First is a design spec, which is the high level concept, the idea in structured form. Second is an initial design version labeled something like V0.1 initial submission, linked back to that spec. This becomes the starting point for collaborative work as the design evolves through module 2. Multiple versions will be created, branches, merges, refinements, and adaptations, but they all trace back to the original structured specification for reference.

Now, Module 2, the collaborative design workspace, is where the design is developed. If Module 1 is the front door, Module 2 is the workshop behind it. As mentioned in the overview, you can think of this again as a GitHub for physical design. You begin with a base design or initial version, contributors can fork it. They can propose merges back to the original line if those changes are accepted after general review. How that review occurs is to be explored in terms of the teamwork associated, but they can annotate, comment and leave explanations for why they did what they did and every change is tracked with an author timestamp and a change log. Basic stuff.

And once again, this is about physical objects, not just code. So we’re dealing with CAD geometry, material selections, component specifications and other relevant data.

Now there are existing platforms that do this kind of stuff. OnShape is probably one of the better known collaborative CAD systems. WikiFactory, in fact, is noted for trying to function as indeed an open source hardware equivalent of GitHub. So pieces of this already exist. And where open source tools can be repurposed for integrals OAD without conflict, we should consider building on the existing stuff that is out there, the UI interfaces, et cetera.

But remember what’s truly distinct about OAD is it’s not simply collaborative design. It’s a combination of collaborative design and the rest of the accounting pipeline, ecological coefficients, life cycle models, feasibility simulation, labor step decomposition, systems integration, optimization, certification, and feedback from the real world.

In the white paper pseudo-code module two has two primary operations. The first is create [design branch], which takes an existing version, forks it, and creates a new design version with a parent version ID pointing back to the base version. The second is [update design version], which applies incremental changes to an existing version. There is also a third function [import from commons for local adaptation], which is how designs from Module 10, we enter the workspace for local modification. I’ll come back to that when we get to Module 10, but this is the mechanical entry point for the reuse recursion described in the overview.

So Module 2 is not just a workshop. It’s a place where variations of a design can coexist. For a water filtration design, for example, you might have three serious branches being developed in parallel with, say, different materials. One’s using plastic, another bamboo, another steel. They are legitimate explorations, people are behind them, and module two will preserve that plurality. The downstream modules then evaluate each branch independently. Module three may find that the steel version is too ecologically burdensome. Module four may find that the bamboo version has lower material impact but a higher failure rate in humidl climates. Module 5 may find that one geometry performs better under pressure or flow constraints.

In this way, module 2 is where design variations are explored and the downstream evaluation modules provide the information necessary to decide which paths are worth developing.

Now module 1 and 2 aside, let’s enter module 3, the material, ecological coefficient engine. At some point in module 2, a design branch reaches enough maturity that collaborators want to know whether it is ecologically viable.

Module 3 runs by extracting the bill of materials from the design, meaning the complete list of what the design is made of and in what quantities. Specifically, it applies per material coefficients from a pre-established database. Every material in that database has a known or estimated set of properties. Continuously updated if needed. Embodied energy in megajoules per kilogram. Embodied carbon in the kilograms of CO2 equivalent. A toxicity index from zero to one, a recyclability index from zero to one, water use in liters per kilogram, land use in square meters per kilogram, and a scarcity index. And we are going to walk through each one of these.

But first, let’s get a little bit basic, a coefficient for anyone who gazed out the window during high school math class, A coefficient is just the multiplier. In this case, it is a number you multiply against the quantity of material to get a result. So steel might have an embodied energy coefficient of around 25 megajoules per kilogram. The same logic applies to embodied carbon, toxicity, recyclability, water use, land use, and scarcity, as all listed before. Each coefficient converts a quantity of material into a specific kind of impact.

Now, what exactly is embodied energy? Embodied energy is the total amount of energy required to produce a kilogram of material, extraction, processing, refining, transportation, and everything required to bring that material into usable form. It is commonly measured in megajoules per kilogram. And once again, this kind of number is almost completely absent from market pricing. When you buy something at the store, you generally have no idea how much energy it took to produce. OAD makes this visible, assuming, of course, the correct data can be found.

Now, embodied carbon is the closest cousin of embodied energy. It is measured in kilograms of CO2 equivalent per kilogram of material. The reason it is CO2 equivalent rather than simply CO2 is that different greenhouse gases have different warming potentials and they are normalized to a common unit and necessarily so. This coefficient lets the system see the climate footprint of a design before it is ever built. Steel has significant carbon footprint cement in concrete or also major climate concerns because cement production is a very large source of CO2 emissions and so forth.

Next, we have the toxicity index. And this ranges from zero to one. This is a normalized measure of how harmful the material is to humans, the ecosystem, or the environment across its life cycle. This includes leaching, off-gassing, disposal contamination, occupational exposure, and other hazards. A zero would mean relatively benign, a one would mean severely toxic. Of course, toxicity is complex and dependent on context, pathway of exposure, concentration, and so forth, but the index gives the system something to work with.

Then we have the Recyclability Index, which is also measured from zero to one, and it measures how a material can realistically be recovered and reused at the end of its design’s life. A one means highly recyclable with existing technology and infrastructure. A zero means essentially non-recyclable or practically un-recoverable. And critically, recyclability is contextual. The material can be technically recyclable, but practically un-recyclable if the infrastructure does not exist to process it, needless to say. This is why regional data and the FRS matter. The index should reflect realistic recyclability under actual conditions not the abstract ideal.

Water use in liters per kilogram is exactly what it sounds like. How much fresh water is consumed to produce a kilogram of the material. This can matter enormously, especially in water-stressed regions.

And then we have land use. Land use in square meters per kilogram captures the physical footprint of producing the material. For agricultural materials like cotton or hemp or bamboo, this includes land required to grow the input. For mined materials, it includes land disturbed by extraction. For manufactured materials, it may include facility footprint, amortized over production volume. This matters because land is finite and competing uses food production, ecosystem preservation, housing, rewilding, and infrastructure all draw from the same global total. Bamboo may be useful in some context, but if everyone switched to bamboo for everything, you could easily create monocultures that displace forests and biodiversity.

And finally, we have the scarcity index, which again has a range of measurement from zero to one. A zero means abundant and accessible, and a one means severely constrained. This could reflect rare earth metals, existing supply bottlenecks, extraction limits, or weak substitution options in fact. But anyway, scarcity is not just how much exists in the earth, it is a practical constraint measure of how available, accessible, substitutable, recyclable, and regionally appropriate material is. And like all the other coefficients, it is recalibrated as conditions change, needless to say.

Those are the seven core coefficients of Module 3, Embodied Energy, Embodied Carbon, Toxicity, Recyclability, Water Use, Land Use, and Scarcity. Each is attached to every material in the database, showing a different dimension of impact per kilogram. Multiply each coefficient by the quantity of that material in the design, sum across all materials and you get the design’s ecological signature across those dimensions.

And in this way, OAD begins measuring the true physical cost of production. Market economics doesn’t do this. It just shows you this abstracted price, which pretends to account for what I just talked about. It does in fragments, I should say, more honestly. OAD shows embodied energy, carbon footprint, toxicity profile, recyclability, water demand, land demand, and scarcity jjjexposure all attached to the design as structured data before the design is even built. It’s contingent upon it being built – to make sure it’s done right.

Now, the actual data for all this as implied a moment ago is another story. There are databases and tools already that inform this kind of work to various degrees. Open LCA is a well-known open source life cycle assessment platform. Databases they provide such as eco-invent are widely used sources of life cycle inventory data. Though many high quality data sets and fortunately required paid licenses, obviously in the early stages of a node, this will all be very very crude and it will have to be small and simple initially and then it’ll scale based on what kind of access can be achieved or what can actually be done in individual nodes or through the node network.

But module 3 ultimately requires a kind of regional material awareness that does not yet exist in the public, at least in a truly collaborative trustworthy form. Proprietary knowledge still reigns in the market economy. But let’s remember this is such a critical component, and whatever limitations we face does not override the need for this kind of holistic input and analysis. It simply means the system has to begin with approximations crudely once again and work to improve diligently over time.

Okay, back to the process. Module three sums the raw totals. If a design contains 5 kilograms of steel and 2 kilograms of bamboo, you multiply each material by its per kilogram coefficients and add them together. And since raw totals are not automatically comparable across designs, such as the fact that a filtration unit and a bridge have vastly different material “budgets,” you have to normalize this. Normalization converts numbers measured in certain units and scales them into a common unit scale, usually between zero and one.

Module three normalizes each raw total using reference ranges appropriate for that class of design and sector, which it figures out, or which has to be documented, I should say, and input. So in other words, a small water filter gets normalized against metrics of typical other small water filters, a bridge gets normalized against bridges that exist, and you can make meaningful comparisons that way.

Then module three aggregates these normalized values into the Eco score using a weighted sum. A weighted sum is simply a way of combining multiple numbers into one number where some count more than others. Each input is multiplied by a weight, and the weighted values are added together.

Now where do the weights come from? They are policy determined. The white paper sketches default weights as a starting point, but in a real integral node, those weights would likely be refined through CDS and constitutional policy based on legitimate data that has to be analyzed. A water stressed region, for example, might weight water use more heavily. A region with strong recycling capability might treat recyclability different than a region without that kind of infrastructure.

Finally, module 3 applies a policy threshold. If the Eco score is below the threshold, the design passes its ecological screen. If it is above the threshold, the design is flagged and routed back for redesign. The threshold itself is also a policy choice defined by the node or federation. This information can flow in different ways.

Now module 3 does not merely fail designs, it can also suggest alternatives. It has enough information now. If a steel version is too ecologically burdensome, module 3 can recommend substitutions. AI tools and LLMs could assist with this kind of inference, especially if grounded in reliable material database, along with local resource data and a clear sense of constraints.

And now we move on to Module 4, Life Cycle and Maintainability Modeling. This module estimates expected lifespan, mean time to failure (MTTF), or in repairable systems mean time between failures. This accounts for probable maintenance intervals, labor required per maintenance event, which can be estimated; disassembly time number of refurbishment cycles possible; dominant failure modes and an aggregate life cycle burden index. This is all consistent with the current state of the white paper. These are core metrics that determine not just whether a design works, but whether it will work well over time.

The math here is fairly straightforward. Expected lifespan is derived from usage assumptions hours per day, days per year, and target years of service. Meantime to failure measures the average time a product or component works before experiencing failure. In the white paper sketch, this is adjusted by a material factor and a stress factor. The material factor is a simplified proxy for robustness based partly on recyclability and inverse toxicity. While the stress factor captures environmental severity.

The formula sketched in the white paper is roughly MTTF, meantime to failure, equals a base rating times the material factor divided by the stress factor. So a design using robust materials in a benign environment gets a longer MTTF, a design using fragile materials in a harsh environment gets a shorter one. This is only an approximation of course, in a mature system the material factor would need to be more sophisticated than recyclability and toxicity alone, but as a sketch it shows how durability can become computable.

Now maintenance labor over the designs lifetime is estimated by dividing expected lifespan by the maintenance interval to get the number of maintenance events, then multiplying that by labor per event. If a design is expected to last 20,000 hours and needs maintenance every 2,000 hours, that is 10 maintenance events. If each event takes 2 hours, that is 20 hours of lifetime maintenance labor. Sorry to be so technical, but this is important.

This is all fairly fundamental, however. Module 4 does go further. Produces a repairability index using a formula like [repairability equals 1 divided by 1 plus average labor per event divided by a reference constant]. In practice, this means designs running lots of [labor per maintenance event] get lower repairability scores while designs that can be maintained quickly and easily get higher scores. This is actually a quantification of the “right to repair movement’s” core argument, which groups like “iFixIt” have been putting forward for years through repairability scoring. OAD makes repairability a native part of the design pipeline instead of an external critique after the product already exists.

The Lifecycle Burden and Index then combines normalized [total maintenance labour] with normalized [downtime fraction], giving the system a single number that captures how much long-term human effort and service disruption the design will demand over its lifespan. This number feeds into the ITC access value calculations, which is the critical downstream interface.

Designs with high lifestyle burden influence ITC values upward, because they impose more long-term labor and disruption on the community. While designs with low life cycle burden, influence ITC values downward because they are durable, repairable, and easier to sustain. And this is important because it creates an incentive structure that rewards durability and repairability. The exact opposite of the planned obsolescence logic that dominates market production today.

Okay, moving on. Feasibility and constraint simulation, module 5. This is the physics check, if you will. Module 3 tells you whether the design is ecologically and materially reasonable. Module 4 tells you whether it is likely to remain durable and maintainable over time. Module 5 tells you whether it actually holds up as a physical object under real world conditions.

It runs simulations across scenarios, typically things like nominal load, peak load, and extreme event. For example, imagine a design is a pedestrian bridge. The nominal load is normal use. The peak load is brief, intense spikes of use. And an extreme event is some kind of worst case scenario where there’s a massive flood or something very stressful; an Earthquake.

Module 5 simulates these scenarios and checks whether the design holds up with appropriate safety margins. It runs whatever physics simulations are relevant, structural stress analysis, fluid dynamics, thermal analysis, fatigue modeling, chemical exposure, manufacturability limits, and so forth. Real-world analogs exist and include tools like SimScale, OpenF0AM, EnergyPlus, and other element analysis packages often used in professional engineering.

Simulations produce indicators, max stress, stress ratio relative to yield strength, max deflection, flow rate, pressure drop, heat loss, fatigue risk, or whatever is appropriate to consider for the design. Module 5 then computes a feasibility score per scenario by checking how those indicators compare to safety thresholds. A design where max stress is only 60% of yield strength, gets a high local feasibility score.

The overall feasibility score is then calculated across scenarios, either as an average or a weighted aggregate depending on the design class and the risk profile. Safety margins such as yield factor are extracted as separate outputs for later certification review. Manufacturability flags are also generated here. If the design requires complex machining or tight tolerances or unusual fabrication methods or processes that not every node can handle or a specific node can handle, depending on how we’re contextualizing this, then those constraints get flagged.

So module 5 imposes a hard constraint in the sense that a physically infeasible design cannot move forward as is. If feasibility falls below a certain threshold, a design is flagged and routed back for redesign once again.

And as mentioned in the overview, digital simulation technology has gotten remarkably good. The things you can now model in software, multi physics simulations, coupling thermal structural and flow effects, obviously not everything can be simulated in such an abstracted way, digitally. But in that sense module five lets the OAD eliminate many bad designs before they consume real materials, real labor and real risk.

Okay, that said, let’s move on to module six. Skill and labor step decomposition. This is the bridge between design and actual project planning and economic calculation as commented on in the overview. Module 6 is where the OAD enables structured, non-market economic coordination because without it, there is no reliable way to compute what a design “costs” in real life non-monetary terms.

Module 6 takes a design and decomposes it, meaning it breaks the work down into individual operations that can actually be executed linearly, into a sequenced list of labor steps. Each step gets a name, an estimated time and hours, a skill tier noted in the white paper: we have a distinction of low, medium and high and expert for skills, which can be talked about later. A list of required tools, a sequence index showing where it fits in the workflow, safety notes, ergonomic flags. (For those out there don’t know what an ergonomic flag is in industrial design literature. It has to do with a kind of labor that carries physical risk because of repetitive motion, awkward posturing, heavy lifting, and so forth. This is distinct from acute safety stuff, dealing with immediate hazards like pressure systems or sharp tools or electrical handling, and so forth. So I point this out just to say this is the kind of spread of safety interest, put forward in the OAD as it parses this stuff out.)

And module six would likely build these labor steps from a process template library, a database of standard operations like “assembly housing,” “flow test” or “routine maintenance,” each with base time estimates and skill requirements. This, again, is an application of classical industrial engineering methods, time measurement, process mapping, REFA-like analysis, if you’re familiar.

Industrial engineers have been doing this kind of work for a century. The innovation here is not the labor decomposition itself. The innovation is making it transparent, open, revizable, and part of the design artifact itself rather than a proprietary manufacturing process.

So the module produces a labor profile containing two lists, production steps, and maintenance steps plus aggregated totals; total production hours, total maintenance hours over the designs assumed lifetime, hours broken down by a skilled tier, required tools, safety notes, ergonomic flags consolidated across all steps.

And this maintenance number is worth walking through because it’s where module six has to pull data from module four, by the way. Lifetime maintenance hours are computed by taking an expected lifespan from the lifecycle model, dividing it by the maintenance interval and multiplying by hours per event. If the design is expected to last eight years at four hours per day, 250 days per year, that is 8,000 hours of service. If maintenance is needed every 500 hours and each event takes two hours, that is 16 maintenance events times two hours or 32 hours of lifetime maintenance labor. This number then feeds into ITC evaluation. It is one of the key reasons designs that demand more long-term human attention end up carrying higher access values. The system makes lifetime labor visible at the moment of design. Estimated of course.

And as an aside, once again, in a market economy, the labor embedded in a product gets completely hidden behind the price. You buy a chair for $200 and you have no idea how many hours or what kind of skilled labor went into it under what ergonomic conditions; what safety risks with whatever long-term maintenance implications to expect. In the OAD all that is explicit and attached to the design, its knowledge. ITC can use this data to calculate access values, not based on supply and demand and not based on market price discovery but based on the actual labor time. skill, tooling, safety and maintenance burden the design represents.

This is one of those things that makes non-market economic calculation truly possible as we’ve talked about before. It is the only thing that is economic calculation in true reality. For markets do not actually engage any kind of viable economic calculation.

So, the CDS has its governance logic, COS has its production coordination logic, ITC has its access evaluation logic, but COS and ITC depend directly on OAD module 6 producing this honest, structured, computable, labor data. And labor step estimates are not static either, just like ecological coefficients. If COS throughput data shows that “seal inspection” is actually taking longer in sandy environments than the template assumed, the labor step estimate gets updated. Reality corrects the model in other words.

And just to reemphasize this with respect to Module 6, labor step decomposition is the primary input to COS production planning. ITC uses it for valuation, COS uses it for operational coordination. Critical. Same data, two different downstream uses, both dependent on what module 6 produces.

Okay. Module 7. Systems integration and architectural coordination. Let’s consider something straightforward as an example, like a small electric kettle teapot being designed for a community kitchen. Module 7’s job is to check whether that kettle actually fits into the kitchen, not just physically but technically and systemically.

The model loads what we could call a “node infrastructure registry,” a technical description of what is present at the deployment site, the kitchen. This could include voltage standards, available connectors, tool capacity, workshop equipment, available materials surrounding its spatial limitations, safety clearances, recycling stream is water systems, heat systems, and other relevant infrastructure that may need to be taken into account to support or negate the new item being implemented.

Then it runs two kinds of checks. The first is interface compatibility. Basically does it fit? Does the kettle plug into the voltage, the kitchen actually supplies and so forth? Does it have a specialized cord or connector that nodes do not actually utilize often? Can the cooperative workshop fabricate replacement parts like this? Or is it built around components that have to be outsourced in whatever sense? Each mismatch then generates a conflict entry, a flag saying, “This part of the design does not really match what is actually present, repairable or workable in this node.” And it could apply in a multi-node setting, but that’s a deeper conversation.

The second check is circular resource loop detection. Does the design produce attributes that could be productively connected to other systems already running? In the kettle’s case, maybe waste heat from the heating element could be vented toward warming a nearby seed planting station. I’m being clearly hypothetical here, but you see that point. Maybe the kettle’s housing is designed to be disassembled and its components fed back into the workshop metal recycling stream later on after its lifecycle. Each productive connection generates a circular loop entry, a flag saying “this design contributes to the node’s resource circularity” rather than simply consuming and discarding.

Then the module computes an integration score, with penalties, so to speak, for conflicts and bonuses, so to speak, for circular loops. In a simple formula, the score might equal 1 minus 0.2 times the number of conflicts plus 0.05 times the number of circular loops clamped between 0 and 1. Conflicts hurt the score more than loops help it, which is intentional. Once again, going back to what I talked about, and this balance favoring the perception of problems – to be that much more safe and hence this module should be strongly protective against incompatibility while rewarding circular integration.

So in our kettle example if the kettle plugs into the right voltage, fits available space, uses standard parts, the workshop can replicate; and it happens to feed waste heat to a seed station and it has zero conflicts in a circular loop – then the score lands at say 1.05, then gets clamped down to 1. It’s perfect compatibility with a small bonus, and the kettle gets a clean pass.

Now this is analogous to how building information modeling BIM works in architecture. BIM systems help check whether building components are spatially and functionally compatible before construction begins. Module 7 does something similar for designs entering an integral node, though obviously the kettle example is a tiny case compared to full accounting requirements for buildings, energy systems, transport systems, production equipment, agricultural infrastructure, and so forth.

And like module 5, module 7 can function as a hard constraint on the pipeline. If the integration score falls below the threshold or if there are unresolved conflicts, design cannot move forward for that deployment context.

And we move on. Now to module eight, the optimization and efficiency engine. Now we get to the active improvement module. Much of what came before this has been evaluation, modeling and constraint checking. Module 8 is where the system actually tries to make the design better. It is a different kind of operation from the previous analytical models, as discussed before.

Module 8’s optimization process is multi-objective, as mentioned earlier. In one implementation sketch, the module builds a scalar objective function from several inputs, Eco-score, material intensity, production labor, maintenance labor, life cycle burden, feasibility score, and integration score.

Now what is a scalar objective function? It is a weighted sum similar to the Eco-score for module three, but instead of simply producing a static measurement, it becomes a target for the optimization algorithm to drive downward. One number representing the overall “badness” of the design where lower is better.

The weights work the same way as before. They are policy configurable and can be set constitutionally or through CDS mediated governance. The system has to decide how much it cares about material reduction, labor reduction, ecological burden, life cycle burden, feasibility, integration, and so on. And that often pertains to the characteristics of the note itself as touched upon.

Now, module eight’s optimization loop mutates, design parameters, adjusting dimensions, swapping materials if needed, changing tolerances, altering geometry, simplifying assembly procedures, or changing component choices. For each candidate mutation, the system evaluates the design against the relevant prior modules: ecological impact, life cycle burden, labor decomposition, feasibility, and integration. In full implementation, this might mean rerunning modules 3 through 7 directly and probably often will. In more efficient implementation, it might use cached results, surrogate models, or partial evaluations before committing to a full simulation cycle.

Now if a mutation improves the objective value and all hard constraints still pass, the candidate is retained. If it worsens a score or violates a constraint, it is disregarded or sent back for further revision.

Again, this is just classic evolutionary optimization stuff, similar to how parametric solvers and generative design tools, in fact, already work. Autodesk style generative design, topology optimization, evolutionary solvers, and multi-objective engineering optimization all live in this kind of family. The core difference is that the OAD’s objective function is biophysical and labor-based, again, not $cost-based.

Module 5 and 7 are, indeed, treated as hard constraints. Optimization cannot produce a design that fails physical feasibility or fails integration with the deployment context. Depending on the nodes, ecological policy, module 3 thresholds may also function as hard constraints. So the search, in other words, is bounded. Within those bounds, optimization works to reduce ecological impact, material use, production labor, and maintenance burden while improving durability, feasibility, and integration.

And as mentioned in the overview, optimization is both algorithmic and human-guided. Humans set the weights and humans can intervene when the algorithm hits a trade-off that requires judgment. We want automation as much as possible, but don’t think this is just a black box thing. There’s a great deal of developmental work that has to be done by people behind the scenes with legitimate information. So for example, choosing between a design with lower material intensity and one with lower lifetime maintenance when both are viable, the algorithm searches within the defined objective, but humans define, revise, and govern that objective. I hope that makes sense.

Now, I know a lot of people aren’t familiar with a lot of the stuff I’m talking about here. But if there’s a question that if this kind of thing can be automated, if they think this is real or fantasy, is this just something that integrals proposing that does not exist? No, this is not science fiction. Existence of this is very real. And what the white paper puts forward is a generalized sketch of things that are in fact already happening. Algorithms like NSGA 2, non-dominated sorting genetic algorithm 2 have been used since the early 2000s to optimize designs with conflicting objectives, minimize weight while maximizing strength, minimize cost while maximizing performance, reduce emissions while maximizing reliability, and so forth. And that is precisely the kind of mathematical machinery module 8 is gesturing toward.

Okay, moving on to module 9, the validation certification and release manager. This is the gate. As mentioned earlier, module 9 is actually what approves a design for release. Everything before this has produced measurements, simulations, decompositions, improvements or compatibility checks. Module 9 asks whether the whole package is now coherent enough to become production ready.

This module runs a set of final validation checks across several dimensions. Ecology using the Eco score against the relevant threshold that has been pre-decided. Safety and feasibility using feasibility scores, safety margins, and yield factors. Lifecycle using expected lifetime maintainability and lifecycle burden. Labor and ergonomics using total production hours, maintenance burden, skill requirements, safety notes, and ergonomic flags, integration using integration score, interoperability status, and unresolved conflict count.

And each check can return a pass/fail result plus a risk score between zero and one. Implementation could then compute an overall risk index by aggregating the five per dimension risk scores, as talked about. This could be a simple average or more realistically a weighted average, depending on the design class. A medical device, a bridge, a tea kettle, should not necessarily weight risk dimensions in the same way.

And the critical structural move is that certification requires not only that each individual check pass, but also that the aggregated risk remain below a threshold. A design can meet every individual minimum and still fail if its total risk profile is too high. This prevents what you could call “borderline stacking.” The failure mode where every individual check is marginal and the aggregate becomes dangerous.

And if certification succeeds, a certification record is generated with the [certified at] time stamp, the list of certifiers, the criteria that passed and failed, a link to the documentation bundle, and a status of certified. So you have a certified design version status, and the design is now a production ready.

If certification does fail, potential production is blocked, and the design is routed back to the relevant part of the pipeline to be addressed. If the ecological score fails, it may go back through module three or module eight. If feasibility fails, it may return to module five or module 8. If labor decomposition is incomplete, it returns to module six. If integration fails, it returns to module seven. The point is not that the design is permanently discarded, but it cannot be released in its current form. And once again, nothing is set in stone, something may be certified, but become uncertified when its performance doesn’t meet up to expectations, or something else comes into being, that’s a dramatic improvement, making the other one obsolete.

Now the white paper treats certifiers as an input to the module, and is admittedly vague on this point. Now who or what a certifier is could rest on just the basics aggregate of what’s been put forward throughout the OAD, where the certification is inherent to what has been done because it checked all the boxes of doing all the right things for the time. Or you could have a node kind of ordered a group of people that take one last look at all of this just to triple check at a human level. It could be a kind of CDS process, in fact, if need be. We’ll leave it at that for now and move on to module 10.

The knowledge commons and reuse repository. So this is the commons. Once a design is certified by module 9, it enters module 10. This is where OAD stops being about single designs and becomes civilizations’ accumulated design, intelligence.

The module creates a repo entry, an index record that points to all the canonical data produced during the pipeline. Design specification, the certified version, the eco assessment, the lifecycle model, the labor profile, the simulation results, the integration check, and the certification record. The entry is tagged for relevant application and certain features.

Then the repository does its work. And there are four flows that run through it on an ongoing basis.

First is deployment tracking. Every time a cooperative somewhere in the federation or locally builds and installs a certified design, the deployment is registered. The reuse count goes up, the deployment timestamp updates, new climates and sectors are added if this is the first deployment in that context and other peripheral considerations.

Second, lineage registration. When a node pulls a design from the commons, adapts it locally for its conditions and gets the adaptation re-certified, the child version is linked back to the parent, and over time this builds this evolutionary tree of design lineages.

Third, we have operational feedback registration. The feedback review system, the FRS feeds real-world performance data back into the repository, meaning uptime, maintenance hours per year, common failure modes, maintain and reports, user feedback, cooperative reports, and actual field performance. And this data gets attached to the version record.

And fourth, you have feedback routing. So when operational feedback diverges from the prediction set forward by the OAD, the repository routes that divergence back upstream. Divergent ecological impact hence goes to module three for coefficient recalibration, for example. Divergent life span goes to module four, divergent labor hours go to module six, divergent performance goes to module eight for optimization. And in serious cases, module nine is notified for possible review, re-certification or revocation. Something is truly divergent.

The white paper also sketches something like a commons utility index, a weighted combination of reuse count, climate diversity and sector diversity. And importantly, designs with very high utility indices, very high usage, meaning they’re being applied in many different contexts and continue to perform well, they rise in the search results and become more default accessible templates, if you will.

This is a kind of distributed way for the federation to identify which designs have proven themselves. But it should remain a kind of ranking heuristic, not some kind of authority. Because a newer design might actually be better, but not yet widely deployed. The commons should surface evidence, not just freeze innovation, just because of use patterns, right?

And this is where the interface to the COS and the ITC comes into focus as well. COS uses the commons as a catalog. When a cooperative needs to build something, it does not need to start from scratch. It searches the commons for designs matching the need and high utility, well-documented proven designs naturally surface first.

At the same time, ITC uses the Commons for evaluation stability. A design that has been built many, many times in many, many regions will have a much more reliable labor, material, maintenance, and failure data set than a design that has never been deployed. And hence, its access value can be computed with greater confidence. A brand new design has noisier and more fragmented inputs, which may be reflected as a wider uncertainty range or a review flag in some cases. This is learning-based economic calculation, once again, not price speculation, because the evidence base is real deployment, not market signals.

And I won’t go into this part today, but high priority, high utility designs are also the ones that should be targets for deliberate post-scarcity planning. If a design is essential, widely used, and socially important, integral can consciously focus on making it abundant through strategic-focused standardization, optimized tooling, training, material provisioning, the deliberate and strategic move toward post-scarcity.

Now just say as an aside, if you want to live in a post-scarcity society, become minimalistic. Positive, workable standard of living that is not an excess. Trade all that for the luxuries and nonsense we’ve been conditioned to pine for our status and whatnot in the current market-diseased culture.

So this marks almost the end of another painful exposition that probably doesn’t work well in a podcast format, but I’m doing this anyway. So I do have three more of these to go through. I’m going to make some kind of graphic representation of this. And of course, development will happen with the community when that finally goes online as far as being operational. It’s still all placeholder at the moment as I go through the numerous applications.

But all that said, let’s now just quickly summarize this exploration of the OAD.

A design enters Module 1 as a structured submission. It gets developed collaboratively in Module 2. It gets evaluated through the five analytical lenses of Module 3 through 7, Ecology, Time, Physics, Labor, and Context. It gets optimized in Module 8 with the feasibility space those evaluations define. It then gets certified, if appropriate, at module 9. It then enters the Commons in module 10, where it is available to everyone, can be deployed, generates critical operational feedback, and recursively improves the entire thing, the entire pipeline of how to build this item and frankly anything as evidence and feedback accumulates.

This flow is, as usual, not strictly linear. Designs will bounce back for revisions, certified designs, re-enter Module 2 for perhaps local adaptation or revision operational feedback loops. We’ll always come back in the refinement process to Module 3, 4, 6, and 8, and certification itself can be revoked, et cetera.

It’s a kind of organism, one that designs, builds, develops, observes, learns, and redesigns forever without patents, without intellectual property, without enclosure of any kind, without the structural incentive to recreate scarcity, duplication, planned obsolescence, and so forth.

And that does it for me today.

All right, folks, this program is brought to you by my Patreon. And if you want to subscribe to this channel, feel free as I think the more I talk about this, the more people will stop paying attention because this is not common, angry, objection oriented podcast fodder that the masses love in the activist industrial complex. But I appreciate everybody that does focus on this. And one way or another, this fucker is getting built.