Subscribe to Orion Growth
<100 subscribers
Subscribe to Orion Growth
<100 subscribers
Share Dialog
Share Dialog
I love agentic design. In fact, I’m infatuated by it.
This is our Copernican moment.
We have several complex projects in house right now. An OpCo/PropCo called ‘Deep Gap’ an AI bot called ‘BigLove’, and an urban planning / economic development project called ‘PathHub.’
Each of these projects takes on a traditional DevOps form. We’re always striving for collaboration, automation, and continuous improvement to deliver results faster and more reliably. We have a pretty good handle on the operational silos that cause logjams, and we’ve (for the most part) engineered these silos out of our process. At very least, we’re successfully shining a spotlight on the dark spots.
As a distributed team, we recognize the elemental design at play here:
Single Source of Truth Documentation.
Centralized Repository.
Centralized Comms Platform.
Sync and Async Work Styles.
Personal Operating Manuals.
Similar to the way Samin Nostrat brilliantly brought us his cookbook; *Salt, Fat, Acid, Heat: Mastering the Elements of Good Cooking…..*these basic elements are the key ingredients to our recipe for success here at Orion Growth. These projects are waaay crazier and more ambitious than any we’ve ever worked on before. The incredible humans behind them are passionate, purpose-driven, problem solvers who think in circles, not lines. The goal isn’t the end. The goal is the circle. We will shatter performative metrics by embedding true accounting for things like impact, value, and benefit that haven’t been effectively measured (or valued) before. We’re rebalancing the balance sheet….
So where does AI come into this?
The fundamental structures of AI - neural nets, deep learning, ML, intelligent automation - all refer to tech that has emerged over the last 50 years or so. Just recently, we’ve seen an explosion in AI in terms of its generative form; chatbots, one-on-one conversations - LLM’s that produce pictures and video from human prompt.
Fascinating stuff.
As K Allado-McDowell points out in Designing Neural Media, AI isn’t always generative. Much of the AI that has emerged is perceptual. “Critical and ethical conversations in the last decade dwelt on the proper limits of facial recognition, how we might apply machine sensing of voiceprint, gait and sentiment without empowering totalitarian regimes, or on the nature of digital biometric doubles. The same technology that powered sensing systems developed into the generative AI that we know today.” Whether generative or perceptual, AI use neural nets - math - inspired by the biological structures found in our brains. The compute of neural nets was only limited by the compute of the machine - so for a long time, neural nets only lived in theory.
Not anymore.
Centralized Processors have given way to Graphical Processors. Computational throughput has gone exponential. 3D Vector Graphics are the norm. Rendering in engines like Unity and Unreal are commonplace for games, but companies like V-Ray, OctaneRender, and Arnold are increasingly being used in various industries like architecture, engineering, and construction to create realistic and high-quality visuals.
It’s all about high dimensionality.
The AI systems we’re building have to be able to express themselves. In math and neural nets, that means fidelity and dimensionality. If we want the outcome to be ‘lifelike’ it has to be multi-dimensional or it will feel ‘flat.’ In addition, it has to have spatial awareness and cognitive recognition. This ultimately leads to a sense of familiarity - a relationship with the project that can relate to that relationship. Benjamin Bratton refers to AI as “Matter, thinking about matter, making matter that thinks.” - I’ll wait while you read that again. It blew my mind too.
This is where it becomes relative.
As our friend Einstein wrote: E=mc2
We’re living in a 4-dimensional world, and our machines are finally allowing us to experience, and explore them. We’ve moved from Math to Physics - and we ended up in the Relativity Rabbit Hole: Time.
Now I’m not sure which is our most precious resource - our ideas or time, but as I approach 50, I’m starting to see the treadwear on my Nikes. Unraveling space wasn’t on my bucket list - so I’ll have to leave that for our nexTgen of future explorers. For now, we’re working on the things we can so our work has an impact in time and space right now. This is Long-Now thinking. It addresses the long, but it does it right now.
The Urgency for Urgency.
In a world captivated by immediacy, we often mistake movement for progress. Right now, there are many examples of the race to the bottom. Urgency isn’t about frenetic reaction, it’s about conscious, decisive action - rooted in a profound respect for what’s ahead. Working ‘long-now’ is the antitode to short-termism. It means making decisions today that honor the generations who will inherit the results tomorrow. It’s about Re: everything - ReDesign, ReStructure, ReFinance, ReTeach, ReLearn, ReBuild - not just through market cycles (in which I have been through 5 once-in-a-lifetime financial crisis’s) but through paradigm shifts. Sounds like it would make a great book, (hint, hint).
True urgency isn’t about doing more, faster. It’s about doing the right things now - intentionally, courageously - so that the future isn’t a casualty of our present convenience. We have to act urgently because the future is already here. The work of resilience can’t wait.
The AI Officer’s Spyglass isn’t just a metaphor, it’s a tool for a mission. It’s the lens we hold steady while we’re exploring what’s essential. It’s the deliberate act of looking out, seeing deeper, and setting course through the uncharted waters of time and technology. It sharpens our view while extended, yet it fits in our pocket for convenience and security.
Explorers use compasses, not maps. I’m also packing a spyglass.
(This was originally posted in Substack)
I love agentic design. In fact, I’m infatuated by it.
This is our Copernican moment.
We have several complex projects in house right now. An OpCo/PropCo called ‘Deep Gap’ an AI bot called ‘BigLove’, and an urban planning / economic development project called ‘PathHub.’
Each of these projects takes on a traditional DevOps form. We’re always striving for collaboration, automation, and continuous improvement to deliver results faster and more reliably. We have a pretty good handle on the operational silos that cause logjams, and we’ve (for the most part) engineered these silos out of our process. At very least, we’re successfully shining a spotlight on the dark spots.
As a distributed team, we recognize the elemental design at play here:
Single Source of Truth Documentation.
Centralized Repository.
Centralized Comms Platform.
Sync and Async Work Styles.
Personal Operating Manuals.
Similar to the way Samin Nostrat brilliantly brought us his cookbook; *Salt, Fat, Acid, Heat: Mastering the Elements of Good Cooking…..*these basic elements are the key ingredients to our recipe for success here at Orion Growth. These projects are waaay crazier and more ambitious than any we’ve ever worked on before. The incredible humans behind them are passionate, purpose-driven, problem solvers who think in circles, not lines. The goal isn’t the end. The goal is the circle. We will shatter performative metrics by embedding true accounting for things like impact, value, and benefit that haven’t been effectively measured (or valued) before. We’re rebalancing the balance sheet….
So where does AI come into this?
The fundamental structures of AI - neural nets, deep learning, ML, intelligent automation - all refer to tech that has emerged over the last 50 years or so. Just recently, we’ve seen an explosion in AI in terms of its generative form; chatbots, one-on-one conversations - LLM’s that produce pictures and video from human prompt.
Fascinating stuff.
As K Allado-McDowell points out in Designing Neural Media, AI isn’t always generative. Much of the AI that has emerged is perceptual. “Critical and ethical conversations in the last decade dwelt on the proper limits of facial recognition, how we might apply machine sensing of voiceprint, gait and sentiment without empowering totalitarian regimes, or on the nature of digital biometric doubles. The same technology that powered sensing systems developed into the generative AI that we know today.” Whether generative or perceptual, AI use neural nets - math - inspired by the biological structures found in our brains. The compute of neural nets was only limited by the compute of the machine - so for a long time, neural nets only lived in theory.
Not anymore.
Centralized Processors have given way to Graphical Processors. Computational throughput has gone exponential. 3D Vector Graphics are the norm. Rendering in engines like Unity and Unreal are commonplace for games, but companies like V-Ray, OctaneRender, and Arnold are increasingly being used in various industries like architecture, engineering, and construction to create realistic and high-quality visuals.
It’s all about high dimensionality.
The AI systems we’re building have to be able to express themselves. In math and neural nets, that means fidelity and dimensionality. If we want the outcome to be ‘lifelike’ it has to be multi-dimensional or it will feel ‘flat.’ In addition, it has to have spatial awareness and cognitive recognition. This ultimately leads to a sense of familiarity - a relationship with the project that can relate to that relationship. Benjamin Bratton refers to AI as “Matter, thinking about matter, making matter that thinks.” - I’ll wait while you read that again. It blew my mind too.
This is where it becomes relative.
As our friend Einstein wrote: E=mc2
We’re living in a 4-dimensional world, and our machines are finally allowing us to experience, and explore them. We’ve moved from Math to Physics - and we ended up in the Relativity Rabbit Hole: Time.
Now I’m not sure which is our most precious resource - our ideas or time, but as I approach 50, I’m starting to see the treadwear on my Nikes. Unraveling space wasn’t on my bucket list - so I’ll have to leave that for our nexTgen of future explorers. For now, we’re working on the things we can so our work has an impact in time and space right now. This is Long-Now thinking. It addresses the long, but it does it right now.
The Urgency for Urgency.
In a world captivated by immediacy, we often mistake movement for progress. Right now, there are many examples of the race to the bottom. Urgency isn’t about frenetic reaction, it’s about conscious, decisive action - rooted in a profound respect for what’s ahead. Working ‘long-now’ is the antitode to short-termism. It means making decisions today that honor the generations who will inherit the results tomorrow. It’s about Re: everything - ReDesign, ReStructure, ReFinance, ReTeach, ReLearn, ReBuild - not just through market cycles (in which I have been through 5 once-in-a-lifetime financial crisis’s) but through paradigm shifts. Sounds like it would make a great book, (hint, hint).
True urgency isn’t about doing more, faster. It’s about doing the right things now - intentionally, courageously - so that the future isn’t a casualty of our present convenience. We have to act urgently because the future is already here. The work of resilience can’t wait.
The AI Officer’s Spyglass isn’t just a metaphor, it’s a tool for a mission. It’s the lens we hold steady while we’re exploring what’s essential. It’s the deliberate act of looking out, seeing deeper, and setting course through the uncharted waters of time and technology. It sharpens our view while extended, yet it fits in our pocket for convenience and security.
Explorers use compasses, not maps. I’m also packing a spyglass.
(This was originally posted in Substack)
No comments yet