I. The AI-Native Imperative
Probably the most exciting questions I keep asking is:
What does an AI-native organization look like? And on what principles is it built, and what are the steps to get there?
In this post I try to answer what the first principles to building an AI native org are, and how you can start now.
Why do you want to build an AI native org? It is the most efficient and intelligent way of improving your org for the future. The benefits are: greater speed, complete documentation of processes, human interchangeability and low cost autonomous work.
You can think of the foundational principles as an ongoing process of codifying your organization process starting with A, B then C and on.
You could skip this foundational step. But completing the above allows you to be smart and create the necessary context for rapid innovation with AI.
II. Principle One: Codify Like Navy SEALs
The first step is to codify. Like the Navy SEALs command protocol, you want to build and iterate on a set of documents, data or principles that is your "source of truth".
If the concept is new to you, start simply by writing down and documenting how things get done and the truths your team operate under. Don't stop there, make this the step where you reflect on what is done and how and if it creates the output required. Then you can start to refine and edit these principles to make your entire org play better.
Navy SEALs don't rely on gut feelings when lives are at stake. They document everything, test it relentlessly, and continuously improve their protocols. This doesn't make them robots – it makes them deadly effective by freeing their minds to focus on the mission-critical decisions.
In practice, this means:
Mapping key workflows that generate value in your organization
Documenting decision frameworks your best people use instinctively
Creating knowledge repositories accessible to both humans and AI
Testing and refining these processes until they reliably produce results
Without this foundation, your AI implementations will remain surface-level toys rather than transformative forces. AI needs structured information to be truly powerful. Give it that structure.
III. Principle Two: Maneuver Like Napoleon
For the second step of the foundational AI steps we turn to a strategy from Napoleon: maneuver warfare.
Napoleon structured his army in smaller more mobile units, all driving together towards the ultimate goal. Decision making was decentralized and responsibility of command more effective than conventional top-down rigid command structures.
Conventional organizations maneuver like slow machines limited by group think and indecision. Instead of a single line of organization, give your team room for peer groups and exploration. Like how Napoleon unleashed a scattered (but united in mind and spirit) troop on his enemy, you can divide up your org into divisions experimenting with the approach yet keeping the troop united on the goal or competitor.
Learn from Napoleon the means to experiment. Then iterate on the most effective outcomes of peer group initiatives.
You're facing a future where computation and artificial intelligence will dominate. A true or false AI evolution is yet to be configured. You can follow Napoleon's footsteps and maneuver this uncertainty by encouraging different methods and ideas within your team groups. Now is too early to become rigid by methods when tomorrow can bring the more brilliant method.
Maneuverability gives you the flexibility to test and the peer groups to learn from the different options at your disposal. With skin in the game, the peer groups are incentivized to experiment with the approach.
IV. Principle Three: Learn Like Elon Musk
In every successful founder you can find a powerful ability to adapt, learn and innovate with new knowledge. Either out of necessity or out of curiosity.
Elon Musk is the greatest example of this. Before and during the founding of his companies he has learned skills ranging from: physics, automotive, clean energy, aerospace engineering, software and internet technology, neurotechnology, infrastructure, artificial intelligence.
Elon's approach to learning is driven by an insatiable curiosity and a need to understand the universe. Elon's enemy is the status quo. The world is constantly plagued by consensus and lethargy, here Elon sees his greatest options of learn and innovate. In addition, Elon's incredible memory and creativity is the by-product of immediate utilization of new knowledge. Elon avoids the bubble of ideas and thoughts for too long. Instead, he opts to run his ideas through his various mental models, tests and tangible validations like the laws of physics.
The most useful learning method Musk uses is his network and access to field experts: "Sucking the experience out of them" is how he can quickly get up to speed through self-study and the environmental effects of domain experts.
Going into the future you must become an intense self-student, explore and learn about the foundations and innovations of present and future in the fields of technology, science or business that impel your curiosity. Then you connect with people more obsessed and knowledgeable than you, shortcutting your way to necessary experiences and deeper knowledge for gaining a complete perspective of the art. This is how Elon can suck up new information and skills with an intense speed.
Now, using this method of learning you can, within rigorous sprints, learn and become an expert on emerging innovations within months. For you, this might be to immerse yourself into the key concepts of AI. This includes prompt engineering, code, MCP servers and most importantly getting your hands onto all the various tools.
Get the feel for the future and you will start to live in it.
V. Starting Now
These three principles don't stand alone—they reinforce each other when properly combined:
I. Codification creates the structured knowledge that both humans and AI need to operate effectively. Without it, you're building on ice.
II. Maneuverability provides the adaptive capacity that prevents premature standardization. A rigid approach to AI implementation will inevitably fall behind a more flexible future.
III. Learning velocity is how you, your people and systems continuously warp new capabilities rather than becoming locked into rapidly outdated insights.
Together, these principles create a flywheel effect. Better codification lay the tracks for experimenting with parallel methods. Effective experiments accelerate learning. New learning improves codification data. Then you are set up for meaningful evolution.
Here's how to take concrete action on each principle:
Codification: Start with the highest-value processes in your organization. What knowledge currently lives only in people's heads? What decisions rely on undocumented expertise? Begin documenting these areas, not as a bureaucratic exercise but as source documents for experiments with AIs and practice of writing prompts and mastering the engineering of AI.
Maneuverability: Form small, cross-functional teams with the freedom to experiment with different AI approaches. Give them clear objectives but methodological autonomy. Let them explore different paths to the same destination, then compare results. Be clear about the what, not the how.
Learning velocity: Develop your AI curriculum and immerse yourself in hands-on experience with the tools. Use experts (AI experts included: Perplexity, Claude, GPT…) to accelerate your learning and build specifics to test your ideas. Create mechanisms for rapidly passing on new knowledge throughout your organization, this can take form as group chats.
Once you've woven a net of serious knowledge and insight, connect with experts in and around the technology. Obsess over creating your unique perspectives and sense of where the future is headed.
If you are wise, find mentees with the knowledge you want to understand and put them under your wing. If you are junior, look for an older wiser person where you can mutually benefit each other. This is how you can quickly get a foot inside the door, and hack the time it takes to gain experiences and knowledge. Ultimately increasing your learning velocity and maneuverability creating a sovereign mindset ripple throughout your team.