The Five Levels of Value in the AI Age

AI models are getting better on their own now. Every quarter, the tools get more capable, the cost of execution drops further, and the gap between levels of work widens. If you're choosing what to learn, where to invest your time, or how to position yourself for the next decade, this is the most important thing to understand.

Your position in the economy is either getting more valuable or less valuable as AI improves. Which one depends on the level you're operating at.

Level 0: Spectator

You watch the game. You read about AI, attend conferences, consume newsletters, talk about what's coming. But you're not in the arena. Your relationship to AI is passive consumption.

The trap: spectators often feel productive because they're "staying informed." But information without application is entertainment, not preparation. You can read every AI newsletter published this year and still have zero ability to apply any of it when it matters. Economically, this level is heading to the same place as Level 1. Both are zero.

Level 1: Player

You're in the game. You execute within an existing system, using AI as a tool to be faster and better at what you already do. You might be an elite player: the best editor, the fastest developer, the most responsive account manager. AI makes your hands faster.

The risk: AI is compressing this level toward zero. The gap between a great Player and an AI doing the same task shrinks every quarter. This is where most layoffs hit. If your value is defined by execution speed, you are in a race you will eventually lose.

Look at what DoorDash just launched: "Dasher Tasks." Dashers now get paid to walk into stores and scan shelves with their phone cameras. DoorDash calls it "building the frontier of physical intelligence." Read that again. They are paying human workers to collect training data for the robots that will replace those same workers. The Dashers are literally building the machine that makes them obsolete. Same pattern as the humans who "babysit" Tesla robotaxis: sitting in the driver's seat so the car can legally operate while the AI learns to drive without them. That is Level 1 in its purest form: executing within a system that is actively learning to not need you.

The opportunity: every Player has domain knowledge that qualifies them to climb. You've paid your ignorance debt. You know how things actually work, not just in theory. That knowledge is the raw material for the next level.

BuzzFeed was a Player organization. They were elite at the content game. They optimized execution to industrial scale ($185M in annual revenue). But they never became Coaches. When AI made their execution model obsolete, they had nothing to fall back on. The market priced them at 0.14x revenue. That's investors saying: you are going extinct. (See: Don't Scale Slop)

Level 2: Coach

You design the system that players operate within. You're not editing videos; you're building the editing pipeline. You're not closing deals; you're designing the sales workflow. You're not posting content; you're building the content engine that handles story selection, pre-production, and distribution so the talent just does talent stuff.

This is meta-work: working on the business (or the project, or the team), not in it. Your value is measured by system performance, not personal output. You make other people and AI agents more effective.

This is the minimum viable position for the AI economy. If you're not at least here, you're vulnerable. This is the level where most people should aim first. You don't need to be a founder or an executive to operate here. You need to think in systems, not tasks. Learning to build workflows, not just use tools. Learning to design processes, not just follow them. Learning to create the system, not just be a cog in it.

Level 3: Game Creator

You invent new games entirely. Not just a better version of an existing business, but a new category of value creation that Coaches can build systems around and Players can execute within. You're expanding the economic pie, not just taking a bigger slice.

This is the founder who sees that AI collapsed the cost of operations in their industry and builds a completely new business model around that reality. A new type of agency. A new type of media company. A new model for talent development. A new approach to education that couldn't exist before the tools existed.

You don't get here by optimizing. You get here by seeing what's now possible that wasn't possible before and building for that reality.

Level 4: Game Engine Creator

You build the engine that powers many games. You're not creating one business or one category. You're building the methodology, the infrastructure, the enabling layer that makes it possible for Game Creators to create and Coaches to coach and Players to play.

This is extremely rare. But it's the highest leverage position in the economy.

The Compression Effect

Here's what makes this framework urgent: Spectator and Player are both heading to zero. They feel different (one is watching, the other is working), but in economic terms, AI is compressing both toward the same destination. Execution is becoming cheap. The entire hierarchy shifts upward.

The cost of building technical infrastructure collapsed overnight. But the cost of taste didn't collapse. The cost of trust networks didn't collapse. The cost of deep domain expertise didn't collapse. The cost of knowing how to read a room, make a deal, or build a brand that people believe in didn't collapse.

The human elements are worth more than ever precisely because the technical elements got cheaper. The people who understand this are already moving. Everyone else is still arguing about whether AI will replace them.

This is not dystopian. It's liberating. The compression frees human energy for higher-level work: coaching, game creation, engine building. The people who thrive are the ones who see the compression happening and climb.

Three Ways to Think About Climbing

Knowledge, Understanding, Wisdom

Al and Hattie Hollingsworth developed a framework in their B.O.S.S. Training Syllabus, taught to entrepreneurs in South Central LA decades before "information overload" was a cultural concept. It maps three stages of capability:

• Knowledge: information. You know facts and concepts.
• Understanding: knowing how to use knowledge. You can apply what you know in context.
• Wisdom: knowing how to cross-apply knowledge and convert it into purposeful action. You recognize patterns across domains and act on them.

AI produces knowledge at unprecedented scale. Understanding (knowing how to apply it) is achievable through effort and experience. Wisdom (cross-applying knowledge into purposeful action) is the one stage AI cannot replicate, because it requires knowing what the action is in service of.

Most people are stuck at knowledge. High performers reach understanding. The people who change industries operate at wisdom.

The path from Player to Coach is roughly the path from knowledge to understanding. The path from Coach to Game Creator requires wisdom: seeing across domains, connecting what seems unrelated, and building for a purpose that goes beyond optimization.

The Applied AI Practitioner Path

Learning how to apply AI to grow businesses is like learning how to code 10 years ago. Inference is commoditized. LLMs are token factories. Platforms are becoming interchangeable. But trusted applied AI practitioners? The scarcest resource in the market.

xAI is sending engineers directly into corporate offices. Anthropic is hiring legions of forward-deployed developers. OpenAI is fighting over corporate clients. The companies building the most powerful AI on earth all looked at the market and said: "Businesses can't figure out how to use this. We need to go in and do it for them."

But here's what they can't do: relationships. Trust is local. Trust is relational. Trust is earned one conversation at a time. No corporation is going to monopolize the role of "trusted person who sits down with a business owner and actually helps them." That role is wide open.

You can start as a practitioner (Player/Coach), build trust and domain expertise through real engagements, and climb from there. See the Practitioner Playbook for how.

Infrastructure Levels

If you're building or joining a business, the level of infrastructure determines how far it can scale:

• Level 1: Documentation. Things are written down. Processes exist in docs and checklists. Nothing happens unless someone opens the file and follows the steps.
• Level 2: Triggered Workflows. You trigger a process and it runs. The human initiates, the system executes.
• Level 3: Autonomous Operations. The system acts on schedule or in response to conditions, whether you remember or not.

Most businesses never reach level three. If you can build at level three (or help a business get there), you are operating as a Coach or higher in the value hierarchy. That's the minimum viable position. That's where the demand is infinite and the supply is scarce.

Where to Start

1. Be honest about where you are. Most people are Spectators or Players. That's fine. The point is to know.
2. Stop consuming, start applying. The gap between Spectator and Player is action. Pick one thing and do it. Build something. Help someone. The knowledge only becomes real when you use it.
3. Learn to think in systems. The gap between Player and Coach is the shift from "I do tasks" to "I design the system that does tasks." Start noticing the workflows around you. Map them. Ask how they could be better.
4. Build trust through real work. Domain expertise and trust networks are the assets that appreciate as AI improves. They are not built by consuming content. They are built by doing real work with real people over real time.
5. Find your edge. What do you know deeply that others don't? What combination of skills and experience gives you a perspective that's hard to replicate? That's the raw material for becoming a Game Creator and beyond.

The AI economy rewards people who climb. The tools are accessible. The demand is infinite. The question is whether you'll stay in the stands or get in the game.

See also: Applied AI Economy | Don't Scale Slop | Minimum Viable Jarvis