An industry-defining macroeconomic model for AI · across verticals
A defensibility map for AI companies.
The AI stack explains how intelligence is built. The Supply Chain of Intelligence explains where intelligence becomes economically defensible.
Is your product a moat, a workflow, or a wrapper a platform will absorb? Supply Chain of Intelligence™ scores every AI product across 10 layers and 50 sublayers, from compute and data to workflows, surfaces, and memory, and tells you where value actually accrues.
Supply Chain of Intelligence™, the 10 layers of the generative AI stack.
AI Stack ⇄ Supply Chain of Intelligence — different questions, different answers
SCOI ·supplychainofai.com
- Category reframe
Not another AI stack. A different question entirely.
The AI stack explains how intelligence is built. The Supply Chain of Intelligence explains where intelligence becomes economically defensible.
Axis
AI Stack
Supply Chain of Intelligence™
Category
AI Stack / AI Value Chain
Contains both, and adds gatekeeping, currents, flywheels, absorption
Question
How is AI built?
Where does value accrue?
Lens
Architecture
Economics
Unit
Components
Bottlenecks
Behavior
Static layers
Dynamic system
Discipline
Technology
Strategy
Audience
Engineering
Investment & Product
Output
Describes
Predicts
The AI stack is one input to the Supply Chain of Intelligence — not its competitor.
- Where AI Transformation Happens · 01
AI is transforming three things. This framework is about one of them.
Most AI roadmaps confuse the three. They are not the same problem, they do not have the same defensibility, and they should not be scored the same way.
01
Internal Operations
Copilots, RPA, productivity. Cost out.
Real ROI. Rarely a moat.
02
Distribution & GTM
AI in marketing, sales, support. Reach up.
Easier wins. Easier to copy.
03You are here
Core Product
AI inside what you sell. The product itself becomes intelligent.
Hardest. Most defensible. This site is about this.
Supply Chain of Intelligence™ is a framework for area 03, Core Product. It does not score your internal copilots or your marketing automation. It scores whether the AI inside what you sell is defensible.
- Two Lenses · 02
On Core Product, you need two lenses, not one.
Most teams only use the first lens. They ship a real user need, score a viral launch, and then a platform absorbs them in a release cycle. The second lens is what this framework adds.
LENS 01Necessary
The User Lens
JTBD · NMBA · ICP · positioning
What job is the user hiring this for? What’s the next most valuable action? Who exactly is the buyer? This lens finds demand.
Tells you if anyone wants it.
+
+
LENS 02The missing one
The Intelligence Lens
10 layers · 50 sublayers · defensibility
Which of the 10 layers does your product actually own? Data? Workflow? Memory? Or are you a thin surface on someone else’s model? This lens proves defensibility.
Tells you whether you survive the next platform release.
User Lens without Intelligence Lens → a wrapper with traction. Both lenses together → a moat with users.
AI is a supply chain. Like gold: ore in the ground, refining, assay, retail, the ring on a finger. Value moves through 10 layers, most products sit on one, usually the wrong one.
Two AI-native products. Same wave. Opposite trajectories.
L7
Jasper
Sat on one layer
$1.5B → ~$300M
A thin UX layer over a general model. When the model owners shipped the same surface for free, there was nothing structural left to defend.
LAYERS OWNED · L7 only
L5
Cursor
Owned four layers
$9B+ and compounding
Owns the IDE workflow, the indexing pipeline, the agent loop, and the project memory. Every layer reinforces the others - the model is the only commodity in the stack.
LAYERS OWNED · L4 · L5 · L6 · L8
Same job. Different layers. Different fate. The map below shows which layers compound and which collapse.
- Same company. Two lenses.
Where Cursor sits, through two frameworks.
Same company, same facts. The AI stack gives you one word. The Supply Chain of Intelligence gives you a map — and an answer to the only question that matters: is this defensible?
Through the AI Stack
Application.
· Done ·
Categorization. No verdict. No mechanism. No flywheel.
Through the Supply Chain of Intelligence™
L7SurfaceSurface: Owns the IDE — the daily writing surface.
Screenshot this. Paste it anywhere. Cite it where it helps.
The Framework, At a Glance
SCOI ·supplychainofai.com
The Framework · At a Glance
Supply Chain of Intelligence™
The 10 layers of the generative AI stack, not logistics, not freight.
L8MemoryRetention, learning, compounding context. What the system remembers.
L7SurfaceInterface, presentation, experience. How the user meets the intelligence.
L6OrchestrationWorkflow, routing, coordination. How skills compose into outcomes.
L5ExecutionApplied skills and capabilities. Doing the actual work.
L4AccessConnectivity, permissions, integrations, the pipes layer.
L3GatesTrust, acceptance, approval. Can the system be allowed in?
L2ModelsIntelligence refinement. Rent early, build custom at scale.
L1DataThe raw input. What data do you have that nobody else can get?
L0InfraThe shovels. Chips, data centers, networking, cloud, edge, what is needed to process intelligence.
L−1ResourcesWhat supports the chain. Energy, water, fabs, materials, skilled trades, the inputs the entire stack consumes.
The Four Structural Laws
I
Intelligence commoditizes downward.
II
Value accrues at bottlenecks.
III
Surface captures attention; chain captures power.
IV
Generation and verification must be separate.
10 layers · 50 sublayers · 4 laws. The map for every AI strategy conversation.
SupplyChainOfAI.com
Sales & Marketing Tech, Layer Matrix
SCOI ·supplychainofai.com
WORKED EXAMPLE · SALES & MARKETING TECH
Same category. Different layers. Different fates.
SWIPE→
COMPANY
Resources
L−1
Infra
L0
Data
L1
Models
L2
Gates
L3
Access
L4
Execution
L5
Orchestration
L6
Surface
L7
Memory
L8
Claude / Anthropic
L2 giant
EXPANDING ↑
NVIDIA
L0 monopolist
DOMINANT
Clay
$3B · data + workflow
FORTIFIED
Sierra
$15B · agent infra
FORTIFIED
Apollo
GTM data + L2 connector
L1+L2 SURVIVOR
Outreach
Sales Engagement
COMPRESSES
Core Significant EmergingEmpty = no presence
Claude owns L2 and is reaching into L5/L6/L7, gravity at work. Apollo thins toward a data + connector role as Claude becomes the marketer's command center. Much of martech gets compressed unless it deepens into L1 or L8.
Product leaders, founders, and investors using the 10-layer map.
Reactions from workshops, 1:1 reviews, and LinkedIn exchanges with people who have applied the framework to their own roadmap, thesis, or category. Venture partners have called it “a macroeconomic, industry-defining model” once the Applications view and vertical maps click into place.
Most 'AI frameworks' are taxonomies. This one is absolutely designed to be a macroeconomic, industry-defining model. Once you see the Applications view, the vertical maps, and the Cube together, it stops feeling like a stack diagram and starts feeling like a way to price an entire industry.
PM
Partner, Multi-Stage Venture Fund
Investment Partner (attribution withheld)
Macro lens
JTBD tells you the length of the customer need. Supply Chain of Intelligence tells you the depth of the answer, how many layers you have to own to deliver it durably. 'Trust the output' is one job; you can answer it shallow with a verifier widget, or deep with an L3 gatekeeping layer baked in. The framework finally gave me a vocabulary for that trade-off.
BL
Bill Leece
AI Product Leader, ex-Google · Indeed (AI Agents & Evals)
JTBD × Chain
I have sat through a hundred 'AI strategy' decks. This is the first one that told me which layer a product was actually on, and which layer it had to move to before the model layer ate it. The diagnostic is brutal in a useful way.
RM
Ruth Morales Zimmerman
Investor · Venture & Private Markets Commentator
Filter
We were calling ourselves an 'AI platform' and the framework made us see we were a thin L7 surface on top of someone else's L2. We rewrote the roadmap inside a week to compound on L1b proprietary data instead. The language travels, engineering and GTM both speak it.
Working on AI and ads inside a platform company, you feel the layer compression in real time, what was an app last quarter is a feature this quarter. The 10-layer map is the first framework that names that dynamic instead of describing it after the fact.
MH
Mahek Hooda
Senior Product Manager · AI & Ads · Meta (ex-Microsoft)