Enter the League: Design AI-native systems with taste. Ship products that scale.
AI Strategy League is a builder league for founders and cross-functional operators who move beyond pilots to design and ship AI-native products in the real world.
Benefits
What You’re Entering
The League is a structured AI-native system builder environment where you:
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Design and build AI-native systems end-to-end
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Integrate product, engineering, design, and go-to-market into one operating model
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Build feedback loops for adoption, incentives, and outcomes
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Ship something real, not a prototype, not a deck
Design for
Who the AI-Native System Is For
Built for operators who ship under real constraints and care more about outcomes than ideas: You're already be comfortable building, willing to operate under constraints, and more interested in outcomes than ideas.
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Founders
You’re building AI-native products and are accountable not just for vision, but for shipping systems that people actually use, trust, and pay for in the real world.
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Senior Product, Growth & AI Leaders
You own execution across product, growth, and AI, measured by outcomes, adoption, and impact, not decks, demos, or disconnected roadmaps.
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Cross-Functional Builders
You work across product, engineering, design, and go-to-market to turn AI intent into reliable, scalable systems, not one-off experiments or technical novelty.
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Design & Engineering Leaders
You design systems, not just interfaces or models, optimizing for behavior, incentives, reliability, and scale, not isolated screens or proofs of concept.
Why Apply to Enter
Why Enter the League
If you’re ready to stop experimenting in isolation and start building systems that hold up in reality, the League is where that work begins to help you build AI-native systems that work and keep working as they scale.
Systems and Adoptions
We are building a system that produces products, outcomes, and insight. You design AI-native systems that hold together under real-world use, not just stacks or isolated workflows.
Adoption & taste by design
What you build is shaped by real user behavior, incentives, and judgment.
Outcomes that compound
Progress is measured by what ships, what gets used, and what continues to work as it scales.
What is an AI-Native System
An AI-native system is a system where intelligence is the core operating layer, not an add-on.
An AI-native system:
✅ Is shipped in production, adopted by real users, and produce measurable outcomes
✅ Uses AI to make or augment decisions, not just generate content
✅ Is designed around real workflows, incentives, and constraints
✅ Improves with usage (feedback, signals, learning loops)
✅ Ships with adoption and accountability built in
✅ Continues working as usage, data, and complexity scale
What it is NOT
❌ Adding an LLM interface on top of a legacy workflow
❌ A chatbot bolted onto an existing product
❌ A collection of prompts or prompt libraries
❌ A demo, proof-of-concept, or innovation lab project
❌ Prompt engineering without integration into workflows
❌ A feature that depends on manual babysitting "Human-in-the-loop”
❌ AI as cost-cutting theater: Replace humans with AI” mandates
Benefits
What results you can expect
The League is a structured builder environment where you leave with:
A working AI-Native system
Clear execution standards
Artifacts you can reuse, extend, and scale
Enter the League
Let's map out your current performance and friction points in 30 minutes:
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identify your true pipeline origination;
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bridge the gap between your ideal client and your current audience;
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categorize your audience by their structural bottlenecks;
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audit and analyze your "scaling seiling", your growth is currently limited by human bandwidth and manual workflows;
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evaluate which activities drive exponential growth versus those that cause operational drain.
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How the League Works
The League is designed to help you finish, not just start.
System Framing
You start by defining the real problem space: user intent, constraints, incentives, and success metrics.
System Design
You design an AI-native execution system that spans product logic, workflows, interfaces, and feedback loops.
System Build
You implement and test the system in the real world — with real users, real data, and real tradeoffs.
System Review
You pressure-test what you built: what shipped, what broke, what compounded, what didn’t.
FAQ
Frequently Asked Questions
The League is designed for founders and senior operators who are actively building, or responsible for shipping AI-powered products or systems.
That includes:
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Founders and startup leaders
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Product, growth, and AI leads
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Small cross-functional teams operating under real constraints
If you’re experimenting casually or looking for inspiration, this isn’t the right fit.
If you’re accountable for outcomes, it is.-
No, but you do need decision-making authority or direct influence over what gets built.
Many participants are not engineers, but they:-
Own product direction
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Define workflows and incentives
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Work closely with technical teams
You’ll design systems, not write production code (unless that’s already your role).
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You leave with:
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A designed and shipped AI-native system (or a production-ready version of it)
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Clear system logic and ownership
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Adoption and feedback loops built in
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Artifacts your team can continue to build on
This is not a deck or roadmap.
It’s something real your team, and organization can use.-
ourses teach concepts. Advisory gives opinions. Accelerators optimize pitch and growth narratives.
The League is about execution. You design and build one system, end to end with guidance, pressure, and peer accountability until it works.Yes, especially if:
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AI efforts feel fragmented
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Adoption is lower than expected
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Systems don’t hold up beyond demos
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Teams keep switching tools
The League helps you re-architect or refocus what already exists into a system that actually works.
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Expect focused, high-leverage involvement over 10–14 days.
This includes:
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Async pre-work
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Live build sessions
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Hands-on system design and validation
It’s intense by design, but optimized to replace months of scattered effort.
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Both.
Some participants join solo.
Others join as part of a small team.What matters is that someone in the sprint can make decisions and move work forward.
Examples include:
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AI-native product or feature systems
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AI-driven activation or growth systems
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Internal AI systems that change how decisions are made
If the system can’t be adopted, measured, and owned, it’s not a fit.
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The goal is not perfection, it’s viability.
By the end of the sprint, your system should:
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Be usable
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Be adopted by real users
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Have clear ownership and next steps
You’ll know exactly what works and what scales next.
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We keep cohorts intentionally exclusive and intense.
Applications help ensure:
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Participants are aligned in intent and seniority
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Systems are viable to build within the sprint
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The cohort remains high-signal
Not everyone who applies will be accepted.
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Yes, as long as participants operate within real constraints and have a clear mandate.
Many systems are designed to:
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Integrate with existing tools
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Respect compliance and governance
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Improve decision quality, not just speed
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After the sprint, you can:
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Continue building with your internal team
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Access the League’s library and resources
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Explore scaling and growth support if relevant
There is no obligation to continue beyond the sprint.
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The League is designed to replace:
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Months of experimentation
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Expensive misbuilds
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Disconnected AI initiatives
If shipping a working AI-native system would materially change your trajectory, the sprint pays for itself quickly.
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