Events & webinars for SaaS and AI companies.

We architect and build production-ready AI products for SaaS companies that need to scale — turning roadmaps into results that last.

Softlandia

**A live webinar on the Supply Chain of Intelligence™ framework, AI compression, rising dependency economics, and how founders should reposition before their layer gets absorbed.**

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## **Who This Is For**

Founders, CEOs, CTOs, product leaders, and AI teams building:

*   SaaS products
*   AI-native applications
*   copilots
*   workflow automation platforms
*   enterprise AI tools
*   agentic systems

***

## **The Core Problem**

Most AI companies are competing on features while the real battle is happening deeper in the stack.

As AI juggernauts expand upward:

*   models absorb workflows
*   platforms bundle capabilities
*   surfaces commoditize
*   margins compress
*   dependency costs rise across the ecosystem

Many founders still cannot clearly answer:

*   Where does our product actually sit in the AI stack?
*   Which layers are becoming commodities?
*   Where does durable value accrue?
*   What happens if the layers beneath us absorb our functionality?
*   What compounds over time in our product?
*   Are we building defensibility — or renting intelligence?

Most products sit higher in the stack than they realize.

This webinar introduces a structural framework for understanding where AI value is created, where products become vulnerable, and how companies can reposition before compression accelerates.

***

# **What You’ll Learn**

[The Supply Chain of Intelligence™](https://supplychainofai.com/)

A practical framework for understanding how modern AI products are structured across:

*   infrastructure
*   models
*   execution
*   orchestration
*   surfaces
*   trust systems
*   and institutional memory

You’ll learn:

*   where your company sits
*   which layers are exposed
*   which layers compound
*   where durable moats still exist

***

## **The AI Compression Wave**

Why:

*   model providers
*   hyperscalers
*   platform ecosystems
*   AI-native incumbents

are increasingly compressing companies above them in the stack.

We’ll explore:

*   how compression works
*   why some products become features
*   why others compound
*   how value migrates across layers over time

***

## **The Hidden Economics of AI Dependency**

AI costs are no longer just about tokens.

Founders are increasingly exposed to:

*   usage-based pricing shifts
*   orchestration overhead
*   inference dependency
*   retrieval costs
*   memory persistence
*   verification complexity
*   upstream pricing pressure

Every layer beneath you in the stack increasingly influences the economics of the layer above you.

We’ll discuss:

*   who gets squeezed hardest
*   why
*   what structural moves reduce long-term exposure

***

## **Where Defensibility Still Exists**

Not all layers are equally vulnerable.

We’ll explore where durable value is still accumulating:

*   domain execution
*   workflow ownership
*   orchestration
*   verification systems
*   institutional memory
*   embedded organizational intelligence

***

# **Live Company Mapping (If time permits)**

We’ll also analyze real companies through the framework, including examples like:

*   OpenAI
*   Microsoft
*   Gamma
*   Cursor
*   Harvey

and examine:

*   where they sit
*   where they’re expanding
*   what they own
*   where compression risk exists

***

# **What You’ll Leave With**

→ A clear understanding of where your product sits in the AI stack

→ A structural lens for evaluating defensibility and compression risk

→ A better understanding of AI dependency economics and pricing pressure

→ A roadmap for where your company should move next to become harder to replace

→ A shared vocabulary for discussing AI strategy internally with product, engineering, and leadership teams
