The New Software Landscape · The Summary

What has actually changed?

The defining difference between the internet-driven era we're exiting and the AI era is the shift from connecting information to enabling action.

AI, and specifically agentic AI, removes the human from some of that loop for an expanding class of tasks. An AI agent does not just retrieve information about contract terms, it reads the contract, identifies issues, drafts a redline, and sends it for review. For two decades software helped a human do the work. What is emerging does it.

The agent layer is the new battleground. It is where software stops being a tool humans use and becomes a worker that does the job itself.

The pattern under the new stack

FIGURE 01 · THE STACK, REDRAWN

The internet stack and the AI stack, layer by layer

The internet era had a clean three-layer stack on top of the prior computer foundation. The AI era has a similar structure but with a critical new middle layer: the agent orchestration layer takes the models and makes them useful business tools that approximate human employees.

What is breaking?

The SaaS business model was built on a simple, elegant idea: charge per user, per month, forever. One human, one license. Revenue scaled with headcount.

Agentic AI is dismantling this logic. A single AI agent can now perform the tasks that previously required dozens of people. The industry is in an uncomfortable transition. The old model is broken; the new model is not yet standard. Three pricing paradigms are competing.

You can architect a business from the ground up with outcome-based pricing, something incumbents are structurally incapable of doing without cannibalizing their existing revenue. That asymmetry is your opening.

The asymmetry for builders

FIGURE 02 · PRICING SHIFT

Seat → usage → outcome: value repositions to the work

Approximately $285 billion in market value was wiped from global SaaS and enterprise software companies in 24 hours on Feb 3, 2026, as investors repriced the per-seat model out of existence. Gartner predicts pure seat-based pricing will be obsolete by 2028.

What it teaches

In the internet era, the greatest value was created not by those who built the infrastructure but by those who built the applications: Google, Amazon, Facebook, Salesforce, and hundreds of vertical SaaS companies.

The infrastructure companies were important, but the application builders captured more sustained value. The same is likely true in the AI era. The foundation models are impressive and important. But the $37 billion in enterprise AI spending is going increasingly to applications, to the products built on top of the models, not to the models themselves.

Build trains, not rails. The rails (foundation models, GPUs) are well-capitalized incumbents. The trains (vertical applications on proprietary data) are where durable value accrues.

The takeaway from the internet parallel

FIGURE 03 · THE TAKEAWAY

Build trains, not rails: value migrates up the stack

Build trains, not rails. The rails (foundation models, GPUs) are well-capitalized incumbents. The trains (vertical applications on proprietary data) are where durable value accrues.

The product-leader's lens

Not all AI businesses are equal. The ones that create durable value share specific characteristics. It helps to think in three categories.

Type 1 adds AI features at the edge, the weakest moat. Type 2 is AI-native, with the AI at the core. Type 3 combines AI-native architecture with deep domain knowledge, proprietary data, AND earned relationships inside a specific industry. This is where the most durable value creation lies for teams with domain expertise.

For a product leader with 10+ years of domain experience, Type 3 is the highest-value opportunity. The intelligence is becoming a commodity. The domain knowledge, the trust, and the relationships you spent a decade earning never will.

The argument for Type 3

FIGURE 04 · THE THREE TYPES

From AI at the edge to specialized AI at the core

For a product leader with 10+ years of domain experience, Type 3 is the highest-value opportunity. The intelligence is becoming a commodity. The domain knowledge, the trust, and the relationships you spent a decade earning never will.

The AI era is real, the revenue is real, and the opportunity is genuine.

The builders who will matter in this era are not the ones who understand AI the best. They are the ones who understand their domain the best and can translate that into systems that actually do the work. The window to establish a position is open, but will not remain open indefinitely.