Notes on where seat-based pricing is going

Illustration of an office with computers and chairs, where the floor transforms into circuit-like patterns, blending technology with workspace.
A heashot of Arnon Shimoni, co-founder & marketing at Paid.ai.
Arnon Shimoni 25 Oct 25

Everyone (mostly us) keeps saying seat pricing is dead, and some people are arguing with us online.

I think that's cool, but it's because they don’t understand why it’s dying.

For twenty years, SaaS revenue scaled with headcount.
More humans = more seats.
That logic held so long that we stopped questioning it.

Then the humans disappeared.

So seat pricing didn’t just die, its margins migrated. The value once captured in human licenses now lives in compute bills.

A hose showing how Agents replace users, teams get smaller, and AI eats the revenue

But let's understand why:

The world seat pricing was built for

Seat-based pricing made perfect sense in the era when software automated people. A CRM helped a sales rep. A design tool helped a designer. A support platform helped an agent.

You could literally count your customers by the number of logins.

Here, I'll put it in a table:

Era

Unit of work

Unit of value

Pricing proxy

SaaS 2005–2020

Human performs workflow

Productivity per human

Per-seat license

That means growth looked like this:
more employees → more seats → more ARR.

I definitely experienced this first-hand at the SaaS companies I worked at, and it was beautifully linear and predictable.

Dropbox's public data shows it pretty well too.

Dropbox's revenue growth between 2015 and 2024, showing correlation between revenue and user counts

And for a long time, that linearity made everyone lazy.

The first cracks

Seat pricing broke quietly, and then all at once.

Three structural shifts made it inevitable:

Shift

What changed

Why seats fail

Agents replace users

Work is done through APIs and automation

Agents don’t log in and don't use a seat

Teams get smaller

Ten people with agents can do the work of a hundred

Headcount stops scaling with output, and not everyone needs these tools

AI features eat their own revenue

Every “productivity” feature removes usage minutes

Seat expansion becomes self-defeating

Seat pricing depends on more humans doing more work. AI depends on fewer humans doing less work.

4x more databases are created by AI Agents than by humans on Neon
4x more databases are created by AI Agents than by humans on Neon

That’s not a market correction. It’s a phase change.

Hybrid pricing is just a pause button

Hybrid pricing (seats + usage + minimums) is a holding pattern. Companies add "usage components" not because it’s the future, but because it helps them stay afloat while their core metric stops working.

Hybrid pricing is what disruption looks like from the inside - and you can see it in product telemetry across the industry:

  • Seat count per customer is flat or shrinking.
  • Compute cost per customer is rising.
  • AI adoption cuts user logins but increases workload volume.

How we got trapped by our own success

Seat pricing worked so well it trained an entire generation of SaaS companies to chase adoption metrics that don’t matter anymore.

User logins.
Seats activated.
Seat expansion revenue.

Those signals once indicated health.
Now they measure inertia.

When customers replace 50 support agents with one orchestrator running 50 AI assistants, seat metrics collapse — even though the system’s output increases 10×.

The problem isn’t that usage-based pricing is new.
The problem is that SaaS never had to think about what it’s actually selling.

The new unit of value

The next pricing substrate is not per-seat, but per-work.
We’re already seeing three archetypes emerge:

Model

Example

Unit of value

Usage-based

API calls, tokens, compute minutes

Workload volume

Outcome-based

Leads verified, tickets resolved

Business result

Agent-based

Cost per autonomous agent / month

Synthetic labor

The line running through it all is clear (at least to some of our partners): value tracks work done, not humans doing it.

Unfortunately, this will feel messy for a few years
Just like AWS billing did in 2008: complex, unpredictable, but a lot more aligned with the actual source of value.

2025 or Q1 2026 is the time to act

The SaaS economy grew up during an era of abundance with cheap capital, expanding headcount, endless GTM motion.
Seat pricing thrived because companies were hiring faster than they were automating, but 2021-2022 is over.

AI agents don’t take vacations, and they don’t show up in HRIS exports (not yet, anyway).
They don’t need training seats, onboarding credits, or license renewals.
They just execute.

Seat pricing is a tax on humans. And in the next decade, humans stop being the primary unit of work.

What replaces the seat

We’re heading toward agentic billing models that look a lot like infrastructure pricing:

  • Pay for outcomes, not headcount.
  • Bill for concurrency, not users.
  • Measure success in work completed per dollar spent.

Yes, it'll start rather messy with the tokens/credits, hybrid models and caps - but this will converge toward work-per-unit-time and eventually outcomes.

When that happens, pricing becomes both simpler and truer:
Software bills for what it delivers, not who touches it or how much inputs it used.

What this means for SaaS founders (and investors)

  • If your growth depends on seat expansion, you’re already in decline.
    Expansion revenue now fights automation, not benefits from it.
  • If your pricing isn’t margin-aware under AI load, it will implode.
    Compute costs eat seats for breakfast.
  • If your product’s AI layer doesn’t come with a billing and monetization rethink, it’s just decoration
    You're not disrupting your own business enough, and someone else will.

The new denominator

Every few decades, software changes its unit of measurement.

Era

Unit of measure

Desktop

License

Cloud

Seat

AI / Agentic

Work (and later value)


The tl;dr is seat pricing isn’t dying from lack of innovation - it’s dying from irrelevance.

You can fight it, but when the average company has more agents than employees,
the only question left is simple:

What’s your new denominator for software value?

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