Infinite Software

I think the infinite software era is here.

For most of the history of software, the constraint was pretty obvious. Software was expensive to build. Engineering teams were expensive. Every new product created more code to maintain, more infrastructure, more integrations, more edge cases and more things that could break.

So companies had to choose.

You picked a problem, built a product around it and became very good at that product. If you were building software for freight forwarders, maybe you did shipment visibility. Someone else did bookings. Someone else built the ERP. Someone else built the CRM. Someone else handled payments, accounting or financing.

Entire software categories emerged because there simply wasn't enough software to go around.

I think AI changes this much more fundamentally than we currently appreciate.

It isn't simply going to help companies write the same amount of software with fewer engineers.

Companies are going to write vastly more software.

And eventually, the best companies are going to write almost everything their customers need.

That is what I mean by Infinite Software.

From products to complete platforms

Imagine you are building an AI-native company for freight forwarders.

Today you might start with one painful workflow. Perhaps quoting. Perhaps document processing. Perhaps shipment tracking.

But once you have the customer, the data, the integrations and the intelligence required to understand how that freight forwarder actually operates, why would you stop there?

You can do bookings.

Then tracking.

Then customer communication.

Then documentation.

Then invoicing.

Then payments.

Then collections.

Then CRM.

Then accounting.

Then eventually much of the ERP itself.

Historically you could argue that this was a terrible idea. It would require hundreds of engineers, years of development and a giant product organization. The company would lose focus long before it ever got there.

But what happens when an extremely good engineering team has built its own AI development infrastructure, coding agents, testing systems, evaluation harnesses, design systems, deployment infrastructure and internal frameworks that allow it to ship software at 10x or 50x the previous rate?

At some point the question flips.

It is no longer:

Why should we build this?

It becomes:

Why would we not build this?

If the customer already trusts you, the data is already sitting inside your system and the new workflow naturally connects to everything else you provide, the marginal cost of building the next piece of software starts becoming very small relative to the value of owning the workflow.

That is a completely different software world.

Mercury Books is a perfect example

Mercury started as a bank for startups.

Now it has launched Mercury Books, a full double-entry accounting product sitting directly inside Mercury. Transactions, reconciliation, journal entries, P&L, balance sheet, cash flow, AI categorization, all tied directly into the place where the money already moves.

If you think about the old software world, this is kind of remarkable.

Why is a neobank building accounting software?

Because in the infinite software world, that might be the wrong question.

The better question is: why shouldn't it?

Mercury already has the customer. It already has the financial data. It already sees banking, cards, invoices and bill payments. Accounting is an adjacent workflow sitting directly on top of the same data.

And once accounting is there, there will be another adjacent workflow. And another one after that.

Mercury itself describes Books as part of a future where a company's entire financial life can live inside Mercury.

That is the direction I think a lot of software is going.

Not a bank with a few additional features.

A complete financial operating system built around a customer Mercury already owns.

ElevenLabs is another version of the same thing

Look at ElevenLabs.

At one level, ElevenLabs owns foundational voice infrastructure. Developers can build applications on top of its models and APIs.

But ElevenLabs is now also offering Reception, a finished AI receptionist that a small business can turn on in minutes. It answers calls, understands the business, books appointments, transfers calls, takes messages and handles customer interactions.

There are already plenty of startups building AI receptionists.

So should ElevenLabs stay underneath them as infrastructure?

I don't think that question has an obvious answer anymore.

If ElevenLabs already has the models, the voice infrastructure, the agent platform and the underlying technology, why wouldn't it package some of the highest-value applications itself?

And then why stop at reception?

You can imagine the same infrastructure expanding into sales calls, support, collections, scheduling, lead qualification, customer service and dozens of other voice-heavy workflows.

Again, the boundary between infrastructure and application starts becoming much less rigid.

The model company writes applications.

The bank writes accounting software.

The vertical application writes the ERP.

Everyone moves into everyone else's territory.

Software abundance changes company boundaries

I think this is the important part.

We have spent decades thinking about software companies using boundaries that were partly created by the economics of producing software.

CRM was one category.

Accounting was another.

Banking was another.

Customer support was another.

ERP was another.

These boundaries felt natural because companies were built around them.

But many of them may not actually be natural.

They may simply be artifacts of a world where software was expensive to produce.

Once software becomes abundant, those boundaries begin to collapse.

A company with the strongest relationship with a customer can simply keep expanding around that customer.

A company with the strongest underlying infrastructure can keep moving upward into applications.

A company with the best system of record can keep adding workflows around the data it already owns.

And a vertical AI company can keep expanding until it starts looking less like a point solution and more like the operating system for an entire industry.

This is why I think AI-native software companies may look very different from SaaS companies of the last twenty years.

The goal may no longer be to dominate a category.

The goal may be to cover the customer.

The scarce thing will no longer be software

This doesn't mean every company should randomly build hundreds of features.

There is still such a thing as bad software. There are still products customers don't want. There are still workflows where you lack credibility, data or distribution.

But I think the constraint is moving.

The scarce resource used to be the ability to produce software.

Increasingly, the scarce resources will be:

customer ownership,

distribution,

proprietary data,

workflow context,

trust,

and permission to do more.

Once you have those things, software becomes almost infinitely expandable around them.

This has pretty profound competitive implications.

For years we have talked about software moats in terms of features. But features become much less defensible if every good company can manufacture software extremely quickly.

The moat moves somewhere else.

Who owns the customer?

Who owns the data?

Who sits inside the workflow?

Who is trusted enough to take the next action?

Who can distribute the next product essentially for free?

Those questions become much more important.

And it also means that product roadmaps themselves may change.

The traditional startup advice was to focus relentlessly. Do one thing exceptionally well. Don't become a bloated suite.

That advice was correct in a world where every additional product imposed enormous organizational and engineering cost.

I am not sure it will remain equally correct in a world where a 30-person AI-native engineering organization can eventually produce what previously required 300 or 3,000 people.

The best companies will still start narrow. They will still need a wedge.

But the wedge may increasingly just be the entry point.

Once they have earned the right to expand, they will.

Everybody will write everything

This is why I keep coming back to the phrase Infinite Software.

We are entering a period where the amount of software produced is going to explode.

Not because the world suddenly has 100x more software companies.

Because every software company can potentially produce 100x more software.

And as that happens, the distinction between product companies, platforms, infrastructure companies and application companies will get increasingly blurry.

Banks will write accounting software.

Model companies will write applications.

Vertical AI companies will write ERPs.

Infrastructure companies will move up the stack.

Application companies will move sideways across workflows.

Everyone will cover more ground.

The winners, I suspect, will be the companies that understand this early and build themselves for it. Not just by using AI coding tools, but by creating engineering systems where software production itself becomes a massively scalable internal capability.

Because once you can manufacture high-quality software extremely cheaply and extremely quickly, leaving an obvious customer need for somebody else to solve starts making less and less sense.

For most of software history, companies had to decide what software not to build.

We may now be entering the opposite era.

Everybody will build everything they have the right to build.

That is Infinite Software.