Most product leaders will never ring the opening bell at the New York Stock Exchange. But many will eventually work for a company that is preparing to go public.

And when that happens, something subtle changes.
The roadmap may look the same.
The customers may be the same.
The product strategy may still contain the same initiatives you were discussing six months earlier.

But the economic system around those decisions has changed. And suddenly, some perfectly reasonable product investments become much harder to justify.

We're watching an extraordinary version of this play out right now with OpenAI and Anthropic.

Both companies have confidentially filed paperwork that gives them the option to pursue an IPO. Anthropic moved first. OpenAI followed shortly afterward, although it hasn't committed to when - or even whether - it will complete the offering.

If I were a product executive inside either company, I wouldn't primarily be asking:

What should we build next?

I'd be asking:

What does the business now need the product portfolio to prove?

Because those are very different questions.

At first glance, these companies don't exactly look starved for capital.

Anthropic's most recent private financing valued it at roughly $965 billion.

But AI has created an unusual economic problem.

Building frontier AI doesn't just require great researchers and great products. It requires extraordinary amounts of infrastructure, compute, energy and long-term capital commitments.

Across Amazon, Microsoft, Alphabet and Meta alone, AI-related infrastructure spending has helped push cumulative capital expenditures since the AI boom began beyond $1 trillion.

For companies such as OpenAI and Anthropic, therefore, access to capital isn't merely a finance problem.

Capital is part of the product strategy.

More capital can buy compute.
Compute can improve models.
Better models can attract customers and developers.
More adoption can generate revenue.
Revenue supports more investment.

And that creates the possibility of a flywheel:

Capital → Compute → Capability → Product → Distribution → Revenue → More Capital

That makes an IPO strategically interesting.

Public markets potentially provide access to a vastly larger and more liquid pool of capital. They create liquidity for employees and early investors. Public stock also becomes currency that can be used for acquisitions and compensation.

But there's another reason the timing matters.

If Anthropic reaches the public markets before OpenAI, investors suddenly have something they don't have today:

A publicly traded frontier AI company whose economics they can inspect every quarter.
Revenue growth.
Margins.
Customer concentration.
Infrastructure commitments.
Capital intensity.
Cash generation.
Retention.
Enterprise adoption.
And eventually, return on invested capital.

That company starts helping the market answer a much larger question:

What is a frontier AI company actually worth?

Anthropic's filing has therefore created strategic pressure. Reuters reported that its move could allow it to establish a valuation benchmark for the AI sector and potentially pressure OpenAI's own timetable.

That's why I wouldn't describe this simply as:

The more interesting question is:

And that has enormous implications for product leaders.

Six months before an IPO, I would want every major product investment examined through a different lens.

Not:

Is this a good feature?

Not even:

Will customers use it?

But:

What does this investment prove about the economics of this company?

Suppose you have five major bets competing for capital:

All five could have excellent product arguments.
But approaching an IPO, the portfolio question becomes much harder.

That is executive-level product judgment.

You aren't prioritizing features anymore.
You're helping allocate capital against the future economic story of the company.

Every significant product initiative should have an economic impact attached to it.

Not fake assumption.
An assessed impact.

An IPO isn't simply a celebration of growth.
It's a transfer of financial scrutiny.

Private investors may tolerate enormous uncertainty because they're underwriting a future category winner.

Public investors eventually ask harder questions:

Product strategy has to help answer those questions.

Imagine having to explain one of your largest investments on an earnings call.

"We spent heavily because AI agents seemed strategically important" isn't much of an explanation.

Neither is:

"Our competitors had it."

You want to know which bets can eventually become:

This is especially important in AI.

A product can have extraordinary adoption and still be economically unattractive. If every additional interaction carries meaningful inference costs, usage itself isn't necessarily evidence of value creation.

The executive product question becomes:

This is the dangerous one.

Preparing for public markets can push organizations toward making everything look cleaner.

Revenue.
Margins.
Forecasts.
Roadmaps.

The temptation is to optimize product decisions for the story investors want to hear.

That's where executive judgment matters most.
Because the objective isn't to create a beautiful IPO.

It's to create a company that still deserves its valuation three years later.

Before going public, a company can largely choose when investors see its numbers.

Afterward, the clock starts ticking every quarter.

Suddenly the organization has two time horizons operating simultaneously:

and

Weak product organizations allow the first question to consume the second.

Strong product executives protect both.

That could mean defending expensive foundational investments whose returns won't appear immediately.

It could mean killing highly visible initiatives whose economics no longer make sense.

It could mean refusing to chase competitors even when analysts are asking why you don't have their newest feature.

And it could mean reallocating hundreds of millions -or eventually billions - away from yesterday's strategic priorities.

Because the roadmap isn't just a product artifact anymore.

It is part of the company's capital allocation system.

This is where this case becomes particularly interesting.

A company can have extraordinary technology, enormous revenue and incredible growth - and still be a disappointing public investment.

The valuation might simply assume too much future success.
Infrastructure costs might grow faster than monetization.
Competition could compress pricing.
Model differentiation could narrow.
Enterprise customers could become increasingly multi-model rather than loyal to one provider.
Open-source or lower-cost competitors could change the economics.
Regulation or geopolitical restrictions could constrain markets.
Or investors could simply stop valuing AI growth at today's multiples.

Some investors are already questioning whether the extraordinary level of AI capital spending will generate returns quickly enough to justify it.

That is why the IPO itself isn't the finish line.

It is the beginning of a much harder test:

And product sits directly in the middle of that question.

If I were a VP Product, CPO or senior product leader at OpenAI or Anthropic today, I'd take the roadmap and ask:

Not because investors should dictate the roadmap.

They shouldn't.

But because forcing yourself to answer that question exposes something product organizations frequently avoid:

That's a very different question from:

"What should we prioritize?"

And it's one of the biggest transitions product leaders have to make as they move toward executive-level product judgment.

The higher you go, the roadmap stops being primarily a list of things your teams intend to build.

It becomes a statement about where the company believes its capital will create the greatest future return.

And an IPO simply makes that judgment much more visible.

Most product leaders think going public is primarily a CEO, CFO, and board decision.

The decision may be. Making it work isn't.

Product leaders play a critical role in building the growth, economics, and product strategy that the company will eventually have to defend to public investors - and in making the much harder decisions that come after the IPO.

This is exactly the kind of executive-level product judgment we practice in my cohort: learning to see the business behind the roadmap and make product decisions through that lens.

I'm opening the next cohort in September, capped at just 5–6 people, with one seat already taken.

If you want to become the product leader trusted with bigger, more consequential business decisions, apply for the September cohort.

Until next time,
Elena Leonova