It’s the first thing Taufiq Khan (TK), Chief Product Officer (CPO) at Ordermentum, called out when we asked him about barriers in product.

Product management is in a period of turbulent but exciting transition—as timelines, expectations, and outputs continue to be shortened, escalated, and pushed forward.

Having enough data isn’t the issue. Instead, product managers (PMs) face a new problem: how do you keep up with demand without becoming a bottleneck?

We sat down with TK to learn more about the common problems he’s seeing—and to talk about how his team is building a “Product Brain” to help his PMs thrive.

Effective product management follows a four-stage loop:

“The idea is the faster you go through this loop, the more on the right track you are,” TK explains. “But while the loop itself hasn’t changed so much, the AI acceleration across it has been uneven.”

There are lots of reasons why product managers are feeling burnt out. Macro-economic factors. Always-on Slack culture. Remote working scope creep. But TK believes product data acceleration is the primary driving force causing most of the trouble.

“Over the last few months, product data richness has exploded, both in depth and frequency,” TK says. “Meanwhile, engineers are shipping faster and need quicker, high-quality direction on what to do next. So now, PMs need to synthesize even faster, creating clarity based on a firehouse of to-the-minute data. And when they can’t, they become a serious bottleneck.”

Of course, the severity of the bottleneck only gets worse as demand increases, too.

“PMs are used to shaping up a couple of big things each quarter,” TK explains. “Now, that number looks like five or six or even more, but the quality has to remain the same. That means PMs are tracking usage analytics, sourcing feedback, capitalizing on customer voice shifts, monitoring competitors, and more on significantly more projects a quarter, all while trying to keep up with the biggest technology wave in decades.”

It’s clear the old norm of shaping up multiple months of work for an engineering team doesn’t work anymore. Instead, product decision-making needs to be redesigned systematically to tackle this growing bottleneck.

“We’re at a critical juncture for product management,” TK says. “We need to design for a world where the majority of answers PMs need to give are easier to synthesize and access by whoever needs them. That typically starts by writing out a set of simple, focused product context docs like competitive positioning, strategic choices, and design principles—usually requiring product managers to codify all the tacit knowledge that they already use to make decisions. Then, by designing a more automated system that enriches this context from daily signals like customer call transcripts, usage analytics, competitor monitoring, and anything else PMs already track.”

So, that’s exactly what his team has done. Using AI tools connected to their different SaaS platforms, they’ve plugged in every customer interview, sales call, support ticket, and usage pattern into what they’re describing as their product context layer.

On top of this, they’ve built out a suite of skills and agents to leverage this context as their all-knowing Product Brain.

“Back in the day, our Sales team would need to figure out answers to questions like, ‘What were the top five themes from customer conversations in the last quarter?’ Now, I can get my AI to look at every single call and transcript, unlocking super-specific details on tonality and opinion en masse.”

TK recommends building a Product Brain at your organization before bottlenecks become a significant barrier. He describes the brain in two simple parts:

“Even if your organization isn’t AI-pilled yet, you still need to start preparing by getting your inputs organized,” TK advises. “AI is really good at getting the knowledge of yesterday sorted out for today, but I think it hopefully frees people up to focus on the edges and advancing and innovating.”

This process isn’t about replacing PMs with AI. Instead, it’s using tools to allow your team to spend more time with customers and the organization.

“With this approach, we’ve seen PMs shape a product feature in days, rather than weeks. It’s allowed us to ship more, too,” TK explains. “Automating the cruft at the bottom that’s not as fun and then hopefully doing some more exploration, which is the fun part.”

The benefit of this approach is that it frees up time for PMs to hone their craft and judgment, rather than burn out from being caught up in simpler decision volume.

“There are tons of human skills that a great PM needs to develop that are even more important in the new era. Things like building deeper empathy with users, knowing which signals to trust, getting deeper in the commercial viability of their product, and designing a system that uses all of that to make as many good product decisions as possible.”

The teams that get this right won’t simply move faster. They’ll make better decisions about where to go next. Start by turning the product knowledge scattered across your organization into shared, usable context. From there, experiment with a Product Brain that gives PMs more space to exercise the judgment, empathy, and creativity that make great product work possible.