What product leaders need to understand about AI, velocity, and the trap of shipping fast in the wrong direction.
For the better part of a decade, Martyn Bassett has watched early-stage software companies use speed as their primary competitive weapon. Move faster than the incumbent. Ship more than the competitor. Outpace everyone else to the next feature. It worked, and for a long time, it worked well.
The picture looks different now.
Martyn recently sat down with Daniel Shapiro, former CPO at Workleap and PartnerStack, with over 20 years of building product orgs across B2B SaaS, FinTech, HR tech, and now AI applied to healthcare and pharma, for a conversation framed around a simple tension: velocity versus value. What emerged from that discussion was something more specific and more actionable than a debate about pace.
The core finding was this: velocity as a competitive differentiator is being commoditized. Product leaders who haven’t internalized that yet are building on a foundation that’s quietly shifting beneath them.
When Speed Was a Moat
There was a real logic to the speed-first mentality. If a team could ship faster than anyone else, it could build differentiation before competitors caught up. Learn faster, iterate faster, accumulate product decisions faster. Speed compounded.
For founders and product leaders at early-stage companies, this was the playbook. It still gets taught. It still gets funded.
What AI has done is hand that playbook to everyone simultaneously.
The tools that allow a well-resourced product team to prototype, iterate, and ship at pace are now accessible to every team. The ceiling on raw velocity has moved up dramatically, but it has moved up for competitors at exactly the same rate. The advantage that once came from simply moving faster no longer exists in the way it once did.
Daniel put it plainly: “The ability to differentiate on speed is becoming a bit commoditized. What product leaders need to understand is they need to have an even deeper understanding of what value is to their customers.”
That is the shift. And it has significant implications for how product teams are structured, how they are measured, and how they are led.
The Feature Factory Problem, Accelerated
The feature factory problem is not new. Product orgs that optimize for output features shipped, velocity metrics, and release cadence at the expense of outcome have been a known failure mode for years. What AI has done is dramatically accelerate the rate at which a team can fall into that trap.
A team that can now prototype and ship at a pace that would have been impossible two years ago, but hasn’t changed what it measures or how it makes decisions, is not building faster. It is making mistakes faster.
The diagnostic question Daniel offered was direct: “Are we measuring customer value as our success endpoint, or are we just celebrating speed?”
That distinction between celebrating what goes out the door and measuring what it does once it is out is where most high-velocity orgs that are not delivering will find their answer. The feedback loop is rarely broken at the shipping stage. It breaks at the measurement stage, and it is usually reinforced by culture. When teams celebrate releases rather than retention, growth, or genuine customer impact, the velocity number becomes the thing that gets optimized. Everything else becomes secondary.
The fix is not slowing down. The fix is changing what gets tracked and what gets applauded.
Direction Matters More Than Speed
Daniel introduced a concept that reframes the entire velocity conversation: the vector of speed. The direction a team is moving matters more than how fast it is moving.
Shipping twenty features in a week is not inherently good or bad. What matters is whether those twenty features are advancing a clearly defined product strategy, or whether they are just shipping. When the strategy is clear, customer conversations reinforce and deepen the understanding of where the product is going. Discovery and delivery pull in the same direction. Velocity compounds into something meaningful.
When the strategy is not clear or when it has been generated from a prompt rather than built from genuine choices about customers, market position, and tradeoffs, fast shipping is just faster drift.
This is a pattern Martyn sees repeatedly in early-stage companies right now. AI tools have made it genuinely easy to produce a product strategy that looks and feels right. It has the right sections, the right language, the right frameworks. But it is built on how a language model predicts customers will behave, not on the actual, uncomfortable, time-consuming work of talking to real customers and making real choices. Daniel was direct about what he had seen in those cases: “You end up with strategies that are not as differentiated as you might think they are.”
That is a quiet catastrophe. A team can be moving fast, shipping constantly, and feel like things are working right up until the retention numbers tell them otherwise.
What the Warning Signs Look Like
For anyone running a product org or evaluating one, Daniel flagged four signals worth watching closely.
The team is pointing to synthetic data instead of real conversations. There is a meaningful difference between primary research, direct customer interaction, things heard and observed firsthand and secondary data, however well-synthesized. AI can do extraordinary things with the latter. It cannot replace the former. If a team’s discovery rationale is primarily pointing to AI-generated summaries, research reports, or synthetic personas rather than actual customer conversations, something is off. The question worth asking: when did someone on this team last sit beside a customer and watch them use the product?
Speed is what gets measured and celebrated. Pay attention to what success looks like internally. What does a good sprint look like? What gets recognized in a team meeting?
When the answer is consistently about release frequency rather than customer impact, the culture is optimizing for the wrong thing, and culture is hard to change after it has been set.
The product strategy was generated, not decided. Strategy, at its core, is a set of choices made with imperfect information. It requires someone to commit to a direction, own the tradeoffs, and see them through. That is a human function. When strategy is primarily a prompt output, what gets lost is choosing the actual decisions about where to play and where not to. Teams can end up with strategies that look comprehensive but have never been stress-tested against the real constraints of their market or their customers.
The velocity is real, but the value metrics are not moving. Retention flat. Expansion revenue slow. NPS plateaued. When a product team is shipping constantly, but the indicators of genuine customer value are not moving, the feedback loop between what is being built and what customers actually need is broken somewhere. Finding it usually starts with asking how value is being defined and measured, and whether customers would use those same words.
What This Means for Product Leadership
None of this is an argument against moving fast. Speed still matters. The ability to prototype quickly, get in front of customers, and iterate is genuinely valuable, more so now than it has ever been.
What it is an argument for is intentionality. Product leaders who will thrive in the current environment are the ones who can hold two things at once: the operational ability to move quickly, and the strategic discipline to make sure that speed is pointed at something that actually matters.
That combination is harder to hire for than it sounds. It requires people who are technically fluent enough to understand what they are building and how it ships, strategic enough to make real choices and defend them, and grounded enough in customer reality that they are not substituting synthetic signals for genuine understanding.
Across two decades of recruiting product leadership for early-stage and scale-up software companies, the team at Martyn Bassett Associates sees that profile in higher demand right now than at any point in recent memory. The gap between what companies are asking for in a job description and what they actually need from a hire has rarely been wider.
If you are building a product org and want to think through whether you have the right leaders in place for what the next two years actually require, that is exactly the kind of conversation Martyn Bassett Associates is built for. Book a 15-min meeting with Martyn here.
This piece draws on a recent conversation between Martyn Bassett, founder of Martyn Bassett Associates and The Product Recruiter, and Daniel Shapiro, former CPO at Workleap and PartnerStack. Martyn Bassett Associates is a North American executive search firm specializing in product, sales, and marketing leadership for venture-backed B2B SaaS companies.