The product velocity trap: Why feature factory product management gets zero user adoption

There’s nothing wrong with shipping features quickly. The real problem starts when you’re shipping too many features that no one asked for. “What’s better? A hundred story points in the wrong direction, or one story point in the right direction?” That’s how Kurt Bittner, an author of numerous publications on agile software development, framed how product teams can get caught up in a velocity trap rather than focusing on the customer value. They may appear agile on paper but operate like a feature factory, rushing through backlogs without validating user value.

The State of Agile report shows that 36% of teams define success based on velocity, or the amount of work delivered. In contrast, only 29% of teams collect end-user feedback through surveys to understand whether their work meets user needs. Product teams realize that measuring customer experience is important, but in practice, they still focus on their speed. But the hard truth is that excessive focus on quick feature delivery over devoting time to deep-dive user research costs companies millions in wasted development resources and lost user adoption.

Based on our work with product teams across industries, Xenoss engineers have identified critical patterns that separate velocity-trapped teams from those that ship fast and maintain user adoption. In this analysis, we’ll share:

• The reasons behind the velocity trap and how it can lead to a destructive obsession
• The main drivers of velocity obsession and its costs from technical, operational, and business perspectives
• How businesses can escape the velocity trap, featuring expert advice and real-life examples from world-renowned companies

How the product velocity trap works and the reasons it happens

With agile frameworks and productivity as the core values in the corporate world, the velocity trap may not be obvious. But discovering what keeps it running can help you to tackle the issue at the root.

The pressure to ship: Stakeholder-driven roadmaps

According to the State of Product Management report, 36% of product teams rely on senior leadership to make product strategy decisions. On paper, this looks like alignment. In practice, it often leads to roadmap bloat.

That might sound reasonable, it’s their company, after all. But what happens when strategy is driven solely from the top? 

Stakeholders care about tangible and measurable business value the most, such as the deal volume and revenue uplift. From their point of view, adding more features means more customers, which means more revenue. But that’s where the velocity trap starts. In the chase of quick wins, they push more features into the roadmap, and if those features underperform, their response is even more features. It’s a loop with no learning.

One former product manager said she quit after spending nearly half her time forecasting revenue from features that didn’t match real-world outcomes. Every quarter, the gap between projections and reality widened, making the work feel pointless. Nothing was tied to actual user behavior.

When strategy is grounded in stakeholders’ expectations, companies end up chasing numbers instead of building products people care about. Realizing that user value and revenue are tightly interconnected is the first step to building a product strategy that can make a difference. 

Speed over validation: Why teams perform limited user research

Shipping unvalidated features is one of the fastest ways to waste engineering effort. While comprehensive user research could prevent this, many teams avoid it, not because they don’t care about user input, but because they feel they can’t afford the time. Agile timelines, pressure to deliver visible progress, and unclear ROI from research all push PMs to default to minimal, fast-touch methods like a quick call, an in-app survey, or just gut instinct. 

Stephanie Leue, former CPO at Doodle, introduced continuous discovery to shift her team away from relying solely on customer interviews.

For us, continuous discovery does not only mean talking to customers every week, but it also means we can validate all of our assumptions through various tools. It can be prototyping, fake door tests, or internal interviews. It can be anything.

This kind of multi-layered validation builds confidence across the team. It encourages experimentation, discussion, and course correction. By contrast, a “roadmap-to-production” mindset locks decisions early, discouraging dissent and limiting collaboration.

So what’s your priority? Shipping to satisfy internal timelines and stakeholders or building something users value? When you focus on user impact, you often end up pleasing everyone: your team, stakeholders, and customers.

The “more features = better product” fallacy

Cramming every possible feature into a product can drain your budget while bringing little to no value to end-users. Kevin Henkison, former Founder and Co-Founder of Dust Labs, managed to nip “the more the better” fallacy in the bud before scoring a $200 million product acquisition. He came up with the following remedies:

• Measure atomic user actions (e.g., number of taps or clicks) to expose hidden friction in the user experience.
• Say “no” to feature requests that only add to the product’s complexity. In Kevin’s case, high-demand features like Tasks or Notes were rejected to maintain simplicity and focus.
• Double down on the small set of actions that deliver most of the value.
• Embrace that your product can do less than competitors but better.

Start from the place, “What is the promise our product is making to people?” and build your product strategy around the answer, focusing not on delivering as many features as possible, but on strengthening the promise with every launch.

Drivers of feature velocity obsession in product development

Several forces push product teams toward a “ship it now” mentality. Business goals, modern frameworks, and automation tools all play a part in reinforcing speed as the main KPI, often at the cost of user impact. Here’s what fuels the velocity of product development:

• The Scrum project management framework spurred incremental, quick delivery in sprints with a focus on how much is done, leading to a mistaken belief that the faster, the better.
• Tightening competition and the fear of missing out (FOMO) effect force sales-led companies to keep up with competitors, even if they risk falling into the product parity trap and discouraging user adoption.
• DevOps practices and automated CI/CD pipelines enable faster code delivery to production, which makes it easier to close sprints.
• AI coding tools like GitHub Copilot and Cody accelerate coding tasks, but also lower the barrier to releasing features without validation or review.

Obsessing over velocity metric leads to operating as a feature factory, which in turn leads to product parity, causing customers to stop using products that don’t make a difference. It’s like running an assembly line focused on producing parts as fast as possible. But unlike manufacturing, where every part is essential to the final product, in software, every feature should deliver unique value. Otherwise, you’re just adding noise at speed.

Why “ship fast, iterate later” is a definite way to user and team churn

Speed-driven development has a cost. Prioritizing feature delivery over real user value leads to confusing interfaces. Skipping technical clean-up creates mounting debt. Let’s go through these speed-induced consequences in more detail and discuss possible solutions.

User experience complexity affecting satisfaction rates

Your users don’t love your product because of the ever-growing list of quarterly feature releases. They love it because it makes their work a little easier. They want to get a summary of a sales call so that they can focus on the next one or generate a report with a single click, so they don’t end their quarter drowning in manual work. By shipping too many features, you risk overcomplicating the user experience and discouraging users from adopting and using your product. That’s why you can’t forget the golden rule: Behind every “job-to-be-done” in your backlog is a real person trying to get through a stressful day. 

It’s easy to stray off the right path when you’re building at speed. This is why customer experience metrics such as:

• Customer satisfaction score (CSAT) to measure overall satisfaction
• Net promoter score (NPS) to gauge loyalty
• Customer effort score (CES) to track usability friction

should be your beacons when making decisions about which features to add, update, or retire.

How endless backlogs destroy team morale

Feature bloat and a lack of shared vision behind continuous shipping are affecting your team, too. Have a look at this desperate take on Jira from an employee:

 Jira is an awful product. It’s got tons of feature bloat, it’s slow as hell, and it only serves to ‘increase transparency’ (enable micromanagement) by PMs so they can justify their existence. Whenever it is clearly causing overhead and confusion, it’s always the dev’s fault, as if we can be blamed for years of failure to properly implement this boomer technology. It single-handedly makes me want to quit. 

With velocity as the core metric, your team might feel like they’re working without a clear purpose. You need to ship features as quickly as possible, and the only why behind this rush is the roadmap that was created months ago and might have lost its value already, but no one dares to check.

John Cutler, product manager and the creator of the viral concept of the “feature factory,” said: 

I think the company is the product… Everyone—implementation teams, customer success, HR—is part of what you’re [users] buying into.

If the people building your product don’t believe in it, why should anyone else? 

Before you worry about shipping faster or adding more features, make sure your team understands what problem they’re solving and why it matters. That’s what gives the work meaning. That’s what turns a backlog into something more than a to-do list.

How technical debt slows product development

When your goal is to deliver a bunch of features fast, you’ll inevitably deprioritize those technical issues that your engineering team has flagged repeatedly: slow queries, brittle integrations, outdated dependencies. And the longer you postpone prioritizing them, the more in debt your team will be and the longer it’ll take to ship new features in the future.

You might squeeze in 10 more features, but at what cost? Each addition could mean relying on suboptimal architecture or outdated libraries that won’t scale with your growing product. As the stack expands, so do the trade-offs. How much time, money, and effort will it take to maintain a system built for speed, not stability?

A healthy product backlog reserves at least 10–20% of sprint capacity for addressing technical debt. If you’ve been neglecting it for a while, that share may need to rise to 40–50% just to catch up. The sooner you budget for it, the less painful the recovery.

Stakeholders don’t always see the cost of technical debt until it shows up as outages, delayed time-to-market, or expensive rework. Make those risks visible. Translate neglected tech work into business impact: launch delays, support tickets, and missed targets. Fixing the foundation isn’t glamorous, but it protects everything built on top of it.

Escaping the velocity trap: How to slow down to scale smarter

If you’ve realized your team is caught in the velocity trap, here are a few ways to step back, regain control, and create space for more sustainable growth. Explore three tips provided by our experts that have proven their effectiveness throughout numerous projects Xenoss has worked on:

Tip #1: The feature validation framework that works at speed

Composing a feature validation framework from the tools that correspond to your product mission can help you develop a clear-cut product strategy that operates at speed, but in the direction of user value. Here is what building a feature validation framework might involve:

• Align feature ideas with product strategy. You can use the Lean Value Tree tool to develop a company vision (with a north star metric) as the core driver of product goal-setting and feature development. Another tool could be Reverse impact mapping, which starts from a desired business impact and works backward to identify only the features that contribute to it.
• Test early interest fast. Use in-app surveys to ask users about needs in context. With user interviews, you can discover their deep motivations and emotional drivers. And fake door experiments test real demand track user engagement by showing a feature that doesn’t exist yet (e.g., a button or banner).
• Prototype. Figma lets you build clickable design mockups to test flows and UI quickly. And tools like Maze layer analytics on top of those prototypes to measure user behavior and friction.

Mix and match the tools to cultivate the culture of continuous discovery and ensure a dynamic product market fit that constantly adapts to user needs and market demands.  

Tip #2: Building measurement systems that catch feature adoption failures fast

When you measure user adoption in real time, you get first-hand insight into feature value and can act accordingly: update the feature, delete it, or keep it. This way, each action becomes informed, which makes it harder to ship at speed without pausing to validate first. Below are architectural and analytics solutions that help measure the feature adoption metrics post-release:

• Event-driven architecture. Track user interactions (clicks, checkouts, payments) as discrete events in real time. Analyze workflows using timestamp data to identify adoption bottlenecks or drop-offs immediately after release..
• In-app behavioral analytics. Use tools like Amplitude, Heap, or PostHog to track DAU, MAU, feature-level retention, and usage by cohort. These dashboards reveal how users navigate new features and which actions signal adoption.
• Advanced data analytics. Use Power BI or Tableau to correlate adoption trends with business metrics like LTV, ARR, or user conversion. This view helps teams connect feature performance to commercial outcomes.
• Tag-based feedback. Use automation bots to deliver real-time usage summaries to Slack or email. Tag key product areas and monitor engagement trends, drop-offs, or sudden spikes as they happen.

But measurement alone isn’t enough. It’s reactive. If you skip validation and jump straight to data collection, you risk learning the wrong lessons from flawed features. The process should start with a validation framework, followed by development, and then measurement. Without that foundation, your metrics might reflect effort, not value.

Tip #3: Leading stakeholders away from the velocity trap

Feature validation can feel like a slowdown to business stakeholders. The key is to reframe it as risk reduction and long-term ROI. Here’s how to shift the conversation and get buy-in for smarter product decisions:

Step 1. Provide them with real-world numbers. You can collect data on user churn after release and translate it to potential revenue loss to show the consequences of rushing to ship features. Then contrast those numbers with validated features that drive retention, engagement, or revenue.

Step 2. Compromise. If speed is still a non-negotiable, suggest running experiments (e.g., simulated beta tests) in parallel with the feature development process. Experiments don’t require significant investments and can provide fast, measurable results to optimize the product roadmap. 

Step 3. Measure on business terms. When defining the value of experiments, focus on business-oriented product metrics, such as the average revenue per customer, customer lifetime value (LTV), and the cost to acquire a new customer (CAC). This way, you’ll help stakeholders understand the value of feature validation and get them on board quicker. 

When you translate validation into business impact, stakeholders start to see it not as a delay but as a strategic advantage. You can move fast, reduce risk, and still hit your revenue targets by making smarter product decisions upfront.

Learning from the best: Companies that didn’t fall into the feature velocity trap

As examples of successful “velocity trap avoiders”, we’ve chosen Slack and Linear, as they scaled from startups into enterprise-level products and have managed to retain customer loyalty along the way. Learn how they coped with the pressure and didn’t break their promise to users.

How Slack wins user hearts by preserving simplicity with scale

From the beginning, Slack aimed to build a work tool people loved using, just as much as the apps they use outside of work. That mission meant avoiding the classic velocity trap: overstuffed feature sets designed to please every stakeholder, but no one who uses the product.

Instead of racing to check off roadmap items, Slack grounded their product decisions in qualitative feedback. They interviewed users, ran internal and external tests, and prioritized how features felt in use, not only how they performed on a dashboard. 

Noah Weiss, former CPO at Slack, puts it this way: 

We’re data-informed but not data-driven… It’s important to remember why people are paying us. They’re not paying us to spend more time in Slack—they’re paying us to be more productive. So that means most of the traditional in-product metrics you can directly measure are far removed from our mission.

This mindset helped Slack avoid the false signals of vanity metrics. Instead of tracking message volume, channel creation, and time spent in the app, Slack measures the product’s success with the metrics that directly reflect their mission. And one of their north stars is NPS, which indicates that people love using the product and recommend it to others.

Slack also stays intentional about who they are building for. They recognized the tension between SMBs who wanted innovation and enterprise clients who valued simplicity and customization. But instead of over-rotating toward a high-paying enterprise segment, they kept their balance by remaining loyal to SMBs at the core while solving pressing enterprise challenges.

Even their leadership style reflects this balance. Slack CEO, Stewart Butterfield, is collaborating with the team at the product origination stage to co-create the vision, less during prototyping, and then again more at the end to help validate the final idea or “taste the soup” as they call it at Slack. Such a U-shaped stakeholder involvement (as illustrated in the image below) created space for experimentation without losing alignment.

And while Slack is well aware of the competition, they never let competitors dictate their pace. “We’re competitor-aware but customer-obsessed,” Noah said. That’s how they keep focus on whether the features they ship bring value to real people.

How Linear keeps product velocity focused by saying no

The Linear team approaches product growth by defining which features they can debate and to which they have to say a definite “no”. In particular, they often refuse HiPPOs (highest-paid person’s opinion) in their customization requests, even though they promise profit. But the team knows that such changes can overcomplicate the overall user experience. Striking a balance between serving customers’ every need for the sake of revenue and the core value of the product is what differentiates Linear from other project management solutions.

This level of discipline starts with genuine empathy. Nan Zhang, Head of Product at Linear, says that: “My goal is to feel bad in the same way customers feel bad.” During interviews, they dig beneath operational complaints to uncover what’s bothering users. Instead of rushing to add shiny features, the team ties product decisions to the emotional weight behind users’ problems. 

However, speed is still crucial for Linear, but not in a closing-sprint-after-sprint way. They aim to deliver the first version of the feature to the users as fast as possible to validate its value with beta testing. The first version doesn’t need to be pixel-perfect, just functional enough to validate whether it solves a real problem. 

Linear’s approach to speed also sets a high bar for competence. Their product team can evaluate the feature’s value when it’s only 10% ready, rather than waiting until it’s 80% complete, to save resources and redirect efforts to what truly matters.

By blending competence, proactivity, and speed, Linear keeps their roadmap clean, user experience focused, and teams out of the velocity trap. Saying no is what makes room for building the right yes. 

Final thoughts on the development velocity trap

Product managers are juggling multiple responsibilities at once. And sustaining expected feature delivery is one of them. But there are solutions that can help your team to break free from a velocity trap without hurting either users or stakeholders. 

Combining a team-specific feature validation framework, stakeholder collaboration, and data analytics can help you cease running in sprint velocity circles without producing measurable customer value. Xenoss is there for you to select, validate, and implement the right technology to build a solid foundation for a stable and customer-centric feature pipeline.