Building for the Right Users: Lessons from Meta, Reddit & Credit Karma
This is an excerpt from our virtual event on March 5, 2026 featuring Andreas Gross, GenAI Product Leader at Meta, former product leader at Reddit, Credit Karma, and Life360.
What separates great product leaders from good ones? It often comes down to one deceptively simple question: are you building for the right users? In a wide-ranging conversation with Enrich members, Andreas walked through real-world case studies, tactical frameworks, and his perspective on where AI is taking the craft of product management.
Here are some of the key takeaways:
Most Teams Are Focused on the Wrong Users
Andreas opened with a counterintuitive provocation: product teams at most companies are optimizing for the wrong audience - their most vocal existing users. For companies outside the top ten in any category, the pool of potential new users dwarfs the pool of current ones.
"Existing users are vocal and have strong opinions, but they represent only a small portion of potential users and have pre-conceived notions about how things should work," Andreas explained.
The implication is significant. When you listen primarily to power users, you risk building features that make your product incrementally better for a small group while remaining inaccessible, or possibly irrelevant, to the much larger audience you haven't yet reached.
The Reddit Redesign: A Case Study in Earning the Right to Change
When Andreas joined Reddit, the team believed they had 100,000 active communities and 300 million monthly users. But when they raised the bar for what "active" really meant, a different picture emerged.
Reddit was succeeding in specific content categories, and most of its millions of visitors were arriving via Google, getting their answer, and leaving. They were never becoming true Reddit users. Tasked with redesigning a product beloved by hardcore users, Andreas (himself not a Reddit user) had to earn credibility before he could drive change.
Andreas outlined his approach:
Spend two months on deep research into successful vs unsuccessful user journeys.
Introduce A/B testing culture despite pushback from those who felt it was wrong to "test on community members."
Prioritize moderators early on, recognizing them as Reddit's essential DNA.
Keep old.reddit.com alive for users who didn't want change, offering a gesture of respect to the core community.
Post transparently about the redesign (even when those posts received zero upvotes).
That last move, adopting radical transparency, turned out to be a way of finding the internal allies who wanted change. The redesign's success was measured not just by consumer metrics but by a specific milestone: getting 50% of communities to adopt the new design.
A significant technical obstacle loomed beneath all of this work. Reddit's old codebase made building painful. A full site rewrite was necessary to unlock the velocity needed to execute the vision. But the pain would be worth the gain, as Andreas and the team had quantified the benefit through a careful process of experimentation.
Credit Karma: Empathy as a Growth Strategy
At Credit Karma, the challenge was internal before it was external. Employees, many in well-paid jobs in the Bay Area, didn't live the realities of the struggling Americans who made up the core user base. Founder Ken Lin addressed this directly, running exercises designed to help the team viscerally understand what financial stress actually feels like.
The result of that empathy translated into product decisions that seem small but proved to be anything but. The credit score dial originally displayed low scores in red, accompanied by language like "this needs work," adding psychological weight to an experience users were already finding stressful. Changing to more positive, action-oriented colors and copy drove a 2% engagement lift, one of the best gains the team achieved.
As Credit Karma neared saturation with 100 million Americans using its core product, growth required introducing new financial products like mortgages and personal loans to users who were often financially undereducated. The challenge became educating users why switching products could benefit them financially.
The Three Stages of Company Growth, and the Skills Each Demands
Andreas categorized his career across three distinct company stages, each with its own demands on a product leader:
Founding stage, or the "drunk walk." You’re moving in many directions, learning new skills, and it’s hard to build quickly. Although AI is making this stage easier for founders today.
Scaling stage (roughly the 100-person company): The most rewarding stage, in Andreas's view. You have autonomy, hard problems, some resources, and product-market fit. But, you're largely figuring it out yourself, constantly learning in areas where you're not fully qualified.
Large company (i.e., Meta): Highly specialized. Andreas estimates he used only 30% of his skillset at Meta, but applied that 30% to enormous scale. Meta excels at identifying what individuals do best and maximizing it.
His preference is the middle stage, precisely because of the discomfort. The breadth of challenges make it the richest environment for growth.
How AI Is Reshaping the Product Manager Role
Andreas outlined his views on how specific roles will evolve:
Product managers will focus more on bigger bets, business use cases, and judgment calls that AI can't yet make objectively. PMs need to become more like business operators with a clear grasp of financial impact.
Engineers will do more optimization work, running daily landing page variant tests, for example, based on AI-generated hypotheses.
AI is trained on internet data that contains both good and bad product thinking. It hasn't figured out how to reliably make strong business decisions yet.
On AI's impact, Andreas is both optimistic and cautious. The removal of constraints that AI enables is genuinely exciting, but also dangerous.
"The constraint removal that AI brings is both exciting and scary,” he explained. “Most companies succeed by picking an area to focus on, but with AI you can do so much so fast that you risk trying to do too much and building for no one."
User Research: What It's Good For and Where It Falls Short
Andreas is a believer in research for optimization decisions, but more skeptical of relying on it for bigger bets. His reasoning is that users describe how they currently use products, not how they would use products that don't yet exist.
He shared a real-life example. At Life360, users said they wanted neighbors to have temporary access to their children's location data. Rather than investing six months building that feature, the team repurposed an existing "Circles" feature to run a quick validation. Almost no one used it because users found it awkward to ask neighbors, and often didn't even have their contact information handy.
His preferred approach for generating insights on bigger bets is concept testing. Present 20 potential features and asking users to rank them rather than presenting open-ended requests for wishlist items.
For raw discovery, he and his team at Reddit would go to Union Square weekly to talk to strangers about the product. A consistent finding was that Reddit conversations are invaluable to experienced users who understand the ecosystem. However, new users have no reason to trust the advice from a random Reddit commenter when making a purchase decision.
Leading Teams: The Honest Skills Conversation
For assessing and developing PM talent, Andreas uses a 12-skill framework that includes six hard skills and six soft skills. He asks team members to rank themselves, with the requirement that they must assign some "ones." No one can claim to be good at everything.
This creates the conditions for an honest conversation about where someone genuinely spikes and where they want to grow. At companies like Reddit and Credit Karma, where retaining talent against the pull of larger companies is an ongoing challenge, leaders need to actively encourage people to stretch into new areas, not just play to existing strengths.
One management principle he brought up from Meta is that everyone, including engineers, manages to a business objective. As AI gives individuals more autonomy, this business-mindedness will become an increasingly critical baseline skill.
Key Takeaways
Ask who you're really building for. Existing users are vocal but often unrepresentative of your true growth opportunity.
Credibility precedes change. When you're new or an outsider, lead with research and data, not personal opinions.
Empathy isn't soft, it's a product strategy. Understanding your users' real lives leads directly to better product decisions.
Measure what matters. Loose definitions of success (like "active communities") can mask the reality of where you're actually winning or losing.
Use research for optimization; use judgment for big bets. Don't ask users to design the future for you.
AI expands what's possible, which means you need more discipline, not less, about what to focus on.
The middle stage of company growth is the best classroom. Embrace the discomfort of being under-qualified.
