The former growth leader at Dropbox, Miro, and Amplitude on using AI to automate the basics — so humans can focus on the creative work that actually matters.
When Elena Verna joined Lovable, an AI-native startup, she wasn’t chasing another growth role.
“I actually wanted to retire before I hit Lovable,” she admits. After leading growth at Dropbox, SurveyMonkey, Miro, and Amplitude, she’d seen the same patterns play out again and again. “I couldn’t do another gig where I felt like I’m doing growth 101. Onboarding flows, lifecycle emails, A/B tests. They all felt the same.”
But the speed at which AI-native tools are changing how teams build pulled her back in. “I wanted to automate myself out of the job,” she says. “All of these baseline optimizations should be codified into products themselves so growth leaders can actually focus on creativity and innovation again.”
That’s Elena’s operating principle: Use AI to automate the basics so humans can elevate the creative.
AI isn’t 100%. It’s ‘average intelligence’ that can take you 40 or 50 percent of the way. The real lift still comes from human judgment layered on top.”
Elena Verna, Head of Growth, Lovable
Listen to the full episode of Product in Practice with Elena Verna to hear her workflow demo and deeper reflections on how AI is changing the way we build products.
Automate the 101
For Elena, AI’s real value is simple: Do the busywork so people can focus on the good stuff.
“We all spend too much time doing the same baseline optimizations,” she says. “AI should free us from that. What can you automate that you as a human don’t add value to?”
She argues that the foundational “growth 101” work — A/B tests, lifecycle emails, onboarding flows — should be baked directly into products. “No company should need to hire a growth leader just to get the fundamentals right,” she says. “Growth should be about creativity and innovation, not doing the same things over and over.”
Solve the empty-state problem
Everyone knows the paralysis of a blank page. For Elena, this is exactly where AI shines.
“Humans struggle with the empty-state problem,” she says. “We have an empty Google Doc, and our brain freezes. Now we don’t have that anymore. We can go to AI, have it give us the first 40%, and then apply our authentic expertise to finish the last 60%.”
At Lovable, that mindset shows up in daily workflows: product specs, prototypes, and go-to-market plans start with an AI draft that sparks iteration. “I’m not looking for a final output,” she says. “I’m looking for an initial reaction. It’s faster to fix and improve than to start from scratch.”
Hire AI-native talent
If you want to change how your team builds, start with who you hire.
“I highly encourage hiring an AI-native employee,” says Elena. “They’re most likely coming from smaller companies or they’re brand-new grads who didn’t know a pre-AI workflow. They come in and infuse incredible energy into the team (as long as the rest of the team is willing to listen).”
While some fear that AI will make entry-level roles obsolete, she argues the opposite: “New grads are graduating with AI skills and curiosity. They show us the new way of doing things.”
New grads are graduating with AI skills and curiosity. They show us the new way of doing things.”
Elena Verna, Head of Growth, Lovable
Loosen the guardrails
For larger or more established teams, Elena recommends temporarily loosening procurement and compliance guardrails to make space for bottom-up experimentation.
“If you have very tight permissions around what can be used inside the team, you’re preventing innovation from happening from within,” she says. “Yes, you’ll feel pain on budgeting and compliance, but it’s a necessary growing pain. You can tighten up later. For the next six months, let your employees explore.”
That experimentation mindset also applies to the tools themselves. “Don’t assume that if AI performs poorly at a task today, it won’t get better. Things are changing weekly. Keep trying.”
Share what you learn
Elena’s next call to action: Don’t go it alone.
“We don’t need to figure this out all on our own,” she says. “If we do, it’ll just take our industry so much longer. Share your failure points as well as your success points. Ask other people to help you. That’s where human-to-human connection goes really far.”
Cross-company knowledge sharing, she argues, is what will create network effects that move the entire industry faster.
Anchor in what doesn’t change
Even in an AI-driven world, some fundamentals of product management stay the same. “You cannot automate talking to customers,” Elena says. “You still have to get on the call, read what they’re saying, go talk to them.”
The second constant: vision. “If everybody uses AI to build their products, we’ll all converge into building exactly the same thing. AI should not set your destination. You should still define what awesome looks like for your product.”
Finally, she reminds product managers to stay sharp on differentiation and distribution.
“With tools like Lovable, everyone can build a product. You have to understand what’s commoditized and what’s actually your differentiator: the part you need to market, monetize, and protect.”
If everybody uses AI to build their products, we’ll all converge into building exactly the same thing. AI should not set your destination. You should still define what awesome looks like for your product.”
Elena Verna, Head of Growth, Lovable
Keep the human edge
Instead of seeing AI as replacing product managers, Elena sees AI as reshaping jobs.
“The things AI can automate, I don’t want to do anyway,” she says. “Those aren’t the exciting things that I wake up for every day. If AI can take away that foundational stuff off my plate — let’s go.”
Elena’s framework — alongside perspectives from Kene Anoliefo, Laura Burkhauser, Ravi Mehta, and Aakash Gupta — is featured in Atlassian’s new ebook, AI fluency: The new product superpower.