AI has made building faster and cheaper than ever. That leaves product leaders with an uncomfortable question: if engineering isn’t the bottleneck anymore, what is? And do we still need product managers?
Today’s guest has a clear answer. Naomi Lariviere is Chief Product Officer at ADP, where she oversees a roughly $4 billion mid-market portfolio for a company that pays one in six Americans. Her career path is unusual for a CPO: she started as a business systems analyst in financial services, then stepped away from product to run an IT PMO, professional services, and even pricing and sales ops before coming back.
Her take: much of the PM job over the past decade drifted toward tickets and standups instead of customers and markets. AI is finally a chance to hand that work off and get back to the real job.
In this episode, Naomi shares:
What happened when ADP’s dev team tried to deliver without a product team, and why they came back
How ADP studied what its PMs actually do all day to find the busywork AI can take off their plates
Why she’s skeptical of the push to turn every PM into a product builder who ships code
How ADP keeps innovating when a single mistake could mean thousands of people don’t get paid
1. The experiment: Shipping without product
At ADP, the question of whether product was still necessary didn’t stay theoretical. When the idea came up that product could be eliminated, Naomi handed the dev team the challenge and told them to figure out how to deliver something on their own.
It didn’t take long for the gaps to show.
“Ultimately we ended up, ‘Oh, wait. We need the product person to tell us, like, well, what are the rules? What is the compliance regulation?’”
Naomi’s explains why this happened:
“AI makes building cheaper, but it doesn’t make choosing things any easier.”
Product takeaway: Speed without direction isn’t progress. As AI compresses build time, the scarce resource becomes knowing which problem to solve, under which constraints, for which customer. If your org is debating whether product is still needed, the fastest way to answer is to look at what breaks when nobody owns the rules, the regulations, and the “why.”
2. How PMs got “Scrumful, not Agile”
Early in her career, Naomi spent her time with clients and prospects, doing market research and studying the competitive landscape. Then Agile arrived, and the expectations quietly shifted. PMs were now expected to write every requirement, run the backlog, and direct each sprint.
The cost of that shift was everything PMs stopped doing:
Talking to clients
Understanding the market
Reading the macroeconomic picture
And that’s exactly why AI looks like a threat to some. If the job is writing PRDs and user stories, AI can do it.
But that was never the actual job:
“What product actually is doing is synthesizing multiple inputs and then going, ‘Here’s the best opportunities that we have to solve a problem, and here’s the ones that are gonna make you money.’”
Product takeaway: If your team’s value is measured by how well it runs ceremonies, it’s vulnerable. Look honestly at where your PMs’ hours go. Process should exist to drive decisions, and every recurring meeting should earn its place by unlocking one. Three standups across three teams is busywork, not product management.
3. Innovating when a mistake means someone doesn’t get paid
Startups can push code multiple times a day. ADP, with over 1.1 million clients, operates with much higher risk. They pay 1 in 6 Americans, and as Naomi says:
“When you think about somebody’s pay, they could be counting on that check to make their rent or, you know, pay for a vacation, or they’re getting married and they need to put a deposit on an event space. You know, if we do something that means they miss that, that is, that’s not okay.”
That doesn’t mean ADP doesn’t move. It means it moves deliberately:
“We innovate actually all the time, but we do it very thoughtfully and in a very controlled fashion.”
Product takeaway: “Move fast” isn’t a universal virtue. The right release cadence depends on the cost of being wrong for your users. In high-stakes domains like payroll, finance, and healthcare, the product team’s job includes keeping the user’s real-world consequences at the center of every innovation decision, and building the controls that let you ship confidently.
4. Product managers, not product builders
There’s a growing push to turn every PM into a builder who ships code with AI. Naomi thinks that misreads what the role is for.
“Yes, I do know how to code, but do you trust me at launching feature and functionality into a platform like one of ADP’s? Probably you shouldn’t do that.”
The skills that actually make a PM effective are the ones that coding doesn’t touch. Interviewing a client without introducing your own bias. Understanding what pushes someone to buy. And above all, telling the story:
“When someone asks me what would be the one surprising thing about my job that most people don’t understand, it’s the storytelling, it’s the influencing that we do. And, you know, coding doesn’t help me do that.”
Naomi does expect roles to become more fluid, but she wants developers doing what they’re great at and product people doing what they’re great at.
Product takeaway: Before requiring that every PM become a builder, ask what you’d lose. The PMs everyone in an org seeks out, from sales to engineering to execs, are rarely the best coders. They’re the ones who read the room, carry empathy for the user, and articulate why something matters. Protect and invest in those skills; they’re becoming the core of the job.
Chapters
00:00 Introduction
02:24 Naomi's path from business analyst to ADP product leader
04:19 Is AI the end of product management?
06:12 AI makes building cheaper, not choosing easier
08:22 How product teams became "Scrumful, not Agile"
12:58 Why ADP has to innovate carefully at its scale
15:32 Process with a purpose vs. process for its own sake
17:30 Should product managers become product builders?
20:22 ADP's jobs-to-be-done study of the PM role
22:13 Fluid roles and why less technical PMs can deliver more
25:43 Storytelling, empathy, and the human skills AI can't replace
28:23 Conclusion
Links
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