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Human-Centered Product Management in the Age of AI
- JJ Rorie
- 22 hours ago
- 21 min read
Episode 103
Amanda Di Dio, Vice President of Partnerships at Optimistic Design, explores how product teams can thoughtfully navigate AI without losing sight of what matters most: people.
Amanda shares her journey from traditional program and product management into systems thinking and human-centered design—and how that shift changed the way she views responsibility, impact, and decision-making in product work. Together, JJ and Amanda unpack what systems thinking really looks like in practice, how product teams can embed research and co-creation without overhauling their entire process, and why slowing down early often leads to better outcomes later.
The conversation also dives into AI’s growing role in product development and the opportunities and risks that come with moving fast. From responsible design and bias awareness to the danger of jumping to solutions too quickly, this episode offers a grounded, pragmatic take on building products with care in a rapidly evolving landscape.
Finally, Amanda shares advice for aspiring product managers navigating a tough job market, including how to build perspective, develop craft beyond the basics, and stay human in an increasingly automated world.
This episode is a must-listen for product managers, designers, educators, and leaders who want to build meaningful products—without losing their soul in the process.
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SUMMARY
Topics Covered:
What systems thinking and human-centered design actually look like in product teams
Moving from “building for users” to “building with users”
How small process shifts can create big improvements in product discovery
Why research is often undervalued—and how to advocate for it
AI’s impact on product development, especially in education
Responsible AI, bias, transparency, and ethical design considerations
The risk of jumping to solutions too quickly with AI-powered tools
How AI can free up time for strategic thinking, storytelling, and leadership
Advice for aspiring and early-career product managers in today’s market
Key Quotes:
“We should be building with users, not just for them.”
“It doesn’t have to be a massive shift—start in the small moments where you can involve users earlier.”
“Product management is as much about human dynamics as it is about roadmaps and delivery.”
“AI gives us time back. The real question is what we choose to do with that time.”
Takeaways:
Slow down early to move faster later. Spending more time in discovery and problem definition reduces misalignment and tech debt.
Human-centered design doesn’t require a full reset. Even small additions—like earlier interviews or co-creation workshops—can make a big difference.
AI is a force multiplier, not a replacement for judgment. It should support thinking, not shortcut it.
Responsible AI is now part of product leadership. Literacy, transparency, and equity are no longer optional.
The future PM role is deeper, not narrower. AI creates space for stronger storytelling, facilitation, strategy, and influence.
Aspiring PMs should broaden, not panic. Build fundamentals, explore adjacent disciplines, and connect with people doing the work.
TRANSCRIPT
JJ: Hello and welcome to Product Voices. I am so excited about my conversation today, my guest. Is amazing. And I actually have had her on before on a podcast. And we go way back and I'm very excited to have her again. We're gonna be talking about all things, product management, ai, all the fun stuff that we know and love.
And so it's gonna be a really amazing conversation and I'm looking forward to sharing it with you. Amanda Di Dio is [00:01:00] Vice President of Partnerships at Optimistic Design. And a strategic program leader with over a decade of experience advancing digital solutions and services across sectors, she has led complex cross-functional initiatives for our organizations, including the Gates Foundation and Renaissance Learning.
Amanda, thank you so much for being here with me today and having this conversation.
Amanda: Yeah. Thanks JJ. It's pleasure to be back. I'm excited to hop into this topic around product management and delivery. Thoughts about human and equity center design and what that role plays into thinking about the impacts of AI.
JJ: Yeah, it's it's such an interesting time. I think we probably could say this at virtually anytime in product management's history, but I feel particularly energized and excited. And a little unknown about today's product management world. And I think that's exciting.
I think there's a, I think there's room for us to almost build it the way we want it to be. Not just, [00:02:00] what it's always been. So I only gave a very brief bio of you just to introduce you to the audience or the audience to you, but. I often find a person's career and a person's career stops, and the different things that they have experienced over their career in their lives has an impact and a and drives a bit of their point of view or their perspective on product and design and other things.
And and. We know what you do. Now we know a little bit about your history, but tell us more about your career, your path, and maybe a little bit if some particular experiences have driven your overall point of view on product and design.
Amanda: Yeah, I as you mentioned, I started my career in program and product management consulting and primarily supporting clients across sectors, building web-based tools, mobile application, proprietary SaaS platforms, leading cross-functional teams through the traditional frameworks of product R&D.
And I was introduced [00:03:00] to systems thinking and human-centered design. Relatively recently in my career, and I was immediately drawn to, how these frameworks could fundamentally reimagine the traditional product development process. And it challenged me, I think, to think beyond, building for users and instead focusing on building with them and elevating end user voice is essential driver to product delivery.
And I think that, was a mindset Shyft for me and became the core catalyst to co-founding Optimistic Design, which is a design research and strategy practice where we are dedicated to helping organizations and product teams deliver agAInst and understand how they can build their own capacity around understanding systems thinking and human-centered design frameworks and implementing that [00:04:00] into the core of their work.
It is, a slight different. Shyft and how you think about building roadmaps, how you think about prioritizing research and how you think about really understanding, the problem space. And we support our partners in how to intentionally embed co-creation and insights led strategy and that inclusive.
Part of designing a service or a product that really thinks thoughtfully about the users and the ecosystem of the stakeholders that their problem is serving. And I think that is the heart of product development and and yeah and I think it really has changed the way I view my role and the responsibility that I have as a product manager and a leader and a a part of that triad of product and design and development and research.
JJ: Yeah. That's amazing. I love your background and optimistic design and kind of it's coming to [00:05:00] fruition I think is a great story. And I think you're spot on in terms of we should be doing all of this in product development. We should be centering the customer and the user.
But it's hard, and I don't mean it, it's, it's rare, let's be honest, right? We don't, there aren't enough organizations that truly co-create for sure. And, even center the user, we think we do, we're doing some things here and there that, that, that may be beneficial. But we get so internally focused so quickly and so easily it doesn't mean that we do everything wrong, but it's very difficult to.
To have that kind of mindset in an organization. So I'd love to hear a little bit more about specifically like what is systems design? What is human like, how do, how does an organization, and I get, we're taking us back to the basics here, but what does that mean to an organization? So folks out there listening that, that don't really know what that means or don't really embed that yet.
Or at least knowingly embed, embed [00:06:00] that. Tell me more about that. Tell me more about how organizations use that and what that looks like in a product team.
Amanda: Yeah, I think there's small shifts to thinking about the traditional R&D process where you define the problem. And usually that is either a business led problem because there's a gap in the market of your product, or it could be customer feedback that comes in.
And so you define the problem. You might do some research around, what is that problem from the user perspective, you jump into designing. You prototype, you Shyft that into A PRD and you start delivering against development and then you might test again a new release.
And I think, that's worked and it's worked for organizations who are able to move through to be able to deliver something fast. But I think what tends to happen is you start to release features that haven't actually been really thought about where that actual problem sits. And are we just acutely solving a problem or are we actually looking at a root [00:07:00] cause of where that might sit within your product?
And a lot of times what happens is you accrue tech debt and then the, and the product becomes really loaded instead of thoughtfully and taking a little bit more time to really understand, where does this problem sit within the larger ecosystem of our product? And again, are we actually acutely solving the problem?
And I think the small shifts that we usually guide teams who are like, I don't know where to start or how to rethink our process, is to expand that R&D cycle a little bit further. Spend more time in the initial define and discovery by doing some secondary research, actually talking to end users through qualitative interviews and doing some quantitative data collection, synthesizing that and reflecting it back.
Is this right? What we heard correctly from you? Help us prioritize what the most important thing is that doesn't absolve you from thinking about your business stakeholders. What are your business stakeholders priorities amongst what your end users have said and what they [00:08:00] prioritize? And then that's the fun part of the collaboration and making those trade-offs as you start to then move that prioritization or opportunity ideation space with end users.
Continue to involve them in that process. Generative design, conceptual design, and bringing end users into that fold. It doesn't need to be an elaborate process. These are sprint based. Integrate that into your sprint. There's many different tools out there that can help you do that rapidly.
There's also different modalities of research that we've used that are easy and pretty fun to spin off collaborative workshops. We use Miro. We use things like color coding and prioritizing where. Our users are starting to get bought in. They have agency in the process, they become ambassadors and wanna continue to engage.
So you're not defining the problem, developing something, prototyping and then testing it. You're continuing to validate and prioritize along the way so that by the time you [00:09:00] release, you've already done a lot of that work to then set yourself up to continue to test what's next once it's live, once it's matched.
So fundamentally, it's. Finding the moments that are available to you to start earlier on in your process, to engage end users. And they do not need to be massive shifts to your process. It could be the smaller moments where your. Bringing them and spending another week of doing more qualitative interviews, spending another week doing some ideation and testing, start there and then open up your repertoire of modality of testing and think creatively about what that could look like.
And I think bringing a systems thinking lens is really understanding that root cause, right? It's really thinking about, are we. Are we solving an acute problem or are we looking at all of the factors in which could be underlying to where a problem might sit? And it could include the user, or it could [00:10:00] include the ecosystem of what is around that user that could be impacting the way that they're using your product.
And so what I love is walking into a team who's I have no idea what systems thinking is. Walking them through some ways of understanding and doing iceberg analysis or thinking about problem and cause reaction and mappings through some different workshops and exercises. And it soon becomes a realization of, oh wow, we saw we were prioritizing the right problem, and it turns out we were at all.
And so it's an elimination and and it does take time and practice and a little bit of a mindset Shyft in your organization or your team, but I think it can start in the small moments.
JJ: Yeah, that makes a lot of sense. And I think it's important what you mentioned about how it doesn't, it doesn't have to be this entire shift of the process. And it can start in those smaller moments. I love the way you say that because I think people get scared of change and in product [00:11:00] everything's always dynamic. Like we never get there. Whatever, wherever there is we're always learning, we're always changing, we're always doing something our customers needs are always changing and it can get overwhelming. And so just the thought of, even when intrinsically we know it's the right thing for us it can get difficult to change the way we do things. So I think that's really a practical way to think about that. So you can't have any conversation these days without this.
So tell me about AI and what you're hearing from clients and, it, it changes weekly, daily. Like I love keeping up with it, but. What are you hearing in the real world of product teams making products, trying to do things very system thinking, very human centered and allow AI to help them with that.
What trends or conversations are you having and seeing out there?
Amanda: We've been really steeped in the education landscape over the last few years, and we're at a an interesting spot [00:12:00] where our client portfolio sits on two different bookends. We have clients that are social impact funders who are looking to fund momentum and movement into integrating ai, doing more research around AI and supporting their grantees on their path to integrating AI into EdTech products.
We also work with ed tech organizations who are integrating AI into their courseware, their curriculum, into the pedagogical practices to support teachers. So we're seeing this ecosystem of how AI is being viewed, how to research it, how to implement it. And so it's an interesting spot to be in as a a design research consultancy to look at the variety of problems that both of these sorts of players are facing.
And I think when I had a I had a moment. I attended a conference in education, one of the largest education conference in the country called A-C-G-S-B. And what I was struck by was the volume of products [00:13:00] that are all AI driven and the, and how quickly. It was just there and these conversation has to be a couple years ago.
Everybody was and what worried me about that was the speed potential with these, LLM driven models that are not actually built and trained equitably. And I think the speed in that could either close or widen a bias app. And I was a little bit unnerved by that. And two things stuck out to me from leaving there that I thought were like aha mo, not aha moments, but just reinforce the things that we like to reinforce when we're working with those bookends of science.
We have, literacy and responsible use is, it just isn't optional anymore. And I think it's becoming a new pillar of a digital citizenship. And I think as fast as we are integrating and building ai especially, and talk [00:14:00] about the education landscape, but I think across sectors, the conversation about education for how to, the utility of it.
The discernment of using it, and especially with students, families, and caregivers, the way it should be integrated in students' life and the way to teach students now and any young person today around its utility and the end it's harms. I and I worry about the volume of that in the education space and in the course or the curriculum, the inundation of it, just becoming a digital first experience, right?
And then the lack of that education around its utility. And so that, that definitely stuck out to me. And the other is this co-creation and testing of the thoughtful integration and build of AI solutions. So I think the rush. To integrate open source LLMs [00:15:00] without thoughtful design, without the continuous iteration, without the input from diverse perspectives and actually subject mapping matter expertise within the space to correctly train a model can cause misalignment and harm.
And I think there is not a lot of transparency in products. At least that I'm using to know what are lm are you using? I don't think there's a lot of data consent either of am I feeding my information in and is it gonna be part of the training of this model? Is it, I think the co-creation and co-design does not start with just a front end solution. I actually think it is a part of the training of a conversation model and to continue to ensure that we are not missing diverse perspectives as part of that model and subject matter expertise to validate and to effectively ensure that the model is changed correctly.
So I think. Those are the trends I'm seeing in a reaction to the fast [00:16:00] paced environment that we are in right now with everything is AI driven and the sort of impacts that will have if it's not, if we don't slow down a little bit and start to take care of that velocity.
JJ: In some ways it's good to hear that. That it's being embraced and that it's being talked about, or the responsibility is at least being talked about. And I don't think we've gotten it yet. I don't think we have our guardrails yet as businesses and societies, but at least.
Most of us, I think, know that they need to be there. So I think that's a positive. And it's, it's interesting to hear a sector like education, embracing it to the extent it is. Because I, there are a lot of pitfalls and there are a lot of, or there could be pitfalls and there could be a hands-off approach.
And I think that if anything like this. It's I started my career way back in the, 17 hundreds it feels like. Just kidding. But basically [00:17:00] when the.com era was coming to life, and it's a little bit the same in terms of there's all this excitement and all this there know trepidation and the truth is it is going to be completely different in five years and 10 years.
And we're gonna look back and we're not gonna use AI in every sentence because it's just gonna be. Part of our world, right? We don't say.com anymore because that's old school but it's very interesting. But I and so I'm glad to see folks in companies and sectors embrace it. I'm also glad to see some responsibility conversations happening.
One thing that I am cautiously. Optimistic about, but also very cautious about. And so both of those words are very important in, in, in this, to me is the balance of moving to solution too quickly. It's always been a problem in product management. It's always been a product in design and making good, customer focused products.
Not just hearing one little piece of data [00:18:00] and jumping on a potential solution, but really understanding the problem first. This has the potential vibe, coding and, prototypes that could be spun up in 20 minutes. All this, all of this wonderful stuff. Very cool stuff. But it has the potential to just make that worse, right?
We don't have to spend a lot of time on any problem. We can just build something. Now I have my theories on how that can actually work and be very beneficial, but I'm curious to hear your thought on how do we instill in product teams that. It's still about problems, it's still about users, it's still about finding those needs and solving it.
It's not about the cool new solution or the ability to build this new solution. What are your thoughts there?
Amanda: Yeah, I think you're absolutely right. There's a tendency to, especially in moving in a fast moving product environments to jump straight into the solutioning, use those, quickly prototyping and able tools to be able to just to get something [00:19:00] up and out.
And I think it was hearkening back to what I was mentioning before, I think it's a mindset shift. I think, there's, quite of an expense, I think for not deeply understanding the problem space, in my opinion. And I think that is where misalignment starts. I think, the intentionality and care that you put in to deeply understanding the problems that you're solving for your user, for your business, for your stakeholders, and truly getting a evidence-based driven.
Design solution of impact thoughtfully prioritized roadmap that includes how they might prioritize and they, you're end user, your stakeholders. I think it's a again, a shift into running a product. Management life cycle or a product life cycle. I, I definitely think the foundational pieces of immersion and discovery and really understanding the problem that exists, who might affect and what's at stake, and validating that as soon as possible [00:20:00] before you jump into prototyping and releasing it could be an incremental, again, small change.
And I think that a lot of times in larger product teams. I've noticed this because I've been a part of that is that research is undervalued. It sometimes is usually thought as just testing and user experience testing uxr, and it's much more nuanced and it starts much sooner and it comes with many different mixed modalities.
Generative design, a evaluative testing a lot of the mixed message methods that I had mentioned before. And it usually is the piece that is cut out. How do we close the, testing cycles? How do we remove that? Because we need more time for design, we need more time for development.
And I think it needs to become more of a integrated practice and it does require advocacy and a mindset shift. So I do think that, and I, where I. I try to do my best to support and become an advocate for that is including it [00:21:00] into my project plan and my product roadmap plan where we're doing it, and we'll see what happens, right?
Like I will advocate for that and we will find a way to move quick. We'll find a way to meet that timeline. We'll do it in a crafty way. We'll start with thoughtful recruitment of existing customers. We'll spike in doing some desk research, so we can do some asynchronous collaboration as well.
So I think it becomes crafty, but I do feel like it is a mindset shift for not wanting to move so quickly in a fast paced prototype release to really understanding that value. And I think you'll see that value as you start moving through that cycle. It become the fiber of what, how you view, the way of thinking about your product and the value of research is part of that.
JJ: Yeah that's really spot on. I think, I think you touched on virtually everything that I am feeling and seeing and thinking about this issue or potential issue or opportunity is, I think it's both of those.
[00:22:00] And that is, is. Using it as co-creation right back to the kind of start of the conversation. And I think it's a really powerful way to practically do that now that more teams will have the opportunity to potentially do that with real users. But we still have the potential to, to bias that because we're, literally showing them a solution in the beginning.
Or, too quickly in some cases, as opposed to just digging into the problem a little bit more. Now if we've done that and then we get to the solution and we can go through really rapid, feedback cycles, that's awesome and that's amazing and I hope that happens and continues to happen.
It just is, it can end up being just another thing that forces us into biasing our users and biasing our feedback. And almost forcing this internal view. So I'm a big proponent of it. I actually think it's wonderful and I think it will [00:23:00] end up changing the way we do work in product. But I also think that the best teams are the ones who stick with the idea and that we're still just problems solvers and that the word is problem first and then we go solve it.
And yeah. So it's great to hear your perspectives on this. We've talked a little bit about both of these. But I would love to just cap this part of the conversation with what do you see the biggest opportunities are for AI in product teams generally? Education sector specifically if you want, or just generally, and then the flip side, what are the potential pitfalls of that?
Amanda: Yeah, I think, like specifically for product management and the introduction of AI and all of the tools that we use and the way that's shaping and shifting that role. And I think it's not just with product management, I think it's with any role in technology. And I think also it's with any role of a teacher using a product that includes ai.
And I think that what that does is [00:24:00] transform. A little bit of the focus of your your job, your role to be able to reinvest the time savings that AI can provide you through either automation, optimization, and a lot of teacher facing products. It's, child and classroom data.
It's assessment data that can provide suggestions to what sort of in classroom curriculum you should do next. That is the time savings. So what happens? With that time that you have, it opens. It's an opportunity. It's an opportunity to learn something new to more intentionally give face time to your class or a teacher, for example.
Think about different ways of expanding for a product manager. Upscale for you. What if you learn a new delivery framework? What if workshop facilitation became a big part of your role? You have now the ability to take all of that time off your plate of doing the, risk management and the future [00:25:00] casting.
And what if that became storytelling, what if that part of that time savings, again, opened up an opportunity for you to upskill and to use that time thoughtfully and expand your role to go deeper into maybe a craft? For me, it was designed and research, right? It was the ability to flex, because now I'm able to free up my time and learn more about.
Background to be an interpreter of what AI is providing me, but have the discernment to have that strategic thinking and to be able to bring that into context and the vision. And I think that is the opportunity that we're seeing. Again it's across. I think the board for a lot of different roles in technology a lot of different places in which AI is becoming an automator of tasks of, things that we used to do as busy work.
So what does that time saved give you? And I think that's an open-ended question, but I do think for product management, there's so much at our disposal. [00:26:00] You go deeper into a specific concentration area and learn more. And again, for me, I think that storytelling ability and the future casting and the articulation of a vision to keep it in focus is something that I don't think an AI tool can do for us.
So yeah, I think there's a lot of opportunity. I see it as a value add. It's used in the right way.
JJ: Yeah, I completely agree, and I love, love, love that perspective, and I'm hoping that's what happens, right? I am hoping that because again we've complained for a long time that product teams or product managers become, task masters and order takers from internal stakeholders.
And we've been complaining about it for a long time about how so much of our work becomes tactical, even though we're supposed to be strategic leaders of the product and the product vision. Hey, this is it, right? This is ours. It. And so let's see if the, put our money where our mouth was and see if we actually [00:27:00] take advantage of this. Because I agree a hundred percent there. I think my final ish question for you is thinking about thinking about product managers. We've talked a lot about how product managers, product teams, people that are in a role today. Can get a little bit better. Just a just do things a little bit better.
From an AI perspective, design perspective, human-centered. I have a soft spot for aspiring product managers. Obviously I teach at Johns Hopkins and love, my students who want to eventually be product manage managers. I founded a company about how to bridge those gaps between aspiring product managers and companies.
It's hard to be a new product manager. It's there's a lot of chatter in the market today that says there will be no more APMs and Junior PMs and that we don't need those anymore. I personally don't believe that. I believe it is a role of some sort that we as organizations should create and, and frankly he, build [00:28:00] our pipeline of amazing product talent from the ground up. With that said, if you were talking to an aspiring product manager, and so maybe that's somebody who's already working, but newer in their career and maybe wanting to pivot into product management, maybe it's somebody in university wanting to start in product management or get into product management early in their career.
What kind of advice would you give that person?
Amanda: I think there is so much amazing content out there right now to help ground and shape the. Just the different ways you can apply product management. There are specialty roles now. Product management, ai product management. I was just reading a bunch of articles about how there's now a specific set of courses just on product management and ai.
So do that research. Start broadening your spectrum and scope. What you learn about the fundamentals of product management will always be there, [00:29:00] but how are you starting to maybe think a little bit more broadly about the cap, the possibilities of potentially going narrow or specifically in a sector or a domain that you really like and enjoy.
Do that research and broaden your ability to understand different perspectives and different frameworks. It's something that I've really enjoyed. It's brought a new. Way of looking at product management that I didn't think was possible. And I think that will be a value add as you start to interview having a framework or a perspective or something that you've learned that is not just product management but is in design or in research.
I also think keep your eyes out for internships for where you can be a part of a product team where you are learning on the ground. I think that is. An invaluable experience that I had of understanding my personal touch to product management. It is such a human connection role. You are not only orchestrating the time on the task that, but [00:30:00] also the human science of it, the behavioral science of a team and the interpersonal.
That is just important. Understand and embody that and try to expose yourself to do as many internships as possible. I know this market is tough. It really is. Reach out to those who you are seeing, provide voices in this space. Grab coffee. I am, would love to connect with as many people as possible to be able to share my advice and guide and support.
So yeah, con, continue to educate and expand your view of what pop product management can do. Think about different disciplines that you can go deep into to broaden how you might be able to bring that to a table, to an interview. Explore internships as you can. Keep your eyes open for that and connect with people on LinkedIn.
Those are those would be the advice I have for folks.
JJ: I love it. It's, that's amazing advice. And I echo all of that and, it's people like you who give back a little bit of their time, having this conversation and allowing us to record it [00:31:00] and put it out on product voices and, offering, offering time for coffee chats.
Those are the things that, that when you look back on your career. You realize that those things happened, and maybe it was once a year, once a quarter, once a, that you met someone, that just gave you a little bit of a glimpse, a little bit of a spark at the time you needed it. And so it's so important.
And again, I applaud you for what you do. Not only here but elsewhere. So amended a deal. Thank you so much for joining me. It was an amazing conversation. Loved having you. And thanks again for sharing all of your wisdom.
Amanda: Yeah. Thanks so much for having me. It made me such a pleasure, and yeah, I appreciate the time.
JJ: Thanks Amanda, and thank you all for joining us on Product Voices. Hope to see you on the next episode.
