Course Highlight: Industry experts share Product Management advice with MSSM students
By Jordyn Pike
Professor Adrian Ott recognizes the importance of professional advice in the classroom, especially for students pursuing a Master’s degree. In the half-semester course, Product Management, at 好色先生TV’s Silicon Valley Campus, professionals were invited to speak to Master of Science in Software Management (MSSM) students about the nuances and details of a product management career.
Large companies such as Meta, GoDaddy and Hewlett-Packard Enterprise were represented by speakers, along with emerging ventures such as Aisera, Inevitable AI, and Magnetic. Each guest covered a different topic related to product management, bringing their own unique perspectives, career histories, and expertise in the field.
Vidya Srinivasan: What Makes a Good Product Manager?
was the first guest speaker to share her expertise as a Product Manager (PM) with Professor Ott’s students. After thirteen years of professional experience, she currently works at Meta as an L7 PM and is responsible for Trust and Safety efforts on Threads, having joined the organization in 2021. Prior to joining Meta, Vidya was a PM at Microsoft.
With her wealth of knowledge in the field, Vidya shared with students the traits that make a PM successful, how a crisp product strategy is built and implemented, and the importance of recognizing the impact that tradeoffs can have on an organization.
According to Vidya, a good product strategy delivers maximum value to users, and in turn, to the business. Simply put, product strategy involves making decisions about what the product should and should not do during its life cycle. A product should solve a problem that users are experiencing, but that solution should also meet users where they are at. Vidya emphasized that simply solving a problem is not enough; making sure there is a market for your solution is half the battle.
Does the problem need to be solved now? Or will your solution go to market too soon, and people will be hesitant to become early adopters? To answer these questions, Vidya affirmed that products need to have a north star, a goal that the product team is striving to achieve, to ensure that changes are not too small that they are just features, or too large that they are new products entirely. In Vidya's opinion, every decision a PM makes creates a consequence or tradeoff that needs to be considered, as it can have adverse effects on the product or the company as a whole.
The most important skill a product manager can have is the ability to drive clarity within their organization. The job presents a PM with ambiguity, along with competing priorities and interests, and a good PM can cut through the noise and execute within what is best for the product’s success. Vidya noted that a PM needs to be an extrovert, as they must interface with diverse groups of people, ranging from engineers to lawyers, and consider the contributions and opinions of each group.
In conclusion, Vidya describes the job of a PM as inherently complex. It is non-transactional and generally chaotic, where you need to balance the demanding environment with quality product decisions.
Rahul Goyal & Maneesh Sharma: How has AI Impacted Product Management?
Recent CMU Silicon Valley graduates (MSSM ‘23) and (MSSM '23) are very familiar with AI’s impact on product management. Both alumni are AI-specific product managers, and this proximity to the technology has taught them what future PMs need to consider regarding AI before they embark on their careers.
Rahul is an AI Product Manager at Cisco, working on the organization’s AI Defense Team. He has previously worked at Hewlett-Packard Enterprise in a PM role. He is also the founder and host of the podcast , where he interviews other PMs and they discuss developments within the industry. Maneesh is also a Product Manager and recently worked at Aisera, focusing on AI Agents, and is currently a Senior AI Product Manager for RingCentral. Both Rahul and Maneesh are critically aware of the changes that the advent of AI brings to their industry, and gave students insight into how to be a PM for an AI product.
AI products have shifted the way a PM operates, according to Maneesh and Rahul, as they now have to consider both the user experience and satisfaction, along with the efficacy of the AI software, equally. Previously, products would be built entirely first, then evaluated based on user feedback and updated from initial data. However, with AI products, every change is done iteratively, meaning that the product is not fully realized when sent to market, but is a piece of what the final product will be. The iterative approach presents a range of challenges for PMs, as it generates feedback from users based on an incomplete version of the product.
Beyond the timeline challenges that AI presents PMs, Maneesh and Rahul also discussed what they have observed about the widespread adoption of AI. Comparing AI to the invention of Excel and how it revolutionized the field of accounting, they called AI the catalyst for how problems will be solved in the future for product managers. However, they cautioned that AI should not be the primary goal of a product; ultimately, solving problems is the fundamental objective of a product. The tech industry may lean on AI to be a universal solution, but PMs should determine if an AI product is a valid use case for a problem, or if it makes sense for a business at all.
A final analogy for AI that the pair used was that future product managers should treat it like electricity, rather than how it is sometimes treated like magic. AI is not a one-size-fits-all solution, but it is a vital tool that both product and product managers should utilize.
David Thomson: What Happens When Product Development Happens in an Instant?
Twenty-seven years of experience in design, product strategy, and executive leadership have endowed with a wealth of knowledge in the realm of product development. Founder and former Global CEO of Momentum Design Lab, and current Founder and CEO of Inevitable, David presented students with his perspective as a designer by trade that has had to adapt to AI collapsing the product management cycle, and the limitations that AI can have on the efficacy of product and business ideas.
David’s former career, which involved selling experience-oriented design and optimizing the experience around intangible elements of service design, changed instantly with the introduction of Claude 3.5 Sonnet. This specific version of Anthropic’s AI was able to, according to David, encode the entire product design life cycle, including strategy, design, product management, and software engineering, which were collapsed into each other and became accessible at the click of a button within a chat box. What once took teams of people and endless collaboration could now be accomplished instantaneously, before a team could even send out meeting invitations.
This advancement in AI technology, while an escalation of the timetable David was used to working with, was instrumental in the development of his new venture, Inevitable. With the rapid maturation of skills that AI agents can possess, almost every task can be automated, from demos to presentations, saving time and startups’ precious resources.
After serving as a CEO and becoming accustomed to having teams of employees dedicated to tasks and creating deliverables, David found himself utilizing agentic AI to develop his company’s first product. His journey of finding the software that best suited his needs regarding automation was impacted by the constantly changing landscape, and he saw that the most efficient platform can change as quickly as every month.
The ease with which AI enables developers to create agent-based products, compared to task-based products, has led David to question how to design agent systems with human values in mind. The lightning-fast pace that AI technology has set has created the opportunity for lapses in ethical judgment in the product development lifecycle. It also leads to something David defined as the velocity trap—developers are now able to create a product at the same speed at which the idea occurred, leading to products that lack evidence of future success.
Additionally, he found that the design elements that were once foundational to the field have shifted their position in the development cycle. What was once a design thinking waterfall model, a rigid order of events, had now been replaced by the implementation of the principle in a loop. Now, the designer’s pathway of once empathizing, then defining, then ideating, then prototyping, and testing last, should instead be conducted at every step of the development process. Every iteration of a product should run through the design thinking’s validation process, and the product should always be in a building, testing, and ideating state. This conclusion is the basis for Inevitable’s product, SignalPattern, which compresses the product development process into an agentic workflow that makes validation an eight-minute process, complete with specifications.
David Thomson’s lecture provided students with insight into the changing landscape of product development, emphasizing the risks associated with the collapsing space between idea and prototype, as well as the shift in the design thinking waterfall.
Thomas Shelley: What are the Consequences of Not Defining Your Goals?
The tumultuous nature of product development, management, and launching is all too familiar to (ISM ‘15), the second-to-last professional who spoke to Professor Ott’s product management class. Thomas began his career by creating a startup, but then spent the majority of his career working in the gaming industry. He has more recently returned to the startup space and shifted his focus to the tax industry. Currently, he is the co-founder of Magnetic, an AI software sold to CPA firms that automates the creation of tax returns. Magnetic was recently selected and participated in Y Combinator’s Summer 2025 Cohort.
His unique and varied career has exposed him to different facets of product management, giving him the authority to share his expertise with students. By walking through his past work experiences, Thomas shared where he learned hard lessons and gave real-world examples.
Thomas has learned from his career that the importance of solid data collection is crucial to avoid overthinking and outsmarting one's product. In his experience, instead of conducting research, analyzing feedback, or even just using the product yourself, Thomas found that he and other people could be guilty of trying to find the smartest thing to do with limited information regarding the product’s effect on users. Instead of taking the time to become more knowledgeable about the product and industry, some individuals will reinvent the wheel without the necessary data to support their efforts.
At the first startup he co-founded during graduate school, he cited never truly understanding the business's goal as a core reason why it was not a success. He and his co-founder were so hyper-focused on creating back-end infrastructure, scalability, and integrating payment processing that they never actually processed a real transaction. By his own admission, they created what they thought a startup should be, instead of creating a product people wanted to spend money on, or at the very least, use. In hindsight, Thomas concluded that if they had taken the time to actually write the goal of the business down on paper, being forced to articulate what they were striving toward, they would not have overcomplicated the product to the degree they did.
The lesson of goal-setting followed Thomas into his corporate career at Zynga and Niantic, where goals were clearly defined, and the teams he led needed to achieve these goals or face reassignment or the dissolution of their roles. At Zynga, he worked on their mobile poker game and found that when they focused on the goal and the easiest solution to completing it, that is when they achieved the most success. To increase revenue, simply make the game easier for users to get hooked on and give them more digital currency to start their gameplay, keeping them engaged. Conversely, at Niantic, when given a strict deadline to increase revenue in 30 days on a Settlers of Catan mobile game, the team drifted from the goal. Instead of trying to maximize profits, they tried to launch a timed event feature that proved too complicated to rapidly increase profits, and the game was abandoned by the company. Thomas’s takeaway was that practicality and strict adherence to the goal are the best ways to ensure that efforts are in alignment with the future success of the product.
Thomas Shelley reminded students that obvious solutions are not often obvious when working on a product daily, and that success can be achieved through a path of least resistance.
Vinod Suresh: How Do Core Beliefs Influence Problem-Solving and Solutions?
For , figuring out and diagnosing the problem a customer is facing is more important than creating the solution. The last lecturer featured in the Product Management course for MSSM, Vinod, led students through what he learned as a PM at companies like Walmart, Anheuser-Busch InBev, eBay, and his current organization, GoDaddy. He began by presenting students with his four core beliefs, which he has developed over an impressive career, and then gave two case study examples of his process for researching and identifying problems that plague consumers, along with the solutions developed for each.
The four core beliefs that Vinod has defined for himself are:
- Fall in Love with Customer Problems
- My Team is My First Customer
- Change is Always Good and
- Student for Life
The first belief aligns with his emphasis on the problem rather than the solution, as he has found that professionals can tend to fall in love with the solution. They fall into the trap of thinking they have solved the problem the best or the smartest, even if their solution is not necessarily the best for users. By falling in love with the problem, not the solution, you can better understand what actually needs to be solved and how the user experience can be improved by a solution, rather than thinking about a solution and then finding a problem that it would fix.
“My Team is My First Customer” is Vinod’s second core belief, which relates specifically to being in a leadership position. To build the right product for customers, the first step is building the right team. The main way to influence the execution of a product is by building a team of experienced, dedicated individuals who are committed to creating a great product, just as a company is devoted to its customers.
The third belief, “Change is Always Good,” originated during Vinod’s time at eBay, where frequent manager turnover was common. Within 13 months, Vinod had 11 different managers, leaving his peers on the team demotivated and distressed by the instability. Instead of despairing, Vinod saw an opportunity in the situation and chose to be optimistic about the tumultuous environment. This time taught him that every company is going through some type of change, whether it's related to business processes, innovation, technology, or the marketplace in which it conducts business. Instead of fighting change, adapting and learning how to capitalize on it is much more beneficial for professional development.
“Student for Life,” the final of Vinod’s four core beliefs, is the result of his lifelong devotion to being a student. Since beginning his professional career, he has returned to school in various formats and has 22 total educational experiences on LinkedIn. Currently, he is taking MIT Professional Education courses alongside his professional endeavors.
These core beliefs laid the foundation for students to understand Vinod’s processes and how he approached not only being a PM but also being a leader in a professional space. After these were explained to students, Vinod presented case studies of how he implemented his beliefs and solved problems for Walmart and GoDaddy.