5 Practical Tips for Breaking into AI Product Management with Marily Nika
Shyvee Shi
Product @ Microsoft | A forward-thinking product leader combining creativity, user psychology, and AI to drive growth and scale communities | ex-LinkedIn
Welcome to the latest issue of the Product Management Learning Series - a series of live streaming events and newsletter articles to help you level up your product career! ??
For our 13th installment, our speaker was Dr. Marily Nika . Marily is an AI Product Leader with over 10 years of experience in AI Product Management. She has worked for Google & Meta as Product Lead and is an Executive Fellow at Harvard Business School where she teaches Digital Product Management & Strategy. Marily is also a LinkedIn Learning instructor and has a PhD in Machine Learning from Imperial College London. Marily was a 3x TEDx Speaker.
If you missed the event, you can watch the full event recording here. ??
Below are the main takeaways from the conversation I had with Marily:
Generalist PMs focus on building product features, while AI PMs manage the problems.
Marily discussed the difference between generalist Product Management and AI Product Management. She stated generalist PMs usually have a target user persona, they look at their pain points and figure out how they can help users achieve what they want, through various different potential solutions.?
On the other hand, as an AI PM, you're helping your team and your company solve the right problem, so you're managing the problem, not the product. Marily shared that the key questions you need to ask in AI product management are, how can you find the best solution to a problem? What are you hoping to see in a few months to a year to know if the solution can be converted into something that’s going to be meaningful to the users? What happens if a competitor has solved the problem first? AI management is about making these strategic decisions on what can be leveraged that make sense for the users.
Always be mindful of figuring out what ‘good quality’ means when it comes to deciding whether a product is ready to launch.?
Imagine AI as an input and an output. Marily shared an example of clustering photos: put a group of dog and cat photos together; how can you tell which one is which and subsequently search for them? This is an example of supervised learning: you label a bunch of photos telling the system which one is a cat vs. a dog. You then pass on millions of cat and dog pictures and train the model to understand how to recognize them. After this supervised training, the model would provide an output: the probability of whether a picture was either a cat or a dog.?
From there the question for a PM becomes, how can we apply this technology onto a product and be confident that the quality is good enough for it to be usable and valuable to our users?
Avoid developing AI products for the sake of the technology or algorithm.?
Marily advised AI Product Managers to avoid the ‘shiny object trap’ when it comes to developing AI products, i.e., don’t develop AI products for the sake of the technology or algorithm. Instead she shared that you always need to have a mental model of how your product can work, and some of the market data that can validate its potential success. Even when there is no market data since there is no user yet, there are adjacent products launched by other companies into which you can look. From there, you can give yourself or your team a certain amount of time to decide on whether or not to continue and proceed.?
To break into AI PM, focus on building your understanding of AI through colleagues, courses, books, 20% projects, and learning the AI tools online and in hackathons.?
Marily shared that there are two different paths to get into AI PM depending on your current background. For someone with an engineering background, especially those in AI, they likely have the underlying knowledge, and their gaps often are the strategy component of PM, how to create roadmaps, etc. The path to AI PM is more straightforward because there are books to read and courses to take to round out the product knowledge to fill in the skill gaps.
Marily shared that for the other folks who have no technical background and want to become an AI product manager, the best bet would be starting with a non AI PM role so that you can actually master the process, the creation of roadmaps, general product strategy, and how to launch products. Even better if you can work with a zero to one product, and from there apply for roles in AI Product Management. To build the AI specific skill set, she recommended taking AI courses on platforms like Coursera, participating in hackathons and leveraging AI in your projects.??
Looking back from her own experience, she recommends starting the process of breaking into AI PM as early as possible, and reaching out to friends and colleagues who are already in the space to network with and learn from. She recommends even asking some of those friends and colleagues if you can help them on a 20% project to gain some experience in AI PM while still working in your current role. Marily expressed the importance of going the extra mile to get your hands dirty by trying to use AI online tools yourself to get exposure.?
She has a recurring cohort course launching on how to break into AI Product Management starting this week (Sep 26)! Check it out here. You can also follow her on LinkedIn and Instagram to stay up to date with her PM course offerings.
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Get out of your head and push forward, tell yourself you can do it.
Marily shared a piece of advice she would give to her younger self and to women and people from underrepresented groups, to get out of your head and not think that you can’t achieve something because of the situation you are in, your gender, or your background. It is up to you to go out and achieve your goals and dreams. The basis of comparison should be looking at your growth and comparing yourself to other versions of yourself from the past and not comparing yourself to anyone else. If an opportunity presents itself, you should grab it and run with it.?
She shared a personal example of when she was eight months pregnant and someone asked if she wanted to film an official video for Google about the day-to-day of a PM, and she did it without a doubt in her mind. She finished this thought by sharing that if anyone tells you that you can’t do something just push forward and prove them wrong.?
More on Marily’s story of her talk with Google here.
Additional gems from Marily:
?? The Nintendo Switch , a hybrid video game console, consisting of a console unit, a dock, and two Joy-Con controllers is Marily’s favorite product. Her favorite game, Monkey Island, just came out recently for the Nintendo Switch.?
?? Marily shared that her product role model is Deb Liu who is the CEO of Ancestry. She will be coming to join the PM Learning Series on December 16th. You can register to that session directly by clicking here. ??
?? The last piece of advice from Marily is to understand the importance of sticking with your goals even if things don’t work the first couple times you try to do something. Don’t give up and keep pushing forward your goals!?
?? Special kudos to Andrew Altschuler for writing this article.
This article is sponsored by Mentordial. Learn and grow with help from over 150 world-class mentors from top companies like Google, Apple, Amazon, Slack, Facebook, and LinkedIn. Use the coupon code 15_off to get 15% discount. Learn more at https://www.mentordial.com/ ??
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Learn more about the Product Management Learning Series and view past recordings here .
Please i am interested
Product | Experienced in business, marketing and design strategy
2 年Another wonderful piece Shyvee! Always approachable, as well as insightful. Keep ‘em coming! Thank you Teresa Torres for sharing your knowledge with us.
Process Engineer, Product Manager, Product Marketing Manager, Business Strategist
2 年Thank you for sharing this.
Product Manager @ Pace CCS | PhD in Chemistry | Certified Product Owner | Certified Scrum Master
2 年Thank you Shyvee Shi for posting this, and Marily Nika, Ph.D for sharing your recommendations, such an insightful post! I am a scientist by training and I've always been focused on solving problems. Despite the fact that I spent the last five years as a Generalist PM and polished my skills related to building the right product, I always felt that AI PM is something that I want to end up doing. Now I have the explanation, thank you for articulating that!
Product, Strategy & Technology Leader | I build AI driven B2B & B2C SaaS Products and grow startups & scaleups (PLG) | ex-IBM | Startup Advisor | Fulbright Scholar | AI Council Member | BOD, Coach & Global Speaker
2 年I enjoyed the session with Marily. Thank you for re-sharing the key take aways Shyvee Shi