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ready to move to the next level in your
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product career I'm from intentional
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product manager join me as we discuss
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ways to help you stand out in your job
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search and your career so you can have
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more impact and make more money nikel
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thank you so much for being here as a
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guest speaker on this video yeah I'm
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happy to be here uh thank you for having
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me awesome so as we dig into you know
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AIML product management something that a
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lot of people are very keen to move into
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and learn about take us through your
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journey in both your career and then
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getting into this field yeah sure uh I
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can start with a brief intro about
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myself um so I'm Niko I've been in AI
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product management for over five years
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now I'm currently in AI product manager
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at meta where I work on AI for ads uh
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prior to that I was an AI product
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manager at Adobe both on consumer and
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Enterprise Products um in my rool is at
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and Adobe I've built and scaled uh
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multiple AI products uh serving you know
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billions of individuals and millions of
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of
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businesses and in addition to that I'm
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also a part-time AI educator and Mentor
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I run a podcast called Art and Science
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of AI where I share like my passion and
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learnings um around AI with people who
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are curious prior to AI product
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management um I also used to advise like
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Fortune 500 companies on uh Big Data
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strategy and implementation like the
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early days of AI as a consultant at deoe
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uh that's where I started my career and
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I live in the San Francisco Bay Area um
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outside of work and AI uh some of my
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hobbies include uh reading Science
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Fiction and Fantasy and
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weightlifting we lifting
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amazing uh really really great to hear
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about your your journey into the space
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so I'm I'm going to like it seems that
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you had uh Ai and big data background
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byi prior to your first role as a AI
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product manager is that actually yeah
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that's right so I've been involved with
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AI for over 10 years now like I wrote my
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first Master's thesis back in 2014 on
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comparing two different approaches to
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language understanding there was the
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rule-based systems approach which was
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called formal semantics and then there's
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the machine learning approach which was
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called natural language
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processing and then like I said I got
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into um management consulting and worked
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on strategy and analytics projects there
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uh a lot of like big data strategy um I
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think where I really made the transition
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to Ai and product management was when I
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went um to business school so um I I
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went to a business school at Yale from
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2017 to 2019 and and at that time in
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addition to the business coursework that
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we were required to take I took a lot of
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elective cours work in uh computer
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science and machine learning and I was
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learning about topics like uh language
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modeling and natural language processing
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and coincidentally this was the time
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when open AI had just launched gpt2 at
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the time and I was like totally Blown
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Away by the possibilities and
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implications for um you know for
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business and society and and the impact
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that that AI was going to have and
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that's kind of was a transformative
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moment for me when I realized that I
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wanted to Pivot my career to focus more
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on this direction because I thought this
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is the thing that's going to be really
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impacting the world in the next decade
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or two awesome so at that point you like
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you you just realized this curious like
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what was the journey from that
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realization to actually getting your
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first AI product man control what did
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you do how did you prepare a lot of
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people are are interested in in that
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that aspect of it yeah um so this so
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like I said I was at business school I
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was doing an NBA program and uh MBA
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programs are typically set up to help
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people make career transitions so most U
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of my peer group including myself is
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there trying to transition from one
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thing to another people are trying to
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transition functions Industries
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geographies different kinds of things so
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it's it's a time it's an environment
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that is good for it's conducive to
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helping people figure out how to
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navigate this journey so I that was I
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had a lot of resources to to help me
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with this that that's one thing I I
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think I I want to call out so the MBA
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program really helped and I like I said
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in addition to that I was also taking
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some coursework in U machine learning
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and computer science so that's something
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that that certainly helped me a lot like
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I was tinkering with projects on my own
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just like learning how to build um
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simple applications like how to um build
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machine learning models and things like
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that and that really was something that
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helped me stand out I was able to um
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bring my like passion and enthusiasm for
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machine learning and AI to the
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interviews when I started talking to to
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company and that's something that that
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helped me stand out but yeah the reality
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of it is that I did not have any
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experience in product management at that
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time I was uh my background was in
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management consulting and so I had some
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domain expertise in AI I was trying to
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leverage that and transition to product
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management at tech companies so I think
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U yeah I would say the things that
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helped me were one is like having
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resources and peer group that like
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helped me navigate this transition
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through theba program second is my
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domain expertise and like passion for um
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machine learning and AI which helped me
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stand out that's the second thing and
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maybe the third thing is like I was very
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fortunate in that companies like so the
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first job I got out of business school
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was as a product manager at Adobe on a
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product called Adobe experience platform
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which is a uh consumer dat plat a
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customer data platform that's used by
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like Enterprise marketing teams and
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within that we were building some
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machine learning and and data science
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capabilities um
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Adobe was helpful in that they have um
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NBA recruiting programs um so where the
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goal of that is often they're not trying
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to find the best candidate for a given
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role but they're trying to get talent
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that they think will grow with the
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company and possibly stay in in like
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multiple roles so that's another thing
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that helped me um yeah so I I would say
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and then of course there's the standard
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um you know interview process stuff that
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you have to go through like you have to
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develop a pipeline of applications like
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be ready to face tons of rejection um
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apply to hundreds of roles get hundreds
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of rejections just keep pushing through
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that and uh you have to be willing to
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proactively go out and and network with
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people um constantly like having
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conversations with new people trying to
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um learn more about uh different roles
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and companies and what's available and
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then yeah there's the whole like
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interview preparation process you have
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to like practice and do mock interviews
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and make sure you're able to present
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your Knowledge and Skills in a way that
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um you know comes across um as having
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the right kind of expertise so yeah the
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whole G just thinking of when you were
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applying for those product roles did you
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focus it on cool like o AIML product
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management roles I mean at that point
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they were probably like fewer than the
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number that exists right now given the
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interest but was it very focused or were
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you open to any sort of product
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management roles oh at that time I just
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wanted any role related to AI or machine
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learning it I wasn't focused on product
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management per se so I applied to a
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bunch of different roles I
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I applied to many data scientist roles I
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applied to like analytics roles um so
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yeah my lens at that time was less on
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product management it was more on AI
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because I was like hey that's what I
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want to do um it just turns out that
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given my background and experience like
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now I realize it like product management
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is a really good fit for me uh I don't
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know maybe I could have also been a good
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data scientist or machine learning
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engineer but it was harder at that time
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to convince anyone that they should take
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a chance on me for that uh product
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management had a much more clear story
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and yeah since then I've been doing this
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for five years I think I I found the
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right fit um I love uh product
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management it enables me to um have like
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the level of technical exposure to AI
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that I I want to have but also it
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enables me to focus not very narrowly on
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the technology but more on on what are
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the problems that we're solving with
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this what's like the longer term
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strategy uh for developing products with
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with this technology and things like
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that so yes I I found a good fit in this
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function of product management but it
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happened by accident at the time I
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didn't really know what product
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management was um I just wanted to work
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on cool things with AI love it okay so I
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understand all those well so now I'm
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curious about to whatever extent you can
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share you know assume I know there's
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confidential compaign for which you
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won't share but like what are the kinds
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of things you worked on that have this
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intersection of product management and
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AI both at Adobe and meta yeah sure I
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I'd be happy to talk about um what I've
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done so far at these companies so at
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Adobe I had two roles the first role I
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had was um as a product manager on Adobe
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experience platform as I said what the
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product is it's a customer data platform
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that's used by Enterprise marketing
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teams to unify all of their customer
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data in one place and then um use that
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to create personalized uh experiences
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using machine learning and data science
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so for example a company uh has so say
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like a hypothetical example say you're
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like a company like Best Buy um you have
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customer data from many different
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sources there's customers who purchase
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things in store or there's customers
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that purchase things online those are
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two different data sources you have you
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have data about customers who interacted
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with your website uh best buy.com and
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that it gets uh captured through
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analytics data uh adoe actually has a
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analytics product called Adobe analytics
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and you know people who use that like
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this was a good fit for them then you
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also have data like uh there's call
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center data customers might call you and
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um ask some questions or something so
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the idea is that like we have companies
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like uh Best Buy for example but you can
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generalize that example have a lot of
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customer data from different sources and
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now they want to leverage this all the
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data together to create like
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personalized um experiences so for
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example next time you call Best Buy
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instead of just asking you that hey like
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what are you calling about like um can
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they leverage all of this data to
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predict like what you may be calling
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about and give you a more personalized
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EXP experience or when you go onto the
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storefront um on the website like
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instead of just showing you something
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generic maybe they can show you things
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that are relevant to you so that was the
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the first um product that I worked on um
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then after that so Adobe has multiple
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business units this their their biggest
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business unit is called the Creative
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Cloud where they create um software for
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Creative professionals like video
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editing photos um audio and so on uh the
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other business unit they have is called
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document Cloud where they create uh
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productivity software to work with PDFs
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and documents and the third business
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unit is called the digital experience or
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the marketing Cloud so that role that I
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described and that product that was in
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the uh marketing cloud and then uh I
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moved to a new role at Adobe in uh Adobe
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Acrobat AI so at the time what we were
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trying to the problem we're trying to
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solve is that reading PDFs on your
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mobile device sucks because PDF f s are
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optimized for large screens or like A4
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size paper or letter size paper when you
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read a PDF on your mobile you constantly
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have to pinch and zoom to read it in the
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right way um so we were using AI to
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understand the content and structure of
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documents and then create a mobile
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responsive PDF reading experience uh it
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was called liquid mode and it still is
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and I I think it's awesome it's one of
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the best ways to read a PDF on on your
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mobile device and now of course like
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Adobe Acrobat AI has a lot more than
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that there's with generative AI they're
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also trying to get into helping people
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um understand documents like ask
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questions and answers and then things
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like that so that's one thing I worked
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on uh now in my current role at meta up
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I work in AI for ads and specifically
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focusing on improving the ads personal
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ization system and the algorithms that
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uh determine which ads to show to which
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users so our goal is to make meaningful
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connections between advertisers and
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users so we want to help advertisers
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find uh the right customers who are
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interested in their products we want to
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find help users find the right products
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that that they're interested in and this
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is a problem space that comes with like
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tons of uh data like uh because there's
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at any given time like there are
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billions of users there's like millions
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of ads in the system and how do you
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figure out like this um matching problem
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what kind of data can you leverage for
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that what are the kind of algorithms
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that you want to use for that um and
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yeah that that's kind of the area I
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focus on and this also interesting
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because there's tons of um it intersects
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with not only
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like machine learning but there's also a
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lot of like uh legal regulatory privacy
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concerns that that you have to pay
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attention to so it's a by Nature like a
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very cross functional role and there are
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like many considerations that that you
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have to balance awesome great to hear
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about your work now I'm going to put you
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just like sort of last set of questions
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but given that there's a lot of product
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managers who are let's say somebody with
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you know some experience in product
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management but they're really trying to
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figure out how do they get into AI
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product management to some extent how do
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they future prooof their career like
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that's the term often people use and
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thinking about the impact AI is going to
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have on product management product
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development in general what sort of
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advice would you have for them would you
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suggest any trainings would love to hear
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that from you yeah so I think there are
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multiple ways in which you can think
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about engaging with AI so one is at a
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personal level and one is at the level
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of the product I would say I would
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separate out these two things so SE
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we're talking about a target audience of
00:16:06
product managers right so regardless of
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what your product is there are certain
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activities that you do on a day-to-day
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basis as a product manager you're trying
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to do some market research industry
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analysis you're trying to develop a
00:16:21
strategy for your product and a road map
00:16:24
and trying to come up with requirements
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there's a lot of like communication and
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presentation so all of these things I
00:16:30
think it's definitely helpful to start
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thinking about how you can use AI to
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help you be better at those things more
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productive more efficient and so that
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you can focus more on high value work
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and this I think is General to almost
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like any profession product management
00:16:48
is just an example of this so I
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definitely think whatever profession
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you're in um please start using AI uh
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and see where it can add value what are
00:16:58
the things that it can make you better
00:17:00
at where are the things that can help
00:17:01
you scale up where are the things that
00:17:03
can help you automate um so that's one
00:17:05
thing and that's advice I would give to
00:17:08
like anyone um regardless of the
00:17:10
profession um so yeah within product
00:17:12
management I would look for things that
00:17:15
you think could are repetitive things
00:17:17
that you're doing like frequently um
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things that you could potentially
00:17:22
automate or augment with with AI and for
00:17:25
me often it's things like doing research
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like I need to find some information
00:17:32
across like a whole bunch of documents
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and how do I find the right sources of
00:17:38
information and so I'm very lucky in
00:17:40
that I work at meta and we have a bunch
00:17:43
of pretty like sophisticated internal AI
00:17:46
tools uh to help people be more
00:17:49
productive and solve some of these
00:17:50
challenges uh of course I realized that
00:17:53
most companies probably don't have like
00:17:54
specific internal tools for that uh so
00:17:57
in that case you would have to let
00:17:59
leverage um existing systems like Chad
00:18:02
gbt or gemini or whatever um of course
00:18:06
like pay attention to uh privacy
00:18:08
policies and what what data you're
00:18:11
allowed to share or not um so that
00:18:14
that's a huge like make sure that
00:18:16
whatever you're doing with your
00:18:17
company's data that it's appropriate
00:18:19
that you're U if you're going to go put
00:18:21
that on chat GPT make sure you're
00:18:23
actually allowed to do that if you're
00:18:25
not then try to work with some example
00:18:27
or dummy like data and use the insights
00:18:30
from that I think this problem will be
00:18:32
solved pretty soon most companies are
00:18:33
probably going to either have their own
00:18:35
in-house Solutions or make deal like
00:18:37
chat GPT open Ai and these companies
00:18:40
have Enterprise solutions that have all
00:18:42
the privacy and data security built in
00:18:44
so pretty soon I'm sure most like
00:18:47
companies are going to have um that
00:18:49
built in so yeah start making use of
00:18:51
those do it for your own personal life
00:18:54
as well um in that case then you're not
00:18:57
restricted by your company's data
00:18:59
policiy so a simple example that I use
00:19:02
as you're like a content creator you
00:19:04
create YouTube videos and things like
00:19:06
that and you know that it's a lot of
00:19:08
work every time you create a video you
00:19:12
have to like edit it um and then you
00:19:14
have to extract like a title chapters
00:19:17
descriptions show notes and things like
00:19:19
that so for myself like I automated that
00:19:23
I created like a custom GPT where it has
00:19:27
knowledge about my podcast and then I
00:19:29
just upload a new podcast transcript to
00:19:32
it every time and it automatically gives
00:19:34
me all the info I want in the format
00:19:37
that I wanted so it'll suggest here are
00:19:38
the episode titles you can use here's
00:19:41
some descriptions you can use here are
00:19:42
the chapters and and so on so anything
00:19:45
like that like anything you're doing
00:19:47
repetitively um think about how to
00:19:51
automate that and I would say yeah both
00:19:52
in your personal and professional life
00:19:56
and then there's the other dimension of
00:19:58
okay like with as a product manager sure
00:20:01
I'm using AI for my personal
00:20:03
productivity but you're also like now I
00:20:05
want to think about um maybe
00:20:08
transitioning to working on like an AI
00:20:10
product or like incorporating AI into my
00:20:14
own product and so yeah that then is
00:20:17
different that's more of like a career
00:20:19
transition type thing especially if you
00:20:21
want to change your uh role to like work
00:20:24
on a different product that's more AI
00:20:26
focused um I don't know if that is I I
00:20:30
do see like a lot of people these days
00:20:33
want to make that transition but I'm not
00:20:35
sure if it's super necessary because I
00:20:38
think like pretty soon like all products
00:20:41
are going to have ai incorporated into
00:20:43
it in in some way so you could also just
00:20:46
think about well how am I incorporating
00:20:48
AI into my current product um so that's
00:20:52
something you do but yeah maybe there
00:20:54
are other arguments you could have like
00:20:55
you could say like okay for my personal
00:20:57
growth and learning I want to go work at
00:21:00
a company that has more established
00:21:03
understanding of how to use Ai and so I
00:21:05
I want to work there and then bring the
00:21:07
learnings back um yeah I mean I I think
00:21:10
that's it's it's similar reasons why I
00:21:12
think PMS often want to work at Big tech
00:21:16
companies um to help accelerate their
00:21:19
career and then you can kind of go to
00:21:22
accompanying any other domain and then
00:21:24
you can transfer your knowledge of best
00:21:26
practices and and things like that to
00:21:29
the other domain you're working and so
00:21:31
yeah I think if that is your goal um it
00:21:34
does make sense to try and get some
00:21:37
experience working on AI products that
00:21:41
are being developed by some of the more
00:21:44
like sophisticated like AI uh companies
00:21:48
and I guess if your question is like
00:21:50
well how do you make that happen um I
00:21:54
think a lot of it is just general PM
00:21:57
career guidance will apply here um one
00:22:01
thing I always advise people is to think
00:22:04
of your career transition as like a
00:22:08
multi-step journey and it's often not a
00:22:12
single step like often people who are
00:22:15
like not product managers right now
00:22:17
they're doing something else they might
00:22:19
want to know like well how can I become
00:22:21
an AI product manager at meta and I
00:22:25
think one of the things to recognize is
00:22:27
that that may not be something that you
00:22:29
can do directly in one step like think
00:22:31
about if I were to break this down into
00:22:34
a multi-step Journey um what would that
00:22:36
look like so maybe let's say for example
00:22:39
you are um a product designer at like um
00:22:44
a fintech company so think about moves
00:22:48
you can make that minimize degrees of
00:22:51
transition like so there are many
00:22:53
dimensions to your role right there's
00:22:55
the function you're in which is like
00:22:57
product management product design
00:22:59
Consulting whatever there's the industry
00:23:01
you're in there's the type product
00:23:03
you're working on there's the technical
00:23:05
domain that you working so for the
00:23:08
easiest transitions to make are ones
00:23:10
where you are minimizing the number of
00:23:13
things that you're trying to change so
00:23:15
if you're like hey I'm keeping
00:23:16
everything fixed and I'm just changing
00:23:19
this one thing I work in um you know B2B
00:23:22
SAS I want to go work in b2c SAS doing
00:23:26
everything else the same same industry
00:23:28
I'm manager so that's the easiest the
00:23:30
hardest transition is where you're like
00:23:32
okay I want to change a bunch of things
00:23:33
I want to change the type of product I'm
00:23:35
working on I want to change my function
00:23:37
from product design to product
00:23:38
management I want to change the type of
00:23:40
company I'm working at from a startup to
00:23:42
a big tech company um so I think yeah
00:23:46
you should balance that if if you notice
00:23:48
that like transitions you're trying to
00:23:50
make are like many um try to break that
00:23:53
down into smaller chunks and see like
00:23:55
what are more reasonable Transitions and
00:23:58
specifically I think for the transition
00:24:00
of like I have no experience in Ai and I
00:24:04
want to work on a more AI Focus role for
00:24:07
that part of the transition try to find
00:24:10
ways to show uh your understanding of
00:24:13
this domain and it could be as simple as
00:24:16
the kind of things I mentioned earlier
00:24:18
which is like find ways to incorporate
00:24:21
this into your personal and your you
00:24:23
know workflows and maybe create some
00:24:27
automations go publish them on like your
00:24:30
GitHub profile or there are many no code
00:24:32
platforms now where you can do that and
00:24:34
that's a really simple way of um being
00:24:37
able to demonstrate your Um passion and
00:24:40
expertise in this area and show that
00:24:42
you're actually able to use this stuff
00:24:44
to to solve real problems yeah become a
00:24:47
power user first before you go and try
00:24:49
to understand the tech yeah yeah I think
00:24:52
so awesome nichel thank you so much for
00:24:55
sharing your journey sharing your own
00:24:58
transition and then also advice for
00:24:59
others I totally resonate that example
00:25:02
of automating YouTube stuff I I I follow
00:25:05
the exact same thing and it's so helpful
00:25:07
and it's taken so much repetitive work
00:25:09
off my plate awesome well I I hope uh
00:25:12
whoever is listening to this like finds
00:25:14
this helpful oh and also if I may I'd
00:25:17
love to make a last plug for my podcast
00:25:20
the Art and Science of AI where we talk
00:25:23
about various Topics in understanding
00:25:26
the science of how AI works and and the
00:25:28
Art of using AI to kind of reimagine
00:25:31
your life or your business and we have a
00:25:34
lot of examples we talk about how to
00:25:35
build like automations and and workflows
00:25:38
uh for yourself so yeah if you found
00:25:41
this helpful please check that out and
00:25:43
and I mean just learning from that would
00:25:45
be a very logical first step for folks
00:25:47
who are looking to transition into their
00:25:49
product meion thanks again n appreciate
00:25:51
it yeah for talking to you hey be sure
00:25:54
to check out our website at intentional
00:25:56
product manager.com to see how you can
00:25:59
level up in your career
