AI and product management | Marily Nika (Meta, Google)

Marily is a computer scientist and an AI Product Leader currently working for Meta’s reality labs, and previously at Google for 8 years. In 2014 she completed a PhD in Machine Learning. She is also an Executive Fellow at Harvard Business School and she has taught numerous courses, actively teaching AI Product Management on Maven and at Harvard. Marily joins us in today's episode to shed light on the role of AI in product management. She shares her insights on how AI is empowering her work, and why she believes that every Product Manager will be an AI Product Manager in the future. We also discuss why PM’s should learn a bit of coding, where they can learn it, and best practices for working with data scientists. Marily shares some insight into building her AI Product Management course and also why she full-heartedly believes you should also create your own course.

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Where to find Marily Nika:

Where to find Lenny:

Referenced:

In this episode, we cover:
(00:00) Marily’s background
(03:20) How Marily stays informed about the latest developments in AI
(04:46) What is overhyped and underhyped in AI right now
(05:59) How Marily uses ChatGPT for work
(08:25) Why product managers will be AI product managers in the future
(11:16) How to get started using AI
(14:12) When not to use AI
(15:47) How much data do you need for AI to work properly?
(17:01) When should companies develop their own AI tools?
(18:35) What an AI model is and how it is trained
(21:25) How Google demonstrated the ability of AI to translate a conversation in real time
(23:02) Why AI will not replace PMs
(23:48) A case for learning to code
(26:21) Where to learn to code
(27:40) How to become a strong AI PM
(29:25) Challenges that AI PMs face
(31:16) Getting leadership on board with investing in AI
(33:10) How PMs will work with data scientists and AI
(35:29) Marily’s AI course
(39:12) AutoML and how a renewable-energy company used it to improve its turbine maintenance procedure
(40:31) How Marily built her course and the modifications she has made
(42:53) Why you should create your own course
(44:08) Lightning round

[MarilyNikaAIPM]

Thank you for having me, Lenny! It was a great conversation (and honor).

[pminpjs]

I'm beyond grateful to have access to invaluable information! Thank you! I work in a small startup where we help students find and apply for scholarships. One of the challenges we needed to overcome was matching students with the right few scholarships instead of just giving an endless list of matches. We're lucky to have a ton of data. We soon discovered that an AI-powered recommender would be the best solution for us. But before we went into this we actually built a pretty simple system based on specific rules and we gave weights to particular criteria. Of course, the recommendations were not great, but we validated that there's a desirability for this solution. Only then we partnered with an amazing external company that specializes in building AI engines to build our recommender since we didn't have the capability to do it in-house. It was a super fun experience. Now the next challenge for us to figure out is how do we keep evolving the recommender and improving it.

[ananthapadmanabhanss]

Excellent insights. thanks!! having a defined problem statement coupled with AI transformation is powerful.

[manager]

5/10 great Qs, answers can be more straightforward & fruitful

[gnvoul]

Thank you for this Lenny. Marily is one of the best PMs out there! Helped me a lot when I was in the job-hunting process!!

[sephypantsu]

As someone who's new to PM and is helping a start up figuring out product centered around AI, this is great information!
Would love to see more content around AI & PM

[ohadivry]

I really liked the model metaphor - 3 year old brain & train process! Spot on!

[siddhantsingh]

Love how Marily explains everything with context. Awesome and v.v productive podcast! Kudos Lenny :)

[animelover]

Thanks for this content, I'm working my way up to find a P.M role and also into AI related.

[urssoz]

I got first prize on an AI Hackathon and we built a pretty solid AI product in a week. I think the availability of AI models and how each model excels in different areas will be crucial to building AI products.
For the MVP you can use a commercially available model to get the financing for research.
I'm not sure if we are at this stage yet, but I think we'll eventually have a pay to fork model on commercially available AI models as this would mitigate the risk of creating a tool and have it shut down due to other teams development.

[nicholasosookra]

What insight! Loved listening to this in the morning.

Question. You mentioned that there would be recordings of your course? Are these available only to the cohort to your course? The course seems like a fantastic opportunity. Thanks!

[rajavijayach]

Quite informational and inspiring. Thank you for sharing the referenced links.

[alirazarizvi-]

Thanks Lenny. This was great. Couldn’t find the link to her course tho.
Excited to be doing the coursera MI course for PMs right now. Seems like things could be on good track 😅

[navilearn]

It's not just about plugging ChatGPT API here or there, or employing a scientist. The software developers needs to get used to the intricacies of the AI models, data processing, data security, systems architecture. These challenges come not only at a financial cost, but can add many months of testing and technical debt pile up.

[almercy]

Are there any other tools/platforms that PMs can leverage? Something more user-friendly than autoML?

[apurvadarsh]

What was the name of the newsletter apart from Tldr? The transcript is not correct I guess for this part of the conversation.

[mndflctzn]

Unbelievable how quickly mental models become outdated in this space. Warp speed.

[jhanncarlose]

the music is so strong, I don't ear his voice

[sharmarajiba]

Didnt understand anything. Your voice kind of drops which makes it very hard to understand.