If This 81 Minute Video Doesn't Make You an AI PM, I'll Delete My Channel

1. AGAakash Gupta0:00

   There are two types of PMs in the world right now, one who is using AI to get better bonuses and hike their salaries, and the other who is stuck in the old way of doing things. This is the only video you need to watch to become the former. What are the steps you need to take to become an AI PM in twenty-twenty five?

2. ASAnkit Shukla0:19

   What you can see on the deck and what we are going to present in the session today, like a power-packed one hour thirty minute session. That is all you need. I'm going to break down all the steps that has helped multiple people get into AI product management in a very structured way. I don't understand why people think it's so difficult to become an AI PM today.

3. AGAakash Gupta0:35

   Ankit Shukla has helped hundreds of people land AI PM jobs in twenty-twenty five. In fact, I don't think there's anyone else in the world who has helped more people get placed this year. And some people ask me, do AI PM jobs even exist? Are they even a big percentage of jobs?

4. ASAnkit Shukla0:51

   There are not a lot of companies which are promoting their jobs as AI product managers. I think every PM job is an AI PM job because even if you are not developing AI product on your own, still you have to use a lot of AI tools in order to make yourself more productive. If you want to learn AI product management, what you should do is look at-

5. AGAakash Gupta1:08

   If the stakeholder management is the part of the job that is really creating the stickiness in the job, you need to make sure you do a good job. You don't want them to say, "Hey, I could just replace Aakash with an AI agent who is creating the PRD for me."

6. ASAnkit Shukla1:21

   If you are building any product, you have to look at it from four angles.

7. AGAakash Gupta1:28

   Ankit, welcome to the podcast.

8. ASAnkit Shukla1:29

   Thanks for having me here, Aakash. It's nice to have me here again. So Aakash, can you tell me how much AI PMs are making in the US?

9. AGAakash Gupta1:35

   So I actually pulled some numbers on this, and in general, what we're seeing is that it depends on the percentile of PM you are. So in the US, there's a huge range. If you're a product manager in the middle of America, you might just be making seventy-five thousand dollars base, but the AI equivalent version of you is making ninety-three thousand dollars base. And if you're in an expensive high cost of living area like San Francisco or Seattle, average product manager is making a hundred and ninety thousand dollars base. The average AI product manager is making two hundred and fifty-four thousand dollars base. So what we're seeing overall is that AI PMs are getting paid way more than regular PMs. And in fact, there are some AI PMs at OpenAI, Anthropic, Meta, that are making millions of dollars. So it is one of the highest paying jobs in tech right now. What about India? What does the s- compensation scene look like for AI PMs there?

10. ASAnkit Shukla2:33

    Yeah, I think that is the same proportion and similar kind of trends that we are seeing in India. So if you just go ahead and look at job descriptions, they might not explicitly say that it's an AI product manager job, but looking at the description and what they are doing, you'll understand that building evaluations, building AI system, or finding how teams can go ahead and build AI capabilities in their product is an integral part of their job. And what we have observed with our data by talking to people and helping the students out is that an average salary of a product manager with, let's say, a couple of years of experience in India is around twenty-five to thirty lakh rupees per annum. But for AI PM, we have seen that skyrocket from about twenty-five to thirty-five to even forty-five to sixty-five lakh rupees. And as you go ahead and get senior, you understand AI product strategy, you understand how to go ahead and understand the whole AI product development life cycle, that can increase much further. So I think the data is correlated.

11. AGAakash Gupta3:19

    That's what I've heard as well. I was working with somebody who was handling a Google AI PM offer, and their total compensation was looking like, including stock options and bonus, like hundred and twenty-five LPA. So it seems like the highest paying jobs are really in the AI PM niche.

12. ASAnkit Shukla3:36

    Yes, yes, yes. Correct. And, and also, I think not only, uh, in the PM, we are also seeing that even for, let's say, other things such as growth roles, which are related to product management, like understanding users, AI engineers, AI operators, like these are the things-- Like, because companies have a lot of leverage that they can get with an AI person, I think there is a lot of leverage that you can get in your career as well.

13. AGAakash Gupta3:56

    And some people ask me, do AI PM jobs even exist? Are they even a big percentage of jobs?

14. ASAnkit Shukla4:01

    Yeah. I'll tell you. So, um, a, a good way to look at it is that if you go ahead and just search for AI product manager jobs, I'm sure you'll not be able to find a lot of jobs. Why? Because there are not a lot of companies which are promoting their jobs as AI product managers. But if you go ahead, look at the job description, the responsibilities, you'll keep on seeing that, yes, now there are words mentioned such as RAG evaluations, iterations, making sure that you have the foundational understanding of LLMs. You are using tools in order to make yourself more productive. So I think every PM job is an AI PM job because even if you are not developing a core product, AI product on your own with your company, still you have to use a lot of AI tools in order to make yourself more productive. So engineers, if they are adding, let's say, ten X of their value with the AI tools available, I think product managers also have a chance to at least do X, say, X their values.

15. AGAakash Gupta4:52

    One hundred percent. It seems like all PMs are eventually gonna become AI PMs, and there's PMs building AI features even for platforms, even for internal tools. So everybody's having to build AI features. Everybody's having to use AI in order to have more high leverage time in their work, and everybody is having to use new tools like AI prototyping. So let's just get into it. Let's start with the AI PDLC. Can you walk us through it?

16. ASAnkit Shukla5:21

    Hmm. Yes. So this is what we are going to cover today. We'll go ahead and first talk about the AI PDLC. This is super important. Understand everything beyond this can go ahead and change, but this is the fundamental of product management. After that, we'll talk about things which are, let's say, more malleable, but they are still important to learn today. So let's go ahead and get started with the most important questions, okay? Whether there is someone called as a traditional PM in this world or not, okay? So unless you are working as a product owner or a program manager or a project manager, if you are working in those role, that's okay. Otherwise, every PM is going to either become an AI PM or you are going to get obsolete. So I generally divide AI PMs into two sections.The first part is the AI-enabled PMs. This is 100% of the PM even right now. If you are not using AI tools such as ChatGPT, Lovable, NotebookLM, in order to, like, say, productize, like make yourself more productive, then you are, you already losing out on that front. The second part, which we are going to most probably talk about today, is the applied AI PMs or AI product PMs. So here also I can divide them into two parts. First part is core AI PM, and second part is applied AI PM. Core AI PMs are people who are working on the deep technology level or the infra level or the model level. Okay, so we divide it into three parts. One is people who are providing the infra, then people who are providing the cloud, then people who are providing the models. So you can understand Google Cloud, OpenAI are some of the companies there. So if you are looking for, let's say, those kind of companies, not at an application level, but at an infra level, then this is the job for you. So people who have been building Google's Vertex AI or Pinecone database or working on the model of GPT, they are core AI PMs. Here, right now, it is necessary to have an AI, ML, or a data science background in order to excel here. But-

17. AGAakash Gupta7:08

    Yeah

18. ASAnkit Shukla7:08

    ... here is where most of the people make a mistake. What they think is that most of the roles of AI PM are Ps, and that is far from reality. If you look at the internet, if you look at, let's say, UPI revolution in India or anything, you'll understand that, yes, there are a small number of players who are going to create the infrastructure, but most of the value can be harvested in the applications, and that is where you need to learn. Okay, so even if you are someone who's coming from some non-tech background, I think with some kind of skilling up, you should be able to become this. So what are applied AI PMs? These are the PMs who are now leveraging this infra in order to go ahead and build these things. To give you an analogy, the National Payment Corporations of India, big body, has put in a lot of money in order to create something called as UPI, United, like, Payments Interface. They have became-- Because of this, they have became, let's say, the, the-- India has become the fastest growing fintech, uh, ecosystem in India, okay? They have done it. That is a government-based company. Now there are a lot of co-unicorns and companies such as Char, such as, uh, Paytm, such as PhonePe, who are built on the top of the same. Now, this is the AI opportunity for you in the same way. So people who are actually building products such as Notion AI, built on top of GPT. Building Grammarly, built on top of other models. Building ChatGPT, which is actually built on top of GPT. And Lovable, which are built on top of other models, and Cursor as well. This is where most of the value is, and these are the things that can definitely be learned, and you should be able to grab this piece of the AI revolution.

19. AGAakash Gupta8:34

    Yes, and I think that people would assume, "Oh, just because I'm not seeing product manager jobs of OpenAI in my area or Anthropic in my area, those are just in San Francisco, that there are no AI PM jobs." But it's this applied AI PM category where there are jobs absolutely everywhere, all over the world, because everybody is having to build AI into their products.

20. ASAnkit Shukla8:59

    Yes. Yes. That is correct. That is correct. So the first step that you need to do is, okay, and this is the absolutely fundamental of product management. So before I could talk on this, I want to talk about one more idea, which is that whenever a new big change comes in the society, all of us are afraid about what is going to change, how do I make myself relevant, and everything is going to fall, uh, out of place. My mental model is that before you ask what is going to change, you should ask what is not going to change, and can I make it my strength? Can I make it my fundamental? For example, if you look at this meme, building an AI product in the end is building a product. So the fundamentals of products are same. The first principle is you have to make sure that you are building something that is helpful for the users. You are building something that is giving the businesses outcome. You should build something so that the world is a better place than it is right now. So if you focus on these fundamentals, then everything else is just a learning. You have to keep on upskilling. Even, let's say, 10 years from now, AI is going to do something else, some new technology will come. But if you focus on the fundamentals and then you keep on layering on the, uh, new top skills on the top of the same, I think you should be able to become more relevant. So that is if you take only one slide from this.

21. AGAakash Gupta10:11

    [chuckles]

22. ASAnkit Shukla10:11

    For people who want to be relevant in the long period of time, this is this particular slide.

23. AGAakash Gupta10:15

    The fundamentals still matter.

24. ASAnkit Shukla10:17

    Right. And, uh, then, uh, the fundamentals, I'll, I'll repeat it again. That is user empathy, ability to understand the user. You should have problem-solving capabilities, and you should be a great stakeholder manager. Right now, your stakeholders may be engineers, designers. In the long term, it could be leaders only or maybe more of your customers and maybe some AI agents, but that's a different game. Right now, you have to go ahead and focus on these three fundamentals. They are almost never going to change in product management.

25. AGAakash Gupta10:42

    And I think this speaks to why AI product management is here to stay.

26. ASAnkit Shukla10:48

    Yeah.

27. AGAakash Gupta10:48

    Because everybody is very afraid, hey, maybe the AI engineer is gonna start doing the product work because he can just have Devin, his AI agent, actually do the coding, and he then has more time. Or maybe the AI designer can just iterate on the PRD themselves. But those people, they really wanna spend all their time just talking to users, just managing stakeholders, just understanding the business value, working with finance and marketing. So I think it's this inherently people aspect that makes the product management role sticky in the future.

28. ASAnkit Shukla11:24

    Yes, correct. And you have got it right that people expect not only from the, uh, angle of your own internal people, because now we are seeing teams getting shorter because time to value has reduced. Uh, teams getting smaller because the time of, uh, getting value has reduced. I think it's more about external stakeholder management. Most important are your customers and your partners. And a recent example is that Perplexity, they have a very short engineering team or a very small engineering team, but now they are focusing on making sure that they are able to partner with multiple people. They have done a partner with Airtel. They have done a partner with multiple universities to make sure that they're able to get the distribution. So most of your time as a product manager was being spent in managing all the engineers, making sure that you are able to prioritize a lot because you have the engineering cost, uh, the engineering bandwidth is very costly. Now you can spend it at places where you actually want to go ahead and spend it.

29. AGAakash Gupta12:13

    100%.

30. ASAnkit Shukla12:14

    Now I'll go ahead and take a moment to explain-What a product development lifecycle looks like. Okay, so this is the fundamental part. No matter what kind of product that you are creating, this most probably will remain the same. The first part is you as a product manager, whenever you are working on any kind of situations, you generally start with some kind of business problem or maybe a strategy, or maybe sometimes business can give you some kind of explicit goals that this is what we need to do. If you are working, if you are a founder yourself, maybe you are starting from the customer problem, but it's a reality, harsh reality of the business systems that you are given some kind of OKRs or some kind of metrics that you need to follow. So that is how the quarterly planning happens. Now, you also will have a lot of, let's say, because you want to understand what is happening in the market, you will do a lot of market research in terms of trends, what are happening. You will also understand what is that your competition is doing. So, for example, Notion AI might have understood-- Notion might have understood that now this new technology, GPT, has came, and people are facing a problem that, uh, uh, they cannot search documents in their natural language, so we can go ahead and add that capability. So they might have got an idea from the trend of AI. So now from market, we have few kind of ideas from our business problems, and then we have few kind of ideas. Similarly, you are going to work with your partners. For example, if you consider Stripe, then Amex, Mastercard, other banks are their partners, and these guys also keep on suggesting, let's say, new ideas to make the product much better. And then you also have your stakeholders. We have seen that, uh, your customer-facing stakeholders, such as your customer support, your marketing team, your sales team, they can bring the fantastic ideas, especially in the B2B environment, because sales team is actually the account management team as well. And the last part that we have seen is where the insights came from is the data. So it can either be secondary data, primary data. You go ahead and understand a lot of things. You understand funnels, cohort, use various kind of tools in order to make sure that you're able to get some insights from data. Data generally works. Understand that if you are a zero to one product, you can do a lot of market research, secondary research, but generally you have to play by your gut. But in case there, there is a mature product, the scene is different. Whenever you are taking the bets, you have to make sure that you are backed by data in order to make sure that leadership and everything is aligned.

Episode duration: 1:20:42