The Roadmap to Becoming a Product Builder, with Ankit Shukla

0:00LinkedIn eliminated its Associate Product Manager program in favor of an Associate Product Builder program. But is the Product Builder role real or is it just hype? We analyzed 12 ,500 PM job portions and found that the Product Builder role is very, very real. Who should become a Product Builder? Engineers, Customer Success Managers, Marketers, Salespeople, Analysts, Product Owners, they all have the potential to become the Product Builder with the right preparation work that they need to do. What do these roles pay? In the research, we have been able to find that these roles pay 15-20 % more than their non-AI counterparts in the US and Europe.

0:37And they actually pay more than 30-50 % more in India. This, I believe, is one of the biggest opportunities of the decade. Every PM should pay attention to this trend. If you don't learn these skills, you might get left behind. But if you learn this skill, you can earn more money and even work for better companies that you always wanted. So what's the roadmap to become a product builder? Let me give you the step-by-step that just worked for my students to let XROM AI. Step one is...

1:28Airtable, Speechify, Descript, Magic Patterns, Linear, Dovetail, Arise, and Mobbin. And now, into today's show.

1:39Maybe my most popular podcast guest ever is Ankit Shukla, former senior product manager turned founder of Hello PM. And he messaged me with this new trend. After studying tons of job postings, he's found that there is a new role out there, the product builder. I, for one, am a little bit skeptical. It might be hype. It might not be real. So we're going to go through with Ankit today, is this a real role? How much does this role pay? Who can become this role? He's going to give you the real case studies that have worked for his students to land this role at companies like Meta, Amazon, Google, even Sarvam AI, one of the leading AI companies in India.

2:23And we're not just going to cover how you can land this product builder role. We're going to cover the fundamentals of being a product builder. We're going to go through the power framework to think through how to build things. And we're going to go through a real case study of building a product. So this is an action packed episode. Not a single minute is wasted. And with that, let's get right into it. Ankit, thanks for being back on the podcast. Thanks a lot. Thanks for having me here. I'm always excited to have a conversation with you, Akash. Ankit, a year ago, we created the Blockbuster video, how to become an AI product manager.

2:57It feels like the product builder is becoming the new thing. Here, we're looking at LinkedIn. They got rid of their associate product manager program. They created this associate product builder program. So what I want to know, Ankit, is this product builder role real or is it hype? So Akash, that is actually a billion dollar question. Because I get this question from a lot of people, the forums are filled this kind of question. So I thought that rather than giving my opinion about what I think about this role or whether it is hype or it is value or something else out there, I have actually taken the help of Claude and GPT in order to go through actual job descriptions, like more than 10 ,000 of them, precisely 12 ,500, in order to understand what is happening with the real jobs, not with what the influencers are saying, what people are mentioning on YouTube, what people are mentioning on LinkedIn.

3:51But what do the exact job description of some of the top companies of the world say? And I was able to find that, yes, for more than 30 percent of all the PM jobs, they are asking for some good AI skills. Right. And among these AI skills, they are not only asking for just the tools, which is you knowing any time or you knowing, let's say, some kind of rag or agent thing out there. They also want you to understand the core of what are the problems that should be solved by AI and that should not be solved by AI. So that judgment is what people are paying for. So if you combine that product judgment along with your understanding of AI and the tools that you can use, I think we, all the PMs or people who want to become PMs, they are sitting on a very big opportunity.

4:39Okay, so this role is real. What is a product builder? What makes a product builder different from an FDE, from an AI PM? what I don't understand specifically who is this person what's their background what do they do I tell you so before even talking about any of these terms out there which are mostly jargons let us go ahead and talk about the exact core of the problem out there right we have seen for the longest period of time that as a product manager or as anyone who is a problem solver in the company you are operating in one or three of these stages which is you go ahead and you do the discovery discovery basically means you are understanding the customers doing the market research understanding the data in order to build a roadmap roadmap of what to build right this is what you are going to build or your company is going to build this is the roadmap of the product after you have built the roadmap you are going to detail the instructions and then you are going to work with your development team design team in order to do the delivery What is delivery?

5:42You will give them the specs and then they are going to build the products, right? And after you have built and when they are building it, you have to make sure that you are following up because things can also go, maybe they can be getting delayed and maybe people will not go ahead and ship them. So after the delivery, you are also going to do the third phase which is distribution. Distribution basically means you taking them to the customer so that actually go ahead and pay for the product, they go ahead and adopt the product, right? These are the three things that any product managers have been doing for a longer period of time.

6:12Even if you are working in any other role, your role is directly or indirectly related to one or more of these three fields. Now, what used to happen in the industry is that a product manager will invest a lot of time in discovery. And in discovery, they are actually going ahead and doing a lot of research, looking a lot of data, talking to a lot of people. right and ai has now made them a promise that most of these things you can now do it more efficiently for example rather than going ahead and manually browsing the sites of your competitors you can give them to claude or to catch gpt or maybe you can use this tool called as notebook alum to give it all the content it is going to give you like the almost perfect research report that you can use to make the decision that is one small use case that is going to make you not only make you productive, but make the quality of your decisions maybe even better.

7:06So that is the first reason why it is evolving. I've been using AI tools to build product lately. Cloud Code, Cursor, Lovable, V0, the speed is crazy. Describe a flow and a few seconds later, you have working UI. But often it still doesn't feel like something a product team would ship. You see the same cards, the same rounded angles, that purple gradient, very much giving off the feel that I asked an LLM to build me this. The reason is obvious. The AI can write code, but without strong references, it has no clean way to understand what the best shipped products actually do. That's where the Mobbin MCP comes in.

7:45Mobbin has a massive hand-curated library of real product screens. 621 ,500 plus screens, 142 ,200 plus flows, all from shipped apps across SaaS, FinTech, consumer health, commerce, and productivity. Their MCP server lets your AI tools reference that library directly. Let me show you exactly what I mean. So let's say I'm improving the page for my PM operating system, a product I sell to PMs who want to get up to date on Cloud Code fast. Normally, I'd ask Cloud Code, build me a good page that explains this product to someone and gets them to buy. This is what it builds, and this is where the output gets generic.

8:27It's not terrible, but it has that built with a generic LLM feel. Now instead, I'm going to ask it, use Mobbin to find how shipped SaaS, productivity, and education products structure paid product pages and onboarding flows. Look for patterns around the hero, proof, pricing, and checkout. Do not copy any one app. summarize the patterns and help me redesign this vm os page now you can see the agent is going out and referencing real product screens you can see it's establishing how different products handle the moment concrete promise proof before features pricing that feels like the next step one pattern makes the value prop concrete fast another puts proof before a feature list another makes pricing feel like the next natural step so now as it's redesigning the page it's using references to identify patterns and not copying any one app.

9:16So let's see how Cloud Code did. The first version says basically, here is a PMOS. The new version says what changes for the PMs after they buy it. The proof is higher. The pricing block actually fits. This is closer to how good product teams work. Study shipped apps, understand the pattern, then make something original. And it's not just for generation. You can use Mob and MCP for product audit, PRDs with real examples, or giving your AI agents examples grounded in real software. The point is not to clone anyone's work. It's to study the patterns behind good decisions. Good product builders study good products.

9:52Mobbin MCP gives your AI agent better references to work from. Mobbin MCP is on beta for all paid Mobbin plans. Setup took me under a minute and it works with Cloud Code, Cursor, Lovable, and any other vibe coding tool. If you're building product with AI, check out Mobbin MCP. You get a full year of the paid plan used from my bundle which is just a one-year newsletter subscription or you can check out the description url the bigger reason is the block of the delivery what used to happen was the major block in a product company was mostly the delivery which is because of the nature of coding and building products it used to take a lot of time for developers to build something and because of that there has to be a lot of gatekeeping here which is every idea that you can discover you are not going to put it into delivery because your teams cannot build it and because of which what used to happen was although it was a good move that you are going to play on your judgment but it also led to a different thing which is all the successful product managers in the world will agree to the fact that it is almost impossible for you to 100 % say with confidence that this idea is going to work right and because of which what people used to do was because they have to be confident about their idea ideas they need to get clarity before they are building something they will take some very safe products only to the delivery and because of which they will take some mediocre decisions or maybe some covert decisions right so now the promise of ai is that now you can do delivery faster your engineers who are ai native they can use tools such as cursor such as cloud code in order to do things faster they can test it they can deploy and maybe create things at scale so now this has been reducing and now understand delivery is not only a separate part as a product manager when you are doing testing of your product or when you are doing validation of your idea or whenever you are doing experimentation all of these are maybe interchangeable terms you can also leverage ai in order to do the experiments by yourself you do not need to always go to the engineering team get their bandwidth in order to do the experiments you can do it by yourself and i'm going to show you in this video later on that how you can actually go ahead and do all of these things no matter how the complex the product is you can at least get started in order to test it with the customers.

12:03So how much do these product builder roles pay? Should people really be pursuing these? Yeah, I think that is going to be an interesting question. So I actually did the research on the same as well. And we were able to find that AI PMs and AI related roles in India and across the world are willing to pay a premium of more than 20 % as compared to the traditional counterparts. So if you are a PM, you might be paid X. But if you go ahead and get the AI skills, you might get maybe 1.2x and maybe up to 1.8 or 2x as well. What do those numbers actually look like in absolute terms in US and India? Yeah, so to do the comparison, for example, in the US, we have seen that 195k is the median salary that is crawled across the 12 ,300 jobs.

12:51And then we have been able to see that if you are senior, for example, if you have some years, no matter as a senior, as a traditional PM, as an AI PM, if you are able to get these AI skills, you have the potential to make as much as 250 to 560k depending on the uh let's say depending on the companies that you're working at your own background plus how good you are in terms of delivering the products and in india yes and if i go ahead and go to india and and like just before moving to the india you can also see that across the levels right so if you're just starting out maybe you'll start from a 120k base salary which is not bad if you're just acquiring the ai skills and if once you are into the senior role that is where your judgment and your ai skills truly give the leverage to the company and to your career out there right so it can reach maybe up to 350 340k and total compensation at the top laps can maybe reach 800k as well and we have seen like the recent news that netflix has advertised a ai product manager job of maybe up to 900k as well right and if i go ahead and talk about india you will be able to see that in india these have been the salaries, right?

14:01If you are a fresher looking to get into product management, you know some bit about AI. If you have some good projects, you can make maybe starting salary from maybe 12 to 16 LPA, right? Similarly, for two years experience, it is 22 LPA and maybe some people who are already being PM for more than five years, if you just add those right AI skills, build a strong portfolio in order to showcase your work, I am sure you can get these kind of salaries with the right kind of approach. So there's a real premium to learning this product builder skill set. What's the right framework to thinking about how to be a product builder?

14:36So now everyone in the world knows that if they are able to learn AI, they should be able to add this much needed leverage and maybe see this opportunity. But the issue is that there is so much information everywhere that people, whenever they start, they either get anxious or they get too excited that they go ahead and start going into depth of the wrong things so in order to solve that problem i am giving you a crystal clear framework that will reduce all of this anxiety that will eliminate all of this confusion you just have to follow this i call this the power framework if you go ahead and practice it in your own company i am sure you should be able to confidently talk about ai projects you should be able to build them and then you should be able to mark it down very clearly and very confidently in your resumes and get that leverage that we have just shown you on the screen in terms of the real salary numbers the power framework which is going to help you leverage the ai now understand i am not talking about the adoption of ai many companies are still struggling with the adoption as in their people are not using ai they're not able to find the use cases or maybe they're apprehensive of their job but i'm not going to talk about adoption i'm exactly talking about the advantage which is companies who have actually gone who are willing to adopt ai or who have already adopted ai how they can actually get the ROI from the same.

15:50That is what this framework is all about. Yes, now I'll go ahead and maybe give you a small walkthrough of what happens in the power framework and this framework can be utilized by even if you are an entrepreneur, if you are a small company, bigger company, anyone. If you want to truly leverage the power of AI, for example, your CEO might be saying that everything can be done with AI, but there's a disconnect between what you think as an employee and maybe what your CEO thinks. So this is going to bridge that particular gap, which is this is going to actually give you the measurable ROI. This is the framework that I have built.

16:21The first P, it stands for the possibilities. Now, traditionally in product management, we always started with the problems. But AI is different. AI is different in the case that there were some problems that we were not even thinking about the problems. We were thinking of them as harsh realities or we were not even thinking about solving them because we did not have seen a technology like AI. So starting with problem is good. But here, if we go ahead and always start with the problem in the case of AI, you might not be even looking at the whole picture. So here what we have done is the first step in the power framework stands for possibilities means you should do a very detailed research for your company in order to understand what are the possibilities with AI, which is what are the things that AI can do for example ai can right now go ahead and understand transform and generate test text it can go ahead and look at a lot of summaries of the meetings create look at a lot of meeting transcripts and generate the summaries it can generate code it can generate content so utg is a framework that i use which is understand transform and generate is the three things that ai can do now i would also recommend everyone to go to their competitors look at their industry maybe look at the nearby industry and try to understand what are the different kind of people doing with AI.

17:49So that should open up your mind that yes, these are the possible things that I can go ahead and do with AI. So this is the step number one, understand the possibilities. And every company who's serious about AI, they should create their own database of possibilities by researching across and getting that horizontal exposure among how different companies are leveraging AI. Make sense? Got it. Yes. And one other proxy to look at this as in how companies are leveraging AI is that you can go to the customer stories or testimonial pages of these Frontier AI labs such as Anthropik or DeepSeek or Moonshot or OpenAI and you can understand their customer stories or testimonials.

18:27And then you'll understand that how different people in the world are using AI and that should also give you a lot of other possibilities as well. So that is the first part and after you understand the possibilities when you look at the problems in your company you will start thinking that yes this is how I can go ahead and maybe approach this problem with AI. So this is the first P which stands for possibilities. After possibilities we have the O which stands for opportunities. Now in possibilities we were looking at the world what is possible with AI. Now in the opportunities we go ahead and look at our company.

19:03What are the different opportunities or problems in the company where we can go ahead and actually use AI or maybe even not use AI in order to solve that particular problem. For example if I look at a product manager's job I can break it down into multiple parts. For example whenever I do discovery as a product manager I have to do multiple things. For example in discovery first of all I have to do the research it could be a customer research or a competitive research whenever i am doing the user research i have to draft interview questions and many product managers i have seen make a mistake that they ask very leading questions in the interviews right similarly you are going to build a lot of artifacts as a product manager right and these things you should take a lot of time not the thinking part but the documentation part so now ai can go ahead and help you so these are the opportunities for you you think that right now in order to build a product a product manager has to do the research worth of months and in those months they are going ahead and researching multiple companies talking to multiple people can ai go ahead and reduce that so this is the opportunity part for you so what you need to do is talk to the people in your team understand the whole business structure and try to understand that what are the ways what are the places where if you implement ai you should be able to get some or the other kind of roi and now never start with only one use case so many people make a mistake that they only think at one about one thing and they start implementing it rather than looking at the whole picture so for you as a product manager one skill that is very important is about judgment of what problem to pick in order to solve with AI if you are just taking some small redundant problem which are not very frequently occurring you can just go ahead and build it with AI but you'll not be able to get the ROI out there make sense yeah and after the opportunity part we have the third part now this is where you have to put a lot of attention as a product manager the w stands for the workflow now because you really want to solve the problems you cannot afford to be very high level you cannot just say that i can just go ahead and improve discovery or user interviews with my ai what you need to do is you need to go deeper you need to understand the workflows for example when i talk about research i know that in order to take better decisions i should always make sure that my customer support tickets are being considered i am reading them and i am making sure that they are also giving me some inputs about my roadmap i am looking at all my reviews which are coming on google play or maybe some website like g2.com if i'm a b2b company i should be able to understand them whenever my sprint reviews are happening whenever my leaders are going ahead and conducting meetings about the product i should be able to get all of these inputs in order to decide what to build so now you have to understand the complete workflow as in if this is the opportunity what are people doing right now in order to do their work and you can not only for pm's job you can go ahead and look at it look at any job in your company which people are doing in order to make them productive right so the third part is the workflow and here you have to conduct maybe a lot of internal interviews with your stakeholders to understand what is it that you can go ahead and improve with the help of you here also i have one like two approaches to think about in the workflows you have to look at two parts one is you should look at opportunities in the workflow which are optimization opportunities and second is the innovation opportunities by optimization I mean initially used to spend two three hours every week in order to do this now maybe you will take one or two hours so it is optimizing on time but innovation is something that initially you are not even thinking about this process so I'll give you an example that at Hello PM we keep on doing a lot of experimentation with our content we do a lot of experimentation with how we are delivering the content to the students and we are also doing a lot of experimentation with how the lms is going to look and how the website is going to go ahead and look the landing page right and initially what used to happen was that i'll take the decision or my people will take the decision mostly with the limited empathy that they have because we have a lot of people in the program it is almost impossible to have empathy with everyone so what we have done is in the first call when anyone joins the program we ask them to introduce themselves we have taken about 200 of these calls with all the people out there and then we have gone ahead and feed it into Claude and then we created user persona document from the same so i put like i created a new folder put all the transcript over there and then i asked that can you go ahead and create some personas which are representative of the people who are introducing themselves because they have given all their information after that whenever i take a decision i ask my cloud that i'm looking to take this decision can you go ahead and walk me through can you go ahead and walk that decision through all the personas that are mentioned in this folder and then cloud is able to give me that with which persona it is going to do better and where i should go ahead and taking that particular decision so i now i can go ahead and create empathy at scale with the help of this small system that we have created.

24:01So that is the innovation use case. Basically creating personas from your real transcripts enables you to scale your empathy. You are able to observe that so far we have talked about possibilities, opportunities and workflows but when you talk about AI automation or AI workflow leverage or anything about AI you will observe that a lot of people actually start with either NA10 or Claude or something else out there but if you observe here we have not even taken the name of the tool till here right and that is the and that is something that should be the biggest takeaway from this particular master class right which is if you really want to create ROI please do not start with engineering so each here it starts with engineering which is how can I go ahead and create these workflows in NA10, in make, in Zapier, Google Gems, custom GPT or maybe using agentic AI solutions such as cloud and all right.

25:02Many people make a mistake that they always start with this engineering part and then they try to retrofit everything over them right. But my framework is in the power framework always remember POW comes after comes before the engineering part right. If you do this there are very high likely chances that you will not go ahead and make a mistake of putting your ai slot everywhere if the engineering is coming after the pow very high likely chances that you will not be able to produce ai slot because you are actually going ahead and starting with the right kind of use cases and across 12 000 job description that we have seen we have also observed that rag agentic ai and prompt engineering they were not the number one skill the number one skill was identifying the right use case for ai that is the thing that people are willing to pay you the most for because the engineering part can actually be taken care by exactly that part's a lot easier now and so the real alpha is in the pow yes and i'm going to show you like in just a moment after we cover the engineering and our part i'm also going to show you like one product that we have like just developed just few days before and that's a production great product and how easy it was to go ahead and develop that right so now talking about the engineering part now this is a very interesting part everyone is interested in the same so I'll go ahead and maybe expand this a bit.

26:18The engineering means that now that you have certain kind of use cases you understand the problem you understand the gaps in the workflows you know what you are going to build now the part is how are you going to build this and many people are confused about the right set of tools that they need to use. Somebody talks about cloud code somebody talks about codex somebody talks about google jam somebody talks about anything right so what I'm going to do is I'm going to try to give a simpler framework to understand all of this and maybe put a method to this madness i start with the levels right so for me the level zero is you are going ahead and just prompting your way through you have installed you are going to chat gpt.com or claw.com and then you are going ahead and using their chatbot as they are there right it will give you certain leverage and for many use cases that is good but it will not be able to solve a recurring use case very efficiently for you you are wasting your time out there right by prompting it again and again so the first level is prompting almost i think 100 percent of people are doing that the level one that i give is for creating some reusable prompts which is you can either use something called as google gems and i believe you have a fantastic detailed video about google gems on your channel so people can go ahead and check that out and second is you can also go ahead and create these custom gpts right for example if you want to create a prd you can just create a google gem with all the templates that you have and then you can go ahead and always whenever you want to create a prd you can go to that gem you can give your idea and then it should be able to go ahead and generate the prd for you similarly you can also go ahead and create a resume optimizer so for many people we suggest that you can take a job description you can take your resume create a google gem and then you should be able to iterate your resume as per any job description at scale so the second part is you are taking that prompt like a recurring prompt you are improving it and you are putting it into a reusable product or usable structure or a shell such as google gems or a custom gpt but there is an issue with gems or custom gpt which is that you always have to switch between the windows the context is always switching if you want to create a prd with a gem you have to go to that particular window in order to go ahead and do that you have to click on that gem so for that we have level two which is the skills skills part and the connector part so here codex and clot code comes where you can go ahead and create the skills now the good part with the skills is so the problem with gems was that if you go ahead and try to put a lot of instructions in your gems it is going to run out of context because if you are having a prd skill if you are having a gem to write a prd and also to write your resume there can be very long instruction and it is going to run out of context your model will either hallucinate or it is going to give you the bad output now anthropic has solved this very beautifully with skills what they do is they use something called as a progressive disclosure what actually means is that you can keep on chatting in the same window if you have added those instructions skills are nothing but instructions to do a particular task if you have added those instructions you can just go ahead and claude will identify from your chat like intelligently that whether I need this skill or not.

29:36So your context is safe and the skill is only loaded when it thinks that yes for this use case I should actually go ahead and use a particular skill. So that is the third that is the second level. Now skills are not rocket science this is a trick that I tell everyone who wants to create the skills don't get overwhelmed at them open your cloud do the task that you want to do and when you when you are done with the task when you are happy with the results just ask cloud that please go ahead and create a skill out of the same and then you don't have to go ahead and think much about that workflow and claude is going to go ahead and tell you and after whenever you're using that skill if you learn something you think that you have prompted more like more than the skill you can ask a lot to again update the skill based on what additional problems that you have given that creates a scalable system and that will reduce the fear that you need all the skills ready before you can go ahead and do something yeah and this level is really when i think you start to see some huge ROI, like gems and custom GPT, I feel like they're almost basic at this point.

30:36This is like the real unlock. So when the skills connect with the connector, if I want to show you guys like what are skills and how you can go ahead and add them, yes, you can just go ahead and click on your customize option in your cloud code and understand the skills are not only limited to cloud right now. Every AI tool is supporting the script that has become a de facto standard in the industry. So click on customize you can add the skills as I've told you the best way to create the skills for your work is do the work with Claude and in the end ask it to create a skill that is going to go ahead and make sure that next time you don't have to repeat your instructions and the second part is for the connectors.

31:13Now this is very important for example I can go ahead and connect my gmail my slack and google calendar for a product manager very interesting use cases that I can connect my analytics such as post hog mix panel amplitude and I can set up an automation that every day in the morning at 10 a.m. tell me what has been happening with my product and I can give it certain metrics and it is going to automatically send me either the messages or it can also go ahead and trigger an email for you. Understand this is a big productivity unlock because I have seen many product managers are struggling with their dashboard every day in the morning in order to log in and check what is happening and it is going to give you a lot of data in the natural language so you can go ahead and just share it with your team out there before this break.

31:51Yes, GitHub integration, Gmail, Google Calendar, Slack, Amplitude, whatever your analytics is, Tableau, those all are pretty much essential connectors now, right? Now that we have understood the level two, after level two, let's say if you want more granular control, then you can go to level three. Now, for me, level three is, I would say, wipe coding. if there are few things that let's say you want to build and you are not able to get an out-of-box solution with connectors skills or if you want to give an interface to your users out there where you do not want to go ahead and log into a cloud or something you can do wipe coding and my favorite platform to do wipe coding is actually a free one which is google ai studio where you can go you can go ahead and build almost all the simple products that you can think about and this is going to let's say give you more autonomy and more control over what you are going to do in the other parts there right but you don't have to stop at level number three if you are looking to automate the workflows in your company and if these things are not suiting you or maybe there are some teams where you do not let's say there are some tasks that are going to happen at the back end for example whenever a lead comes to your website or your or your product you want to make sure that you are doing the research on that you are trying to understand how important that lead is and you want to assign it with the right kind of sales people or the telecaller out there so for this maybe the skills connection and everything you do not want to give access to this to your sales person so what you can do is you can simply use an ai workflow tool such as na10 or make right and guys understand these days things have become so simpler that you do not have to even understand that what are the hundred kind of nodes that NA10 or make has because many people get overwhelmed by the same.

33:42These platforms have something called as an AI assistant where you just give it a prompt it is going to create the whole workflow for you. You are going to ask it to test so that you are able to go ahead and build something from scratch even without knowing what exactly these nodes are. But this gives you more control you can go ahead and check the whole process which unfortunately wipe coding does not. Is there a level 5? Yes and this is what I'm going to show you as well right so level 5 is a level where you take the most control this is where the production grade applications are built and this is where the future is going to go right this is what the future is and this is actually going ahead and using tools such as cursor such as MCPs which are able to connect you with maybe AWS or Varsal of the world and then using parallelly with maybe you can use your tool of choice which is clot code or codex and also guys one very important thing many people ask me that clot code is good or codex is good let me tell you very honestly it does not matter for your use case unless you are solving a phd level mathematical problem you have to think about whether i should do this with codex or clot code we have gone ahead because it is our job to teach people and give them some kind of benchmarks we have taken all the common use cases which is building an e-commerce website building a social commerce website building a social network website building a gaming platform we have tested these models like codex like both the platforms codex and cloud code and cursor plus the deep sea harness and all of them were able to behave almost similarly there were some token issues there were some let's say we have to uh give some more prompts to some ai but eventually everyone was able to build a functional website so i think we should end this debate like for 90 percent of the use cases it does not matter you are using cloud code or the codex out there Even the very simple model composer from Grok or Karadar actually goes ahead and does a better job.

35:36But I assume there's even a level six, right? Within this, you could go into loop and graph engineering and you could just keep going down and down this rabbit hole. Yes, yes, yes, yes. But I'll tell you, you should actually stop here. After this, you should understand the power of AI. So now, what is power of AI? understand that you have to understand a mental model in order to go ahead and build any product you need certain kind of code and if AI is able to go ahead and code that it is able to run that code it is able to understand the results so why can't you go ahead and give all the permission to the AI in order to do that why don't you leverage the mind of AI in order not just to plan not just to execute but also to iterate that is where you get into harness design and that is where you get into the agentic AI or maybe a better word would be loop engineering where the AI decides all the three parts which is making sure that it is able to plan, it is able to execute and then it is able to evaluate whatever it has written and if it is right it is okay otherwise it is going to again plan and repeat this right.

36:42Let me now go ahead and maybe let's get out of theory let me go ahead and show you like a real product that we have built right. So let me start with the problem statement. So at Hello PM we have a email list of almost 120k subscribers that we have built in the last three years. Now in order to send these emails we use a service from Amazon which is a popular service which is Amazon simple email service SES and for sending maybe a 1 million emails every month we have to pay them just 100 or 120 dollars. But the problem is that SES is actually an API they don't have an interface where we can go ahead and create the campaigns, send the email and do a lot of things out there.

37:22They do not give us the control, that is only an API. So we have taken a third party platform which enables us to create the campaigns, manage the users, make sure that we are able to track everything and everything. And then the day from where we have started sending 1 million emails or maybe 10 emails per month or 5 emails per month to our users, we are able to understand that our costs are rising. So last month only we are able to see that we have paid almost 550 or 700 dollars to that particular platform over and above the Amazon SES. So then I thought that why don't we go ahead and try to maybe build something of our own, right?

37:57And I took a challenge that although I go ahead and know about maybe Python, I know about using PHP, I know about using Java, but I'm not going to use these languages because I want to try if I can go ahead and build it in something that I don't know and I'm able to manage it at a production level. So I took a challenge that I'm going to use completely modern stack which is Node.js and TriScript and maybe I'm going to deploy it on the AWS using all the native services that they have right and I'm not going to touch the dashboard of the AWS because in AWS you have to figure out which thing is where and then how you are going to deploy it and then how you are going to take the backups and all.

38:35So that is complex so i i thought that maybe i know some of it but now i'm going to assume that i do not know anything so what i did was this is the exact process that i have done right so i started with a very basic documents understand although i have written i have created like the most famous video around how to create prds but i did not follow that i just did it like a common man right so i understood what are the features that i need so i have written this very simple like a very layman term specs specs is add the leads add the fields of the lead add text to the leads and then import the mail blaster or the tools that we are using we can export the data from there and then import into a new system and i have mentioned things in a very simplistic way ab testing segments and all of these things after that i have taken this like at a very very basic level and then i have gone ahead and gave it to chat gpd you can also use i don't think we have to debate about what model to use all the models this is very basic work the model should be able to do this right so i just created a simple prompt I have not used any prompt engineering there I want it to be as much for common man as possible right so help me create a concise but complete straight to the point specs document from the features of an emailing system I am trying to replace it with an in-house tool and I will import leads from the mail basher export right I'll be using plot code to develop this completely give me solid specs tech recommendations which I can give to plot code to build deploy and manage this right and then I have gone ahead and copied this all after that it has gone ahead and created a doc for me but I did not like doc so I asked it to please write it into a markdown file right and explain the features more and then it created a document for me right so now I have a spec document which is well written by this understand initially what you used to do was we used to go ahead and write complete specs that we are sure of and then we'll give it to Claude but right now the level is that you can go ahead and write at high level you can ask Claude or GPT to improve it and then you can read it and maybe improve it it allows you to comment everywhere that you want to right so this is what it has created I have read all of this after that what I have done is I just have gone ahead to my computer created a new folder called as postbox I am naming this tool as postbox I pasted this product there I pasted this complete spec file there and this is what I have done now I am going to show you my whole Claude like chat for this particular product right and this is understand this is just from yesterday right which is like i am not sure even 24 hours ago so look at this how what are the exact prompt that you have used in cloud in order to build something but before i could show you this let me show you what were we able to build right so we wanted to build email platform which is build like a email marketing platform that is built on top of amazon's scs or you can plug and play any kind of email sending API out there right now I had some feature that I had in mind so I have gone ahead and documented them like in a very very simplistic term then I asked GPT in order to expand into the specs and then I created a folder in my computer cloud code was already installed I open cloud code I open that folder with the specs already there then I ask this to cloud code this is what is written in the project understand this project and tell me what's the best for you to implement it at to end feel free to make changes and specs if you like to feel it right and then i have put it into the plan mode and then it has done everything and then it has created a plan for me it asked me a few questions after that it has created then i also asked it that i do not know about aws so help me how can i go ahead and do this so it asked me that you can just go ahead and pull in the mcp out there and then i'll be able to take care of aws as well so i do not have even go to aws it just pulled the mcp out there and then it told me how to get the credentials i just copied them right how to get the credential just go to aws click on identity it will give you the api keys that's it right and then i'll maintain not in the chat but maybe i'll create a folder out there if i'm being a bit quick here understand everything that i have been doing has been instructed by cloud code so if you go ahead and try the same prompts i am sure you should be able to figure out your way out there.

42:43So I have gone ahead and created a file and put it all the details out there and then it started doing this. So it has created this plan. You don't need to read this plan if you want to you can but it has divided the whole plan into nine stages. Right. I gave it approval stages after stages after it has tested but after some period of time like it has tested everything I was also testing along the way and eventually what we have done is I have done the phase two the slices are the phases phase one phase two and eventually I also ask it to go with slice three and then it has gone slice three go with slice four and then eventually look at this now I was fed up it was almost like 20 hours from now so which was already 12 or 1 in the night so I asked it that I'm sleeping now for about six hours Continue doing one slice after the other without waiting for more.

43:44Make sure you test every slice before going to the next one. See you in the morning with the completed work. I can just come and configure all the environment variables. And for people who don't know environment variables, these are basically like secret API keys. Yes, yes, yes, correct. So you cannot just go ahead and give your secrets away in this chat. So Claude is going to tell you how to give you that, right? So if someone does not know about A and B, my recommendation is just go ahead and ask Claude. It is going to tell you what it is, right? because I have approached these projects, project almost as a layman so that I can go ahead and teach it out there, right?

44:14But understand that I tried to make myself as a layman, but I had the experience in software development already. So I had to put a lot of work over there. So after this, I have gone ahead and it worked for a few hours maybe. And then after some hours, it gave me a message, templates were created, tools failed, everything is happening, retry, retry retry nine send commands commands nine done now writing this yes and then i asked it now this is important we understand the most problem with people who are not able to try ai is they are generally anxious that what is ai going to do how am i going to deploy it how am i going to manage this right so i asked it that once everything is done and this i did before i sleep once everything is done create a detailed document for me at deploy chocolate.md with all the instruction to deploy this on production AWS with step-by-step instructions right so I can just read it and then I can go ahead and deploy this after that it has done everything and then this is a message good morning all sizes are implemented tested and committed the local stack is running and everything right so now it has done everything I woke up in the morning I trust I tested everything right now everything was done locally so I asked it that I have installed AWS MCP I have given my credential why don't you go ahead and deploy this live and then it has gone ahead and done multiple things take 15-20 minutes ask me to put all the credentials in the respective file and then as a layman I did not know how to get these credentials right so it also the only word that I knew was that I need to use AWS Amazon Web Services which is where I'm going to deploy for everything else I became like a person who does not know anything right so it gave me all the instructions step by step tell me how tell me step by step how do I these get these grades and then it asked me to log in there and put all the information there right after that I copy pasted the information that I told and it was able to give me the information right and after this once it was working and live then what I did was so now I asked it that what are going to be my cost so it also asked me that yes for your new stack this is going to be your cost so now this where you need to pay some attention that already i was spending 550 dollars and someone else was managing the pain for me now it came up with a stack which is almost 420.

46:37so now this is you need to go ahead and pay some attention and understand if this is actually a correct decision right because i knew already about aws i understood that some reason that claude has taken are not appropriate for example you do not need this large machine for this kind of use case so i asked it to update this can't we do with a smaller ec2 also what's the purpose of fargate right we can do it with EC2 under like within EC2 as well right and after that it has gone ahead and given me a new stack 110 and then I was able to deploy it right and after that understand because this is software there are going to be some errors some errors came it was able to correct it and then I was able to test something and eventually we were able to go ahead and build this and once we have built this this is a better interface than the product that we were using not only in terms of like how it looks but also how it functions right so we have already exported almost all of our leads to this database now and we have tested few campaigns as well and we have flushed some data as well now you can see it has almost all the functionalities which is different leads i can create different kind of segments the templates the campaigns the automations like n8n and zapier and reports and documentations and settings and everything a very important part is the documentation so after i have gone ahead and build the product i also ask claude that let's say if my team wants to operate this can you go ahead and understand all the product once again and create the manual for my team just i can go ahead and hand it over to my team and then i can just hand it over to my team and team should be able to understand how to operate this similarly i have created a documentation for the technical guide so let's say tomorrow i want to hire a engineer who's going to dedicately look at the same i can just give them the documentation which mentions about all the decisions on the text tag and everything even if i want to port it from maybe cloud code to codex i can just give it this information in the code base and then it should be able to understand the same right so now this is what we have built i did not want to show you that like how do you use aws or how do you use cloud code or how do you use let's say prompt these kind of things the purpose of this whole exercise was to prove that even with if you know how to go ahead and give just the instructions in the common way as you talk to the developers or talk to maybe even non-technical people out there if you talk to cloud in that way or codex in that way you should be able to create some very good applications just one thing that i have gone ahead and done some security testing before i could go ahead and test like trust what code has built but in your case if you are building something for production for your customers make sure that you are having some clauses for protecting your data and then you are also having let's say a final green flag from your engine team before you go ahead and deploy this onto production.

49:14So I hope this whole setup is going to give a lot of confidence to people that even if you do not know anything about it, you are only maybe few prompts away or you are just away by few, let's say, instruction that you want to give it to Claude. And then Claude or Codex, it is going to surprise you by the output that it is going to give you, as I was surprised by doing all of these things. And I think the most critical thing is that after you got this initial what I'd call really prototype, there was a lot of bug fixing, going through steps, finding errors. That last 20%, that's where the real work is coming now because Claude can take you 80 % of the way there.

49:57And it basically did most of that overnight while you were sleeping. but you need to apply the last 20%. And in many companies, the PM won't be the one doing that last 20%, right? The PM will create this type of prototype because as we've shown, it's pretty easy to create. Then an engineer developer will pick it up. And that's really the role split I've been seeing most commonly. Is that what you've been seeing as well? Yes, correct. So I think that's a very good insight that the last few percentages, it could be 10 or it could be 20 percent it has became more critical now but understand the last 20 percent you only have to think about when you are knowing that you are building something which is substantial where 80 percent is more important right so many people what they used to do was they would spend a lot of time in order to get something out of the place like in order to get something out in the market just to find that maybe it will not work but now you can go ahead and build something maybe with some rough edges here and there and then you can show it to people and then you'll get some kind of feedback that will go ahead and help you iterate faster in the market because I don't think there is any better mode than the speed of your execution.

51:08And so does every PM need to learn this skill set or are there certain types of PMs where this doesn't apply? Yeah, so I'll tell you. So what happens is I look at the use cases of AI in a PM's life in three ways. Either you can make your team more effective. So internal use cases, optimizing the workflows for them for example we were working with a company called as kist which is ipo bound in india and clear tax and a couple of other fintechs in india you are able to understand let's say when a fintech gives a loan to someone their sales people or their underwriting team has to understand their civil score and do a lot of manual checks in order to get the loan approved and it used to take maybe four five hours from every individual now as a pm who understands that bottleneck understand how AI operates you can make your internal team more efficient so now they have built some kind of let's say small tools where AI can go ahead and help them with maybe 80 % of the work now if they used to take three four hours in order to do like a credit underwriting maybe they are going to take maybe 20 or 30 minutes for one file out there right so that is the first use case which is if you know about executing things or you know about the potential of AI and maybe using some of the tools you can first give a leverage to your internal team which is a lot productivity for your team and achieving the outcomes second is you can go ahead and do a lot of things for you you can increase your own productivity by doing better research running multiple simulations so i believe that simulation is a very important thing for a product manager to do which is you running your decisions across multiple simulations even before sending it to the users so that you are able to understand that what is going to happen what are going to be the second order effects of this particular decision out there right so that is the second part it can make you a lot more productive and the third part which is the ultimate part i do not think every product manager has a use case for the same which is how do you utilize ai in order to serve your customers better now there are also two trees like two branches to this one is you are building an ai native product like a like a cursor or a gamma or a granular of the world where you understand how the llms work you are going to build products on top of the same and then your engineers are going to help you out the second way is that you can do some common things for your users for example every company in the world i believe that they can have a customer support chatbot which is powered by ai or you can have an maybe a rag based model where you can make sure that yes every question that the customer is asking they are being answered from your maybe grounded database out there like maybe an amazon roofers right similarly there are other use cases that you can implement if you are let's say someone who knows how ai works and you are able to leverage that so i do not think it is about that you should or you should not learn ai if you are able to like understand ai is a tool i'm sure if you learn this tool well and it does not take a lot of time we teach everything like whatever we are i speak and all the tools that we have mentioned we promise that you'll be able to learn these tools just within four weeks if you just spend the weekends like it is not very difficult the main promise of ai is that that it has made all of these things democratized and available for everyone right so you just have to put some effort and i'm sure you should be able to unlock that next level of power so the question is not whether you should spend some amount of your time and efforts in order to get maybe an infinite leverage for the future.

54:18So Ankit, people now understand how to build an AI product. They understand the power framework. They understand the opportunity. What's the roadmap to becoming a product builder and landing a product builder job? Yes. So now I am going to give you a set of steps that I have seen work with almost all of my students and very recently someone able was able to go ahead and get a job at the frontier AI lab in India out there called a Sarvam AI they were coming from a very traditional background they were able to follow this framework and get that exact job of an SPM now I am going to give you a step-by-step roadmap that I have seen working with a lot of my students and a lot of successful AI PMs out there now this is step-by-step but it does not mean that it is easy to implement right but if you want if you really want that pie of share from the like a ai opportunity then you should go ahead and better follow this so i'll start with step number zero step number zero is align align means if you do not know what you are getting yourself into if you're not aligned with the role you'll not be able to get it so by alignment i mean go ahead and look at about 25 to 30 job listings for either AI PM roles or look at job listings for PM in AI native companies, right?

55:40This should give you the leverage and also understand one more part that even the traditional companies such as banks and such as the fintech organizations and health tech organizations, they are also having the PM roles where they need people to go ahead learn about AI. So go ahead make a list of about 25 to 30 companies understand what kind of people they want to hire look at their job descriptions very carefully after this you need to go ahead and understand and create a skills map now don't use AI for this look at the job description very carefully this is very important this is where like humans have a leverage right now understand this carefully create the skill map and understand where you can go ahead and add the leverage for example if you are already a business analyst or if you are a product owner or something then you already know how to go ahead and do the stakeholder management you are aware about the software development life cycle because you are the part of the same this is your leverage other skills you have to also learn second is if you are a marketing person or if you are sales person who is looking to move into aipm or pm job your skills are understanding the customers better you understand the distribution channels or maybe you also understand the domain so that is your advantage right your domain or your customer empathy skills similarly if you are an engineer you know about solutions really well you know about technology really well you can brainstorm well plus you also know about hdlc so map down what you already know and then try to understand what can become your strength there is almost no one in this world who has at least couple of years experience and they do not have any strength in two years at least you would have built something so this is the first part which is align yourself and gain some confidence right now the step two is step one is i would say go ahead and acquire the skills now for acquiring the skills i generally ask people to go ahead and list the skills that you have done from step number zero go to chat gpt try to understand the brief of the skills watch some youtube videos so that you are able to acquire some information.

57:46But understanding only information is not enough. Information actually gives you a false sense of confidence that is shattered the moment that you enter the interview. So you don't need information, you actually need knowledge. But how do you convert this information into knowledge? The first part is build something. Which is on my YouTube channel on Akash's YouTube channel, you should be able to find a lot of videos where you should be able to learn these exact tools in order to build something and in this video also in the between I have shown you how to go ahead and build a product. So implement that particular framework.

58:19The second part is talk to people who are already in that role. So go to LinkedIn, search for AI product managers. On the search page click on the filter of people. You should be able to find a lot of people. Click on their profile and send them this message. If you want to take an email, if you want to take a premium, LinkedIn go ahead and take that and send this exact message which is hey this is who I am and I'm willing to learn about AI product management and I find your profile really inspiring if you really found it and then ask them that I want to maybe chat with you for maybe 10 minutes I am also willing to compensate for your time and it is going to really help me when people understand that you are respecting their time in order to compensate them most of the time people will not take money but they'll be willing to help you out right everyone wants to give advice and mentorship to the people who deserve it right and after you have done this you will have a good understanding of these skills right and this part alone like learning building and doing things and reaching out to people can take about one to four months depending upon your speed depending upon where you are coming from after this is a step number two which is reach out reaching out means whenever you see the job descriptions make sure that you are not only finding the jobs on linkedin there are other websites as well actually at least you should be active on five job listing websites if you are from india then insta hire nokri indeed angel.co like well found and linkedin are your places out there reach out to multiple companies and if you really want to take it to the next level apply the step so in the reach out make sure that you are also adding the portfolio the things that you have built because people don't owe you trust you have to make them trust you with the help of the portfolio that you have built and now the ultimate step is step three create a list of 25-30 companies these are like the mid-size companies you are inspired by their work or you want to work in that domain understand those companies well ask yourself the question if i were the product manager if I were the PM at this company what would I do in my first six months from all the knowledge that you have acquired from step number one step number two go ahead and build a deck build a prototype do the research take the help of AI and send it to the decision makers of the company at least two people in a company right you can use a platform such as Apollo or Rocket Reach in order to get their email IDs right they all have let's say some free credits right reach out to them and then go ahead and follow up at least three times in a week before calling it a good right initially four or five people are not going to reply you not because they are busy or not because they don't want to reply but your work is going to be of that level right but as you go ahead and do after four and five always remember learning is course correction as you go ahead and keep on doing and delivering more work and more slides and more prototypes you will be able to understand that you are getting that thing right and when you get that momentum after your fifth six seven reach out you should be able to get responses from these people and that is how you are going to go ahead and build and get into interviews and with few iterations in the interviews you should be also able to crack the interviews because when you are going with your portfolio your work in an interview people actually talk in these interviews about your projects which you should be confident in talking about so if you follow these frameworks i'm again saying this is not easy this is not simple i've just laid down the step that does not mean it is going to be easy but if you follow this i'm sure you should be able to go ahead and get that particular aipm role or any role that you deserve and people keep talking about these interviews i think there's a lot of misinformation out there what interview rounds should you be preparing for yes so i'll go ahead and divide this into three rounds right three kind of questions that you should be expecting the number one is the fitment part which is like the most necessary part out there even if you are like an outstanding candidate out there but if they do not find the fitment they are not going to hire you the fitment means you should look at the job description very carefully understand what shouts in the job description that this candidate is appropriate for that that could be your domain matter understanding your past experience some projects that you have built so for example if you are into fintech if you are already working in fintech and the next company is fintech then they are more likely to take you because you the relevant experience maybe the second step is maybe the second kind of people are let's say i'm working in education tech but i want to work for a fintech company what do i show so i can build some projects in my portfolio that will show to that company that yes i am actually interested and i'm actually knowing about that particular domain these days with the help of ai understanding the domain does not take years you can work on some projects maybe for a few months you should be able to gain maybe 60 70 percent of the confidence or get it out there right so first question is your fitment with the company that is super important does nothing happens uh if you are not able to get that treatment the second kind of questions are the general product management question they are also very important because people want to understand whether you have that judgment that product sense that customer empathy that problem solving ability as a product manager or not right so there they are going to test your product sense product design skills by asking normal questions as in how would you improve our product how would you improve your favorite product how you are going to measure the success of this company like product out there for this also like I have created a detailed playlist on my channel.

1:03:43You can go through all the kinds of things, right? And the third kind of questions which are most particularly important right now are the AI related, which is they are going to ask you that, let's say if you build something with AI, what is the complete end-to-end process? And they are not going to ask you for the happy cases. They are going to ask you for the edge cases. For example, if you have built a rack system as a pet projects, what are the ways in which it can fail? if I give maybe 100 million documents how it is going to work what if I use a different kind of model how you are going to evaluate that so whatever project that you build make sure that you are feeling confident on the same you have tried multiple edge cases and you are confident enough to answer it so first fitment or the behavioral question second the product sense question and third is going to be your project related questions or your AI related question if you do these three things it is going to take a few weeks but I'm sure you'll be feeling a lot more confident and maybe one more tip i would share that please leverage gpt or cloud in order to prepare and simulate for these interview conversations that is also going to help you out a lot like create a project put the job description over there mention about your projects mention your resume and then practice the resume by speaking so that you are not just going ahead and putting everything for that interview round you are practicing it beforehand what are the biggest mistakes people make as they're trying to break into a product builder role yeah i'll tell you that they only think about the builder part they always start with the tools so let's say i want to become a builder so i want to go ahead and start by learning any 10 so any 10 has maybe more than 100 connectors so i'm confused how to do what and what right either i'm going to lose the motivation or i'm going to after learning any 10 i'm going to jump to some other tool then to some other tool right they will get that i would say false sense of progress they are making the progress that they will get the false sense that they are making the progress of learning the tools one after the other but eventually they are only learning the tools and techniques not the right part of product management right so if you really want to become a product builder you need to first understand about the product so work on your fundamentals remember the power framework that the possibilities opportunities and workflow which is the problem space always comes before going ahead and maybe building a solution or getting maybe only knowing about the tools tools are easy you can learn them right now it is a leverage but in the long term it is not going to be leverage if people enjoyed this video where should they find you online for more so two things you can either go ahead and find me on linkedin you can just search for ankhish i'm sure you'll be able to find me you can also go to our youtube channel we have a lot of available like free content available to you that you'll seldom get into the paid courses out there and the third part is that we are also we have recently launched our full-fledged gen ai program for the busy professional.

1:06:24This is particularly for people who do not have a lot of time to learn about Gen AI and still they want to go ahead and leverage that in order to stay relevant, in order to get ahead in their career. That's a sweet, very advanced four-week program where you are going to learn only on the weekends and every week you're actually going to build something. So you can also go ahead and check it out on our website. All right, Ankit. Thank you for being so generous with your knowledge. You guys remember that power framework. Take a look at his case study and now go build something yourself. We'll see you in the next episode.

1:06:52Thank you, Akash. Take care.

1:07:22who else we should interview, and we will put on the best shows we possibly can. Finally, don't forget my offer for the bundle. You get an entire year of my paid newsletter, plus my favorite AI tools, Boltut New, Airtable, Speechify, Descript, Magic Patterns, Linear, Dovetail, Arise, and Mobbin. That's$27 ,000 worth of value for just$150. So check that out at bundle.akashg.com if it interests you,

1:07:49Ankit Shukla: and I can't wait to share our next episodes. Thank you.