Hiral Shah

I have a very simple framework for building 0-1 product - IVC framework Identify: The first step in developing any product or feature is to identify the user's needs. Hence, your goal should be to talk to as many users as you possibly can to understand what they say, do, think, and feel. This also helps you learn who you are solving for and who you are not solving for and create a problem statement 2. Validate Building Conviction by testing Discovery, MVP, market analysis, possible conversion. D ...Read More

There are several things that you can consider mistakes, but I do view them as learning opportunities. Every PM goes through some of these in their career (including myself). Here are some of the common mistakes I have seen PMs make: Not talking to customers to validate the problem: A lot of times I see PMs jumping to solutions for a not well-defined problem. How will you know you have solved the problem when the problem definition itself is not correct? Ignoring customer feedback: Worse than no ...Read More

Getting user feedback is a very important element of building any AI feature. Without the user input, you cannot improve your AI, which means you cannot improve your product. Treat the AI feature similar to any product feature, you need to be nimble, agile and adaptable. There are a number of ways you can gather this feedback and depending on that you can incorporate it in many different ways In feature feedback: Think about this as the thumbs up or down you do on your chatGPT or ask it to re-ge ...Read More

When you are thinking about problem statements, you need to first rephrase the problem as a hypothesis, then try to gather as much as data as possible quantitative (usage patterns, experiment results, etc) and qualitative (user research), analyze competitors trying to solve a similar problem, creating prototypes and lightweight experiments. The most critical and fun for me is customer research. This information can be gathered through surveys, interviews, focus groups, 1-1 discussions or observa ...Read More

Validating the problem is of course a critical step in building a great product. A couple of signals to look for Do you have a clearly articulated problem statement you are trying to solve Did you conduct robust user research to narrow down your problem statement to know what you would be solving? Users' desire to buy and use a product to solve the problem is the best signal you are looking for to keep marching forward Business viability of the problem statement - This reflects the market you ar ...Read More

When thinking about Solutions, think they can come from anywhere - From you, from customers, from cross-functional peers, from industry, competitors, or from your everyday experiences with other products. Hence, it's important to keep you mind open and think of different things where you can get inspiration. When I was at Apple, I would actually monitor how kids used the iPhone (without any manuals) and that was the bar for everybody, how can you make it that simple that no one needs training.  ...Read More

Overall I believe that all PMs can be AI PMs since AI PMs also have to be equally customer obsessed as traditional PMs. However, I do believe AI product management role can be a bit different than a traditional PM role. Some differentiations and questions to think about it?➡ Technical Understanding: Can you explain how a machine learning model works, in layman's terms? Or, how would you handle the situation where the model is giving unpredictable outputs?➡ Data Management: Can you provide an exa ...Read More

While I don't believe there are a lot of different types of AI Product Managers, in some large organizations I see two types of AI Product Managers - 1) application focused and 2) AI foundation focused. It also varies based on the size and maturity of the organization. The Application focused AI PM is thinking a lot about how can you leverage the AI to deliver the best customer value, which customer problems can be solved better if we applied AI and then focus on the adoption of AI. The Foundati ...Read More

There are a couple of different things you have to do and validate that can help demonstrate the revenue potential.  You have to do is TAM (Total Addressable Market) analysis. For this, you are looking for industry reports - how an industry has grown, how spending has grown, back of the envelope calculation in how big the market size is From this, you get into the SAM (Serviceable Available Market), what portion of the TAM you will serve based on your product. You can extrapolate that if you alr ...Read More