How to turn meeting notes into prototypes that your sales team can immediately demo to customers

Now that's a high stakes meeting. They want something in their mind. Most productled or more salesled CEOs are very clear in terms of what they want. >> You wore this AI recording device in your meeting with your CEO. Basically recorded this meeting. Then you're just taking the transcript of that meeting and you are pasting it into chat GBT to generate this product. And at the end of this, you know, I have a fully functional now drag and drop canvas builder that could build a full entire user journey. And the goal here is not to say something is easy. It's more so to are they all aligned and can be more fast, which I think is the next superpower as all these tools come out and what could be possible. >> Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive here on a mission to help you build better with these new tools. Today I have an episode that's both going to inspire product managers and CEOs and maybe strike some fear in the heart of product managers and engineers. I'm speaking to Anjan Paneer Selam, CPTO of Acolyte Health, who is using AI in every stakeholder interaction, giving customers access and free reign to all the prototypes on their road map and solving debates with engineering by building products. This is a fun episode. It tells us a lot about both tools and culture and I think it's a must listen for product engineering and startup executives out there. Let's get to it. This episode is brought to you by Notion. Notion is now your do everything AI tool for work. With new AI meeting notes, enterprise search, and research mode, everyone on your team gets a notetaker, researcher, doc, drafter, brainstormer. Your new AI team is here right where your team already works. I've been a longtime Notion user and have been using the new Notion AI features for the last few weeks. I can't imagine working without them. AI meeting notes are a gamecher. The summaries are accurate and extracting action items is super useful for standups, team meetings, one-on- ones, customer interviews, and yes, podcast prep. Notion's AI meeting notes are now an essential part of my team's workflow. The fastest growing companies like OpenAI, Ramp, Verscell, and Cursor all use Notion to get more done. Try all of Notion's new AI features for free by signing up with your work email at notion.com/howi AI. Anjan, welcome to how I AI. >> Thank you so much, Claire. Very happy to be here. Big fan of everything that you do and also a big user of chat purity. So really thanks for putting it out there and helping a lot of us. Well, what I really like is you and I have something in common, which is we have this fairly rare but more common title CPTO, thinking and caring for the product and engineering organizations. And before we dive into your use cases, I'm curious how that specific point of view has really changed how you think about AI or how you've adopted AI inside your startup. For a long time I was jumping between CTO CPO and eventually I found this kind of um role and I think um it's really big thanks to AI that the roles are now starting to the lines are starting to blur for the roles and it's now one role um and you know early stage startups specifically love the CPTTO because they have one person to go ask everything to there's like no two people in the room now um and I think AI definitely has made it much more bearable and much more easier to manage the responsibilities that come with being being both responsible for the product and the technology side of things and most importantly it cuts down the time required to that's spent in transitioning ideas transitioning information and now directly goes into how things could be made possible. What I really like about this role is that you get rid of this false conflict between product and engineering, but unfortunately you do not get rid of I wouldn't call it a conflict, but the debates and negotiations that happen between the product and engineering team and the CEO. And so I would love to dive into your first uh workflow which is really about how to guide maybe an executive whether they're your CEO or another leader through an idea and really solicit out kind of use cases, user experience, all that stuff in a single meeting using AI. So let's dive into that. >> I work in B2B enterprise applications mostly. So um um a very simple idea that came up which I think um I've built this over the years like the last 17 years in my tech career five different startups I've built it at every startup and the timeline always shortened. First it took like 6 months then it took a few months then a few weeks but now it's like in a matter of 30 minutes to two days we're actually building it and also putting it into production and that's how fast it's become. So there's this one idea that's there's a problem that I love a lot. How can we build a user journey map within the application? So a lot of applications that I work on is where customers want to be able to tailor how the experience gets delivered to users. Normally this just imagine this if we had no logic we have to write down all the logic. A Figma designer has to go and design everything in Figma. Then they have to think through all the possibilities. Next engineering has to understand all the different permutations and combinations. Everything's written on document. impossible to think of how much has to be done before we can even have something functional. So in this case we are in a meeting um multiple stakeholders um and then the conversation comes up can we build like a journey builder within our application. So first step where I always start um I love starting with chat GPT because this kind of has become my brain dump of what I'm thinking through and then it helps me consolidate. Um so start here work through a very simple idea. So, I want to be able to build a prototype here. Very simple explanations, right? Natural language that we're just conversing. There's no complex like here's like a structured PRD or a structured statement. Just a pure brain dump of what everybody's talking. >> Yeah. One thing I'd like to call out here is, as much as I'd like to say, of course, that AI can do a lot of the product job, one thing that experienced product managers are very good at that you've shown you're good at is taking probably an idea from your CEO that's like, I want a journey builder. Like, I want people to be able to like build whatever journey they want. And you've actually given some pretty precise language to that. So there is still a job out there for us despite perhaps my my past um >> my past forecasts of the death of PM. I do think the ability to clearly articulate either for a human partner or AI something a little bit more specific which I think you've done here help you know a single page canvas userf facing tool map out personalized workflows like that's all very specific language that I think a great product manager can translate in very short order. So that's what you're putting into this prompt. And then what are you trying to get out of it? So out of this I want actually a simple structured um prompt that could go into another tool like Lovable Vzero or Magic Patterns any of those. Um and uh the idea here is I'm starting with something and AI does a great job of understanding what else is needed because I'm saying I want it to be a lovable prompt or a vzero prompt. AI understands what else might be needed. So as we go in it starts to summarize everything that's needed automatically picks like a pattern like it's a left side vertical toolbar that could have some and the great thing it does is AI helps normalize every good product managers uh product sense or product feeling into very structured information. So that's what typically differentiates different product managers they have each a different way of explaining how they want it. AI doesn't judge you. It's like okay I get it and I'm going to help you. And I think this is where the biggest shift has been even product managers who initially want to think a lot. My push always to them is just jump in and start typing. Don't think about what anybody's going to think, what AI is going to think because it's very kind, very nice. Just jump in, start putting in. So one prompt later, not even too complex, we have a very nice prompt that I could then use um you know um into lovable orb zero. So from here that's all straight goes to um directly we go into LAR v0ero we put it in and start convers um start building the prototype. One thing I want to also mention here is it's not just limited to um something I type here um I wanted to actually show in this use case I was using the limitless pendant um something I was just experimenting with. This is actually live transcript that's coming from the conversation that we're having in the room. And I could go from this directly into chat GPT as well. So, helps normalize it. Or this could be a copy. >> I have to I have to pause you. I have to pause you. Do you have the Limitless Pendant right now? Do you have it close? >> Yeah, I have. >> Wait, you got to you got to show it. Show it to us. >> Give me one sec. I'm just >> Yeah. Yeah. Um, while you're while you're looking um at it or looking for it, I have to shout out my old pal Dan um who's the CEO and founder of Limitless and we'll be thrilled to see um the pendant in real life. >> Yep. This is my Limitless pendant. Um I was actually one of the first few people to pre-order this. >> Um I I worked with pendants my entire life because I used to work in senior living. So we used to build like the medical alert buttons. So when this form factor came on I'm like I'm trying this and this has been like such a gamecher especially like you know you're sitting in a coffee shop you're talking with you know stakeholders partners colleagues ideas flow right there should be no friction oh let me take a paper and write it down oh let me remember it so this just completely changed the game there so this is like transcript for example from a meeting we start here and then directly go into AI so straightforward and simple so thanks for building Thanks. Thanks, Dan and other friends over at Limitless. I have to say, you did not tell me about the Limitless pendant in our prep. And this has been a how I AI first. So, just to recap for folks that are maybe not watching or don't know what this pendant is. Um, you wore this basically AI recording device in your meeting with your CEO, I'm sure. um ascribing to all applicable disclosure laws about about recording. Of course, of course, of course. Yes. >> And you basically recorded this meeting and then that's streaming into the Limitless AI app. Then you're just taking the transcript of that meeting and you are pasting it into chat GBT to generate this prompt. We totally buried the lead on the like new how I AI workflow here. So again, it'll be interesting to see. I think we've seen a lot of, you know, desktop driven meeting recording apps. Um, it'll be really interesting to see as these like wearables and devices come into the workplace, right, >> how that might shift. And I just had to ask you, you know, why why the pendant? Why a hardware device or or wearable versus like turning on something like granola or another meeting recording kind of um product? >> I think, you know, sometimes you want it to be non-intrusive. I think that's, you know, um I'm I'm a big fan of also the Meta Glasses. I'm waiting for better versions, lighter versions to come out, but this this is such such a non-intrusive device. Has amazing transcription. Um and the great thing is it's not limited by language, too. So, you know, sometimes we have voice recorders. You have to open your phone. You have to set it on the table. Oh, let me make sure I do it. So, that's not always possible. When you're talking, you just want to talk. You're thinking through and you're naturally conversing. So, it does a great that that's one, you know, great reason why I think I'm very bullish about hardware um that's going to carry AI and, you know, it's going to completely change what's possible. >> Okay, quick quick request for folks watching or listening in the comments, if you are also a hardware afficionado or have a use case around that, I would love to hear from you. Um I too love the meta the meta glasses. They are my daily drivers for um headphones and things like that and I would love to hear more about how people are using um hardware on how I AI because this has been a first. Okay. >> Yes. >> So side detour through through recording but you're basically taking these meeting transcripts in the meeting. You're saying great, let's get it to a prototype. And then you're getting it into lovable, for example. And this is an example of what you're getting out of it, which is this nice, beautiful workflow builder with a lefth hand kind of card nav, which we had seen in the prompt, and some interactivity, I suppose. >> Yep. Um, fully interactive. So here now, I started with um, you know, this prompt in uh, Chad GPT. As I thought through this, and again, this is one of the great things, right? when you're doing product and technology, you're constantly thinking of how this idea is going to evolve. So, chat GPT gave me a good starting point. I then b into lovable and as I was pasting and I'm adding few more points there. So, hey, I remembered I, you know, ran into a library called React Flow that does great job at making like a canvas-based builder. So, I put that in here. And I did not expect Lovable to know what React Flow is. There's always this like, oh, maybe it doesn't know. But AI always surprises me here. Somehow they it it knew React flow and exactly that's what it went ahead to implement and you know u one of the things I always recommend is break down your concepts for AI and you'll have a lot more success. So I broke it down first starting with the basic idea and slowly as things progress keep building on it. Um, and at the end of this, you know, I have a fully functional now drag and drop canvas builder that could build a full entire user journey. And this, as I mentioned, I've I've built this so many times in my career. And it has literally been like 17, 18 page documents that fully summarize what's possible. pencil sketches, then then UX designers go put it in Figma, all of that stuff, which which is still okay to do now, but I think nobody wants to spend time reading 17 pages and then arriving at a conclusion. They would rather see. And this this exactly does that. So very easy to do and most importantly talk about. So just imagine going to your engineering team, you're not giving them an 18page document, but you're rather standing, let me show a demo of what I'm thinking. Now we're moving from oh let's spend a week aligning to here's the alignment in less than 30 minutes to an hour. And it's the same with the CEO too. Now that's a high stakes meeting. They want something in their mind and they're very you know u most productled or more salesled CEOs are very clear in terms of what they want. They might not explain it always but now here they are visually seeing this and they might say you know what I want something else here that'll make it possible. So, for example, I don't want too many variables or I want to be able to edit each part of whatever block that you have. And that's the great thing with these prototypes that we generate. Everything is editable. It's no longer just static images that like, okay, let me put it on a board and explain it. It's fully explanatory. It's fully interactive. And then we go from this to first alignment with the stakeholders, which is like the leaders of the business. Everybody's on the page. Let's now move on to the next step. So >> yeah, I I really love this. I want to call out a couple things for folks that are listening or maybe not watching. One is this is really it looks great and Lovable's been a wonderful sponsor of the show, so I have to have to shout them out. We do love them. And I do tend to pick Lovable when I want something to look nice, you know, like it tends to be out of the box, >> you know, it it uses color intelligently. it has it tends to have you know kind of beautiful pretty modern user experience. So I do tend to pick this particular tool for something like this especially where visual design is a differentiator. I think you know sometimes people ask me what what prototyping tool should I pick and you're probably like me it's like well which whichever one I feel like is going to do the job of the day and you know when I need something that uh where UX is maybe a little bit of the differentiator or it's highly interactive like data visualizations or a workflow builder >> I've also found that lovable does quite quite a nice job. So that's one thing I wanted to call out. The second thing is, you know, I I did a little little tour in healthcare once and these rules builders, flow builders are like everybody's built one or they built 10. >> Yeah. >> And what's really hard for a product manager is in the past is you're exactly right. You have to sit there and write bullet points for every piece of logic, every customizable field. You have to go in here and say, "Okay, if I send an SMS, I have to check that the SMS has been like opted in. I can't send too many SMSs in a row." Like, you have to do all this logic. >> It's very hard to document. It's very hard to test. And what I like about prototypes as sort of the source of truth for something that is this complex is you can actually just click through and go, "Oh, you're not supposed to put two SMS components in a row. That goes back into the prototype code." or you know you shouldn't do a delay on a delay and so I think these are particularly effective for highly complex products >> because the alignment on the requirements and the testing becomes much more natural it's very unnatural to read rule sets um it's much more natural to interact with something something like this so I think it's a really effective tool and then the third thing I want to call out that in case people missed because they're going to be very mad at you they're like oh no you've given my CEO the idea one, I can get a prototype in 30 minutes. Two, that I can ship it in two days. But I actually think the thing that you called out was really important, which is >> those are high stakes meetings and they're high stakes products when your CEO is asking for something. >> And the worst thing is you say, "Okay, I'm going to come back here two or three weeks and show it to you." And you show it to them and it's totally wrong. They're like, "No, that is not at all what I wanted. >> Not at all what I was thinking. Um, the team is angry. the CEO is frustrated, no one feels good. And so this is like a cheap path to failure, too, which is like if you get this and CEO is like, she's like, "No, not it." Um, it it cost you what, 15 minutes. It's not a big not a big deal. Move on with your life. So, I think those three things are worth worth noting in this particular workflow. But let's go to what you were talking about next, which is great. We have we have something like this. You know, CEO is going to be like, "When can I have it?" And sales is going to be like, "When can I sell it, right?" >> And a product manager is going to ask their favorite question, which is why? Like, do people actually want this? So, >> exactly. >> Um, how do you do kind of testing? I'm I'm curious what what the next part of your flow is, >> right? So, next part from here is three things. Um, I try to put together some slides. Um, thanks GMA here or gamma. The same prompt that we were just using. Um I start here um with the chat um same chat GPD prompt whatever came out I go and iterate on this. So the next question um and again all of this can be done with a custom GPD tool that you can build for yourself but I think um the new models have gotten good where it understands what your persona is where you're asking from. So we don't even have to go through that effort anymore. I just start like I want to be able to do some market research. Can you now make this a little bit better? I can put it into perplexity or do some research um on it. So that's the next step that I start here try to build a very simple just statement of what we're trying to do what is a little bit more about the actual use cases what the customer types are. So on one side I can use the same prompt go into perplexity this particular use case that I just did. So here one of the great things to do is deep research um which cuts down the time analysis time by like 3 brings it down to 3 minutes from whatever it used to take. Um I think I think the main advantage with a lot of this is it reduces the immediate emotional or cognitive burden on product managers or leaders um in general to focus on what makes strategic value and forget about every other thing that's involved. So if we have to do an analysis, every product manager has their way of what all they want to analyze, put into a competitive matrix or any of this. We get past all of that. That's what deep research for example in this case does for us. We give it some information. Again, as I come in here, I put in some more information. I want to build a market analysis on the following feature I'm working on. Paste the rest of the prompt. It goes and builds everything that's needed as a starting point. So review this. So now your market analysis to a certain extent is done. This is again to build conviction within first the PM or the technology leader that I want I know what I'm working on is of meaningful value and I can monetize it. Very important in an early stage startup even in late stage but I think even more important early stage because if we're not seeing ROI immediately that's more money we're burning building products that don't generate immediate ROI. So once that's done um exported as a PDF or goes into kind of gamma from here build very basic slides uh makes it look pretty. So when we're talking to other PMs, other stakeholders, it's like work is already done that immediately you know attracts them makes them bring to the understanding that we have thought this through which is true which is all happening in our minds but now AI is helping implement it and then very basic slides to be able to talk through um talks about what are competitive advantages strategic benefits and then what the product is supposed to do. >> This episode is brought to you by lovable. If you've ever had an idea for an app, but didn't know where to start, Lovable is for you. Lovable lets you build working apps and websites by simply chatting with AI. Then you can customize it, add automations, and deploy it to a live domain. It's perfect for marketers spinning up tools, product managers prototyping new ideas, or founders launching their next business. Unlike Noode tools, Lovable isn't about static pages. It builds full apps with real functionality. And it's fast. What used to take weeks, months, or even years, you can now do over the weekend. So, if you've been sitting on an idea, now's the time to bring it to life. Get started for free at lovable.dev. That's lovable.dev. One of the things that I find challenging working with AI um exciting and challenging is AI has tends to have an abundance mindset in that it tends to think all my ideas are great and everything is opportunity. And so I'm curious if you've gotten a critical market analysis out of AI or if it's always sort of seeking the data that tells you something is a good idea versus figuring out reasons why it might not work or it's not the right investment. And I'm curious what your experience has been there. >> Yeah. Uh I I mean one of the things always as you said AI is bullish about everything that needs to happen. So I think some follow-ups are critical here. So in Perplexity for example when I'm doing it I always have a follow-up at the end saying can you play devil's advocate and tell me if it's really worth it or can you um do you see really value in any of this? In other words, if you're going to ask AI once more to just make sure it is right, it is going to be accurate then to say compare it to all of these other things that are generated. I think this is the reasons why it might be unique. And a procon analysis is again so easy, right? So you could just build it into your prompt or ask it. And I'll tell you there are more features that AI has helped me say no to because it's all in front of me and the data is readily available which I think is again what is the most critical right? You want to save your time for the ones that are really valuable, really meaningful, but now you're no longer carrying the burden that oh my god, I spent 3 weeks working on this just to say no. It's done in an hour. And now you can feel more, you know, you can more freely say no to things and only focus on the things that are important. So I think it goes back to the earlier point you mentioned to good product sense is still critical. Product managers are still critical. It doesn't replace PMs or what they do. it just makes them to focus on what the outcomes to be rather than the entire process. So that's that's that's where I have seen it be useful and helpful. >> Okay. So in our stakeholder Olympics, you have you know crossed the hurdle of the CEO. We've got the CEO excited. You made a deck. So now all the product managers and executives are you a deck with numbers. That's the thing that makes product managers and executives happy. >> What what's your next stakeholder you go after? um more details, right? So, there's always going to be a junior PM or the engineering leader who's going to ask, "Okay, tell me more. Um I want to know what exactly you mean by this." This is where chat PRD is like extremely great for me because I use chat purity almost like a gate to to the point that you mentioned. Are you sure you want to do this? Are you sure you have everything? That's where I find the tool to be extremely helpful because while chat GPD is there, it's a generic unless you give it like a huge persona overload of what it needs to do. It's very generic. But chat purity on the other side is geared towards a requirements document or a product sense um that needs to be validated. And this is where I use the same prompt, but now rather than chat purity going and saying let me generate everything for you just because you asked me, it goes through a series of validations. Have you thought through this? Have you t thought about what could be the disadvantages if you're building something? Do you have any specific inspirations? This is where I find chat PR specifically helpful. Um I have a template that I've built for myself. Um I call it like the CPTO stack where there is a particular type of uh PRD that my team likes. So I sat with them, discussed with them, came to alignment and then I went forward. Now I validate all the questions here. This is kind of core as or the last step before it's handed over to the engineering counterparts. Now they're going to spend actual mental time thinking through the details. So all of it is done. It goes through a series of discussions and we have now a fully functional PRD. Um easy to read, very small bullet points, no large paragraphs, no large tickets yet. And then it's now ready. And this is one that caught me by surprise. This future ideas and enhancements, right? So this is something I've been dumping into the chats as I go through chat GPT perplexity all of it but chat did a good job of pulling this separately what are feature ideas and enhancements what could be possible almost like a teaser to let your engineering team know hey I'm going to come back with a v2 that's going to be all this too but it's a very subtle hint that gets their you know uh creative juices flowing and I think uh makes makes the job easier >> it's a it's a very strange experience experience as a as a founder or as a product person to have somebody explain your own product back to you. But I will say for folks that have not experienced this product that I made. It really is just a replica of going through a product review with me, my poor my poor product teams, which is I've done so many like what we call be called PRDR. We have a little song. It's like PR PRDR. Um it's very fun. But we have this product requirements design or a product requirements document review meeting. And I just found myself consistently asking like who else is doing this? Well, are there other products that we we like here? What's next? Like is this V0? If this is V 0, what's V1? Vitz B2 and I do think this idea of using AI no matter what your function is as a gate to make sure that you've checked all the boxes of the next step without having to go to your boss or having to go to >> you know your other stakeholders is is a really effective way to sort of bring AI into the loop um in a way that ultimately saves everybody time >> right yep definitely and I think you know the one thing I would love which you're building already is integration So from here it goes now to v 0 which makes the job a lot more easier to keep iterating and refining. But I think as time progresses more tools become integrated. It's going to be a big game changer for everything PMs and CTOs are doing um dayto-day. >> Yeah I'm I'm sorry to the engineers out there but we will be building a Ajira integration to turn all of this into tickets. Um sad sad to say. Okay, so you've gotten again through a couple key stakeholders, your CEO, your PM cohort, your AI CPTO here in chat PRD, you know, let's get to customers. What do we do when we want to actually get this in the hands of customers and validate it? What's your next AIdriven next step? >> Yeah, so customers access teams love this as well. So we built what is almost called like a living product library or demo library of pages especially which are like close to the design language of our actual platform and have these all as individual micro sites that we deployed. So now um either sales teams or customer success teams because it's intuitive there's no you know um there's no places where it's going to fail suddenly or I can't click because the Figma interaction was not done. No challenges of that nature. They have now the flexibility to be able to completely take this and show it to customers, get real-time feedback. So, they're no longer worried about how to navigate. This is a fully interactive prototype. So, in this situation, as soon as I built this, um it was so funny. We had a stakeholder meeting in one meeting room. 30 minutes later, we're with the customer actually demoing this because, you know, they wanted to see it. And what would have taken again like 2 3 months of discussions going back and forth, especially if they're a high stakes customer is now done almost immediately. And it does two things, right? Customers see it, they align and say, you know what, this would be really helpful for me. They're no longer reviewing slides. They're no longer having to just listen to long talks about what a product could do. They're seeing what it's going to be. And if they don't like something, they're right there telling us, you know what, I think something could be different. And I think the outcome of all of this is like extremely fast alignment which in my view is kind of what is super critical now as long as you're aligned with your stakeholders with your customers building anything else is easier is more tangible because there is no longer an uncertaintity of okay let me put it into build will this work or not so that's what we do next take it to customers show them anybody on the team can do it even I could trust my CEO to do it because you know it's a demo library it's restricted to that there's no page he has to go to where it's like suddenly going to give a 404. So all of it is very well bounded and this living demo library keeps growing and you know um it most importantly doesn't put any burden on the engineering team which is what I love about being a CBTO. I can almost do my entire product function without worrying the engineering team. Oh please build this demo two days time one day time. I just want this one button to work. It's all now gone. Well, and so I think this is worth repeating because I think it's both very inspirational and also is going to give a whole bunch of teams a big heart attack. And so the thing that you've done here is you've taken not just this prototype, but basically your library of good ideas, fairly highfidelity prototypes. You've put them in a kind of companywide live demo library. So, anybody has access to these links and then you're like customer se success go ahead like sales go ahead CEOs go ahead and I know that you work for a relatively small company and so that cultural change is a little easier for you but I see so many product teams being like oh my god don't don't tell customers we're working on this or don't show them the Figma it's not going to be like that and I do think it's worth reconsidering how tightly we hold product ideas in the product organization and I do think you're showing a different model which is customers are understanding that things are in prototype phase and they're not live yet. >> Your team is intelligent and capable enough to manage customer expectations around things that may or may not come soon or later and it's overall better for the product. It's overall better for the teams and it's overall better for customers to just see what we're working on versus kind of keep it keep it secret. And so I think the AI side of this is interesting because it becomes cheap to sort of show customers stuff which I have also worked in the past where sales needs a demo of this or a prototype of that and you're scrambling two or three engineers to just try to make something happen. That's not great. So now you've changed the cost of that. But then you've also changed the culture around just being more generous with showing your road map, showing your prototype, showing your things things to customers. And so I think it's something that folks generally should consider is going to become a shift in how product and sales teams work together and I think you're totally leading leading the way here in terms of collaboration and openness. >> Yep. Yep. Yeah. That's totally the product and sales collaboration. You know um I had uh my all my previous sales leaders always said like if only you could show me what's possible I can make this happen. So for the longest time what was friction it could easily now be converted to a partnership and I think that's where AI is playing a big role how can you reduce friction across different teams how can you make the impossible possible and you know >> yeah and one thing I want to say which is probably the fear in the back of product team's minds or engineering team's minds is they say if I give this to sales and a customer likes it I'm going to be asked to build it like I'm going to be stressed because all of a sudden we're going to have demand and I as a product leader I will tell you this this is before AI I have always said wouldn't that be a great problem to have like wouldn't it be a great problem to have that a customer wants to buy something so much for us that there's like demand on our time to build something very specific I'm like the most likely outcome of all of this is a customer looks at it and goes eh like maybe you know like they're like eh kind of and I just I think people are so afraid of preserving product energy and engineering energy that they forget that those are like what I call rich people problems. Like having too many customers ask you for too much product is like the best problem a product manager can have. Yeah. >> And so I love this idea of just like getting in there and creating that problem for yourself which is ultimately a good one >> right I mean I like it's almost like you would rather have this prototype and alignment rather than randomly finding it on a quote that has already been signed and executed. Right? Okay, you're you're talking about the other thing, which is the well, I had to close it for Q1, right? Uh feature feature commit uh tied to to revenue recognition, which you know, as as a good old B2B girl. I have been I have been there. I've been there as well. We've all been there. Okay, great. So, you're not only you as a product manager getting this front of customers, but you are letting your team get this in front of customers. Um, so I think you've you've managed stakeholders. It all sounds great. It sounds lovely to me, but we know there's still there's still conflicts, there's still debates. So tell me a little bit more about how you're breaking deadlocks with with AI. >> Yeah. So one one other situation where um we we we ran into a particular challenge was an idea um again that is where it required almost like a mobile app to be built. Um and the whole idea there was we have this concept could it work and now we have never done it for mobile there is no mobile developer on the team and now the team is stuck engineering is like nope I don't want to even hear about this don't even tell me about this and all we want to do is okay can we validate if it's possible rather than like going hiring that's the first step to do before we even start something so what we did in this situation was um a particular use case again um to kind of also show that there is no limit to what could be possible. Um is where we went into building a mobile app. Um this was an idea where we specifically wanted to be able to capture and just a selfie of a person. And we were working with avatars. So we want to be able to test Cappy, capture them in a happy way, in a sad way, in a normal way. And one of the big challenges we saw was enterprise customers or enterprise laptops always don't have the best webcam. So now how do we bring the solution to the customer with whatever they have rather than shipping expensive kits. So we're like okay mobile phones are always great the cameras are great. Now how do we build something very quick? So this is where again ROR comes into play. Um I think uh they're an underdog in this game or a lot of people are using it. Um but when I found it I was like okay this is like another frontier completely unlocked because what was previously not possible was mobile apps with generative AI. So same prompt right um similar concept started with chat GPT um a discussion in a coffee room where they're like okay what if we bring the mobile experience to the customers and have them just capture an avatar. I'm like, "Sure." And then I go off 10 minutes later, just one prompt here, we're able to now have a fully functional iOS app um or like an Expo app that does only two things, right? This is not a production app again, but it does the main thing of building something that you could test on your phones now and shows what could be possible. And this is where a little bit of sensitiveness is critical, too. Um, which requires understanding what engineering needs. We're not saying engineering here, I built it. I think that's not the right explanation to this or what we're doing here. It's more about it's possible. I think let's look at what is required to take this to production. So now this deadlock where there is a lack of knowledge of what could be possible is suddenly lifted to say here's what could be possible. Could we explore more? Right. >> Okay. >> So I I'm laughing because I and I'm making this face. Usually when I'm excited, I make this face, but I'm making I'm making this face, which is I I love this. This is like Clairvo playbook. No lanes, like do whatever you want. Sure, why don't we ship the CEO's idea? Like, yes, let's show it to like let's give it to sales. And everything you're recommending, I can see the flip side of like a product manager being like, why in the world would you give the CEO a prototype? Why in the world would you tell sales we can do that? And then an engineer be like, great, this guy just like whipped up a mobile app and told me that he can code something that I can't code. And what I want to call out here is you know your intentions and you know some someone like me that's really AI trying to adopt AI like our intentions are good which is there are sort of these like artificial rules and blocks that we in organizations have put into place like you're supposed to argue with the CEO about the road map. You're supposed to never overpromise to sales. You're supposed to like trust that engineering will always tell you what's possible and what's not possible. And the reality is like we're all human. We're limited in cognitive capacity. We have good days. We have bad days. We have experience. We lack experience in places. And there's just so much more access now to overcome those like misunderstandings, get more creative, be more inspired. And so, you know, what I would encourage folks to maybe take away from this or what I'm taking away is one, there's a different way you can show up to your team and it may like it may frazzle them a little bit, but I think on the net, it's pretty inspiring and very generative and you can see how this is going to deliver real value for customers first and then I would say on the other side of the table, let's be gentle, friends, which is like >> yes, >> I think people that are trying these new tools and trying these new technologies you know, like you maybe like me are genuinely builders, like genuinely get excited about creating solutions, genuinely want to solve problems. And so, it's not about threatening people's expertise or, you know, trying to take their role or questioning them. It's really about like, I think this could be pretty cool to build for our customers. I think this would be great for our users and I've found something that maybe can inspire us to do that. And so I think there's like a very important cultural takeaway from this episode that I don't want people to miss. In addition to I got to call out. Um I have not used ROR. So now you can AI prototype mobile apps. Did not know. Now I know. Um to kind of figure out things that are possible with consumer devices. So I I appreciate you bringing sort of both sides, the tool sides and the workflow sides as well as the culture side to to this conversation. >> Yeah, definitely. I think the the one word I would use is um to echo what you're saying is alignment. The goal here is not to say something is easy. It's more so to are we all aligned and can we move fast? Um which I think is a is the next superpower as all these tools come out and what could be possible right and uh to you know all the big unicorns today that are coming out or small teams that are moving extremely fast and I think we're all seeing living proof of that with everything that's going on. So yes, nothing to displace good old production resilient code and processes, but this is all before that. >> Well, and I'll also say I mean annoying PMs have been doing this from the beginning of time, which is I have been I have been guilty of being told no and saying like I set up a an an Excel script that like kind of did the thing that I want or I set up like a zap that is basically the flow I want. Can we and at least now you get code. I mean, you know, you get code and something to click. So, you know, we will forever perpetually as product managers find very annoying ways to ask engineering to build two complicated things and scope creep. It will just happen till the end of time and now we just have more tools. Okay, so let's let's stay on this topic. Let's get to lightning questions. We've been here a while. You know, zooming zooming way out. I think the big takeaway from for me from this conversation is roles are changing and the way companies work is changing. So I'm just curious sort of what are your meta you know predictions on not how is this going to change for an individual product manager but really how are companies going to start to operate differently when they have access to these tools? >> I mean I think companies are going to figure out a process that helps them validate things faster and move faster very much early on. I think whatever used to be the bottleneck of let's take time let's wait for something to come back let's wait for more analysis to be done is going to shrink which I think in in turn is really good because you don't want confusion after you ship a product which is what causes the most issues right a good PM is now stuck managing disconnects rather than what should have gone out to be successful after spending all the time so I think companies are going to evolve to where they're spending more time with these tools up front and then being very sure of what they want as they move into building um alignment is going to be faster. I think these prototypes from a perspective of aligning all the different departments. I think about also customer support, right? Enterprise applications. You want to be able to support your customers. You have a customer support team. Rather than them reading booklets of information and preparing manual guides, they can now have a prototype. You could explain it to them with that. They are then training like other hundreds of team members like, "Oh, this is how we would support if something happens." This is like super valuable for large organizations. They don't have to wait until a product is done to be able to train. Now they can train on the fly and you're no longer using obsolete technology, right? You're always staying cutting edge, which could be a big differentiator for a lot of large companies, too. So, I think that's that's where I see companies evolving alignment fast and then being able to ship uh with a ship with I would say precision after that. >> Okay. I I love it. It's like I'm smiling ear to ear. Let's move faster. Let's build better things. Let's enable, you know, our peers in the company a little earlier, um, have them more prepared and give our customers a better experience. Okay. And then you've shown us nothing but perfect outputs. So, I've seen a perfect lovable prototype. I've seen a perfect complexity analysis, gamma presentation, a chef's kiss, uh, chat PR analysis. I've seen all these beautiful things. >> Please tell me AI sometimes steers you wrong. And so what do you do when AI is not giving you giving you what you want? >> I think one take a break. Um sometimes it's like you just need to take a break and stop, you know, prompting until the end of credits. Um so yeah, I could be wrong. I mean for you know the one demo that I showed, I have at least three demos that did not work um in terms of building when we're building something to perfection. That's where initially I was doing all of this inside vzero or lovable and then I realized okay I'm spending way too much time iterating inside the tool which should not be. So I think naturally found chat GPD to be the first starting point. So when AI doesn't work you'll take a step back and use something else more broader to be patient because um AI can make mistakes. It's still a developing field but the benefits you know far outweigh um the failures. >> Yeah. And we were we were joking a little bit before the show saying that how people answer that question is often a reflection of their parenting strategy. And so I like the idea. Honestly, I need to hear this. Sometimes when you're like kid is not doing what you want, like just walk away is usually is usually the answer. You're probably not going to win the argument with the the 5-year-old. Uh so sometimes you just got to go, we're gonna we're gonna take a little break. And so I'm I'm going to take that into my into my AI strategies as well. Well, this has been such a great episode. I've just really enjoyed the conversation top to bottom. Where can we find you and how can we be helpful? >> Yeah, I'm on LinkedIn um Twitter as well um or X I'm on both platforms. Um LinkedIn is the best place to reach. Um I'll leave my email um here and uh happy to also talk you know um if anybody needs insights on how to advocate for more AI in your product or technology workflows, happy to always support with that. Um but you know I think u we as a community uh need to step together to do this. um and not not overselling your tool, but like the chat purity community or Lenny's community is where I've had very meaningful discussions. You know, I've had a lot of PMs talk about what could be done different and I think uh yeah, that's where you can find me. >> Yeah. Okay. So, find you on LinkedIn and let's all chat about how we managed this transition together. Well, thank you so much. I really appreciate this PMs. This is one that I hope you've listened to the very end. Thank you so much. I'll see you later. >> Thank you. Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube, or even better, leave us a comment with your thoughts. 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