Leveraging Powerful AI Tools for Your Product Roadmap

Introduction and Welcome

Rina Alexin | 00:00-02:59

hi everyone welcome we’re just going to wait for people to come

in hey while people are coming in maybe in the chat they should tell us where they’re from oh yeah let us know where you’re from here I’ll show you it’s done all right hello hello okay Patricia from Utah Marco from Brazil nice har dut is with us har dut from Long Island City New York I know him Maxim we got Nicholas in Miami I know I saw Raleigh yep got Dale from Raleigh here let’s see what else we got here got people from Cy Bulgaria how awesome is that Kansas City

hopefully people from Princeton awesome Concord oh look at this we’re from getting they’re getting them all over the world here yeah I love it I love it this is amazing thanks everybody for joining us this I guess I should say whatever time it is for you but morning afternoon evening even some of some of you out there in Europe and looks like possibly even Asia so welcome uh so today we’re going to be discussing AI Innovation for product managers and how to leverage AI technology to benefit your customers and users my name is Reena alexen I am joining from Miami so I saw there is another person out from Miami here uh not quite so sunny today uh my name again Reena alexen CEO of 280 group I’ve been running the company now for the past almost six years and we are focused on transforming product management teams to be their better versions of themselves uh I am joined by Dean Dean why don’t you give yourself give a quick intro

Dean Peters | 00:00-02:59

yes hello I’m Dean Peters and I’m located right side right outside of Raleigh in a little Township called Apex North Carolina I’ve been with the 280 group for about almost two years now I know it seems feel like longer for some um and uh before that I was 15 years in software engineering and then moved into product management for about 20 years I’ve been across several different Industries many of which gave me opportunity needs to work with early early forms of uh AI in fact I published my first AI algorithm in 1987 which is why uh you know I am older than dirt and I’ve seen and lived through more AI mistakes than many people here and survive the tell the tale um and my job here now is to send the ladder down to the next upcoming generation of product

managers

About 280 Group / Productside and Webinar Housekeeping

Rina Alexin | 03:00-04:59

thanks Dean you want to move on to the next slide so we’re going to do just a quick intro to orient ourselves uh in in this webinar uh first uh for those of you who do not know at 280 group what we consider ourselves is to be an outcom driven Pro uh partner uh we want to help products uh product teams build products that people want to buy and use and the reason why companies work with us is because we offer a holistic solution with our Consulting training and coaching Services we customize and tailor our programs to our clients needs and they are backed by our deep bench of invested experts as you see Dean here uh is one of them uh and we just we love what we do I think that is something that is missing from the slide but we really love what we do next slide please for this webinar just a couple house uh keeping items first uh please ask questions so we want this to be interactive engaging not just Dean and me talking the whole time uh though we can do that uh first I want to answer the most popular question we get is can I watch this later and the answer is yes we will be sharing a link so that you could watch the recording of This webinar after the webcast is over uh I do want to call out that we also want to hear from you so I’ll do a reminder at the end of this uh webinar we want to hear from you what other topics in Ai and product management do you want to learn about next so feel free to to write those in chat or in the Q&A button uh we will take that into advisement as we create more content for our audience here uh but uh also I will be taking a look through sorry I’ll be taking a look through chat throughout this webinar and we want to be answering your questions live so anything that’s top of Mind PE please feel free to ask now figure out why I can’t talk today all right uh after this webinar please connect with us also on LinkedIn we’re going to be sharing a link for you to do that you can also use the QR code our LinkedIn group is a place where you can connect with your peers and share best practices uh we also post our content and material there so please please after this do not be alone uh connect with us on LinkedIn now Dean uh over to you why don’t you introduce the agenda for today

Agenda Overview and Setting Up the HiPPO + GenAI Scenario

Dean Peters | 05:00-08:29

all righty let’s get started all right so we did our introduction and Hello by hey Dale thanks for being on apex we’ll catch up later um we want to talk about ai’s impact on product managers and their products so we’re talking about how does this impact you your role the role of your product and we’re getting get into more of that from that we’re going to talk about building an AI strategy and it’s going to be building it around user empathy so it’s it’s not just picking a technology or you know using hope as a strategy we’re going to show you how to build a strategy based around user empathy for AI we’re going to show you how you can formulate that strategy by learning from analogous playing fields and winning plays if you don’t know what that means you will by the end of this webinar we’re going to show you how to validate and socialize your AI initiatives because even though you may have a great strategy you still got to get it funded you still got to get it backed and then finally we’re going to introduce our new AI for Innovation for product management class um and after that Q&A where you get the stump the chump and ask me questions uh you know and pretty much ask me anything here alrighty let’s set the tone for this a hippo and if you’re not familiar with the term hippo it means highest paid person’s opinion in fact we have a picture here from real life well AI of a PM responding to the highest paid person’s opinion and imagine the hippo walks into your backlog planning and Bellows drop what you’re doing and add generative AI to our product Pronto how are you going to respond so in the chat tell me how you’re going to respond to the hippo stampeding into your backlog and telling you drop stop and roll on generative AI in our backlog tomorrow all right see Bruce has one what are we trying to achieve with the Gen feature I like that thank you Bruce who else has got a come here what why thank you laugh stay out of my Dev team’s backlog I like that one um why why why yeah thank you har nicely done oh let’s see here design thinking why before that oh this is great I have one here from Gilbert what have your customers asked for specifically oh this is great so it looks like we just keep putting them in here because we’re going to collect these um but these are great all right and and and I’m thrilled to see that we’re saying like hold on a second here you know slow your roll before we get into you know the the the uh the the how can we talk a little bit about the what and with that we’re going to take our first poll because I know from talking to a lot of you out there that this is a situation that’s actually happened so this what this poll is asking is how real is our geni obsessed hippo scenario to you did it happen this time last year did you get asked for 2024 planning somebody asked you about it a few weeks ago it hasn’t happened to me yet and here’s one that I like to tell people when I teach dangerous animals are like by the way sometimes in product we are the hippo so pick one do I get to confess that I’ve been the hippo a few we’ve all been the hippo right we’ve all been the hippo do the thing I want we’ve all right why isn’t this done now yeah all right we seem to have a lot of uh answers uh looks like yeah it looks like everybody’s just about experienc this use case uh yeah except for I think 33 people so they hasn’t happened to them yet yeah about about 30 yeah about 30% so about 70% of you have experienced the uh you know the the charge of the uh of the uh AI loving obsessed hippo so nicely done and thanks for answering that that uh poll there alrighty okay let’s move on so with 70% of us up against that wall and 30% in the not yet but maybe category here how do you survive a dis corruptive Innovation or maybe I should say how do we survive and thrive okay and you notice I didn’t say AI I said disruptive innovation …

Poll: How Real Is the “GenAI-Obsessed HiPPO” for You?

Dean Peters | 08:30-11:29

… as I mentioned I’m older than dirt so I’ve seen a few disruptors come along all right um and some of them were sort of meh and some of them were like oh my goodness um as soon as I was actually on a plane coming back uh from Saudi Arabia uh and teaching there when had my about this I was sitting next to a person who was actually a professor teaching Ai and I said what do you think he told me it was a flash in a pan I told him that this was probably an earth you know what do you call an earth cratering uh Paradigm Shift like a meteor hitting the Earth we didn’t degree so for 11 hours we didn’t talk after that but nonetheless give me a second here how has generative AI how has this disruptive in innovation of g i impacted your roles a product manager how has it impacted your product leaders how has it impacted the role of your product how has it impacted your product strategy and how has it impacted the role of your customer because everything is changing on this all right I think we’re seeing a lot of change out in the market I think Reena you had put something up there we’ll talk about that later I think you’ve been posting a little bit there and we’re seeing all sorts of change I know you’ve been having conversations with a lot of customer are like this thing is you know everything’s different now yeah I want to share that I’ve been talking to so I I like to spend as much of my day as possible talking to product leaders and recently I’ve been asking them the question of how is AI going to be changing the role of the product manager and I have had a number of different uh responses some of them believe that this is going to unlock uh new kinds of testing so product managers may be expected to know how to prompt enough to code I think that would was a common answer but in general this has this is coming it’s already here so we need to know how to react to it and respond to it adapt and and and help it help it increase our success in our careers yeah uh absolutely and and so I appreciate you sharing that because I’ve been talking to a lot of people …

Generative AI as Disruptive Innovation – Impact on PMs, Products, and Strategy

Dean Peters | 11:30-14:29

… if you’ve gone to any AI product management agile meetups here in Raleigh here I’ve been bending your ear over the past year on the impact of AI um that’s how I know the hippo scenario the real deal now advice to you is when the hippo does charge in all right and you ask that question how do I even know AI is going to solve the problem and I’ve seen that in the comments here I think um Gilbert had something like that in the questions here and I think we uh uh you know hatal had the same thing in the in the Q&A here my advice to you keep calm and focus on the problem space okay yes that was AI generated um but keep calm and focus on the problem

Keep Calm and Focus on the Problem Space (Pains, Gains, JTBD)

Dean Peters | 14:30-18:29

space and start shaping your strategy start mapping the customers startop mapping the customers pains gains and jobs to be done and when you do that I want you to prioritize on underserved needs so we all know we if we haven’t learned how to do that that means us basically mapping out what is my customer trying to get done what type of job are they trying to get done functionally what sort of social job are they trying to get done to to help Elevate their position what sort of um emotional job are they trying to to get done and and so AI certainly can help with these but first we need to know the customers pains gains and jobs to be done and from that we need to find those opportunities in the form of underserved needs something I can do cheaper something I can do faster something I can do more elegantly once you’ve got those opportunities then you’re in a position and here’s so everybody knows this top two parts not everybody but most people but here’s the part that may be new to you your next step in shaping your AI strategy is picking an AI playing field to explore now what do I mean by a playing field don’t worry I got a slide for that identify analogous plays in the wild or in real life I we’ll be talking about that in a second then rapidly validate your hypothesis so here’s a little plan here on how you can quickly shape an AI strategy when that hppo comes in here so you’re not in a position of hey let me go to the engineers right and you know like I said let me go to the engineers and say hey you know what do we think we do because what are they going to do they’re going to talk about like well let’s let’s think about using Lambda why because you know they’re Engineers they’re thinking about the how not the why not the who all right you’re talking to ux they’re going to talk to you about the interface and this is not casting shade on them this is just suggesting that you’re the it’s your job to get everyone real back into to the customer’s pains gains and jobs to be done so let me talk about those key Playing Fields first …

Shaping an AI Strategy: Underserved Needs and Hypothesis-Driven Discovery

Dean Peters | 18:30-21:59

… first of all understand when we talk about generative AI it is not a thing a singular thing here I think one of the things that especially Upstream as we try to manage up uh when they talk to us about generative AI they think they they may not understand that it is actually this tapestry of several forms of AI that have been woven together so generative AI has at its core a large language model but it also has natural language processing cooked in it also has deep learning cooked in usually has robotics cooked in and reinforced learning all these other areas so and they’re starting to add computer vision to some of these as well so you’re starting to see all these different elements of that now so don’t worry about what that technology is but understand each of those Technologies evolve to solve sets of problems if you look at the problems they were trying to solve and if you look at some of the problems generative AI we’re trying to solve it comes across a couple of vectors here tactical activity versus strategic workflow and optimizing processes or assisting users so in general and clearly not every case fits neatly in the boxes and there may be some other outliers here but in general if you look at the population of AI Solutions out there they are either involving themselves in task enhancements where they improve the efficiency and quality assurance of a process or they’re offering system improvements where they’re offering predictive accuracy or risk mitigation again in the terms of a workflow if you look at other forms of AI they’re dealing with that customer experience so they’re assisting people at a task level with content generation conversational interactions and quite a few other items here that you know we could add to this chart and then finally this is the area that I’ve spent a lot of time with augmented intelligence where it provides collaborative efficiency as so you work as a team and helps you with your decision support …

Defining AI Playing Fields: Task Enhancements, System Improvements, CX, Augmented Intelligence

Dean Peters | 22:00-26:29

So What I suggest to people is as you look at your pains gains and jobs to be done as you think about your opportunity solution here where does it generally land all right does it land somewhere over here in the system improvements quadrant that’s fine it it could be tasked but mostly it’s here just pick one for now and figure out where is that landing and it’s important here’s why it’s important here you pick one of these playing areas to position your product first as an experiment we’re not going to build it yet then we want to learn from analogous plays in real life you know with task enhancement here with the task enhancements and the system improvements and the augmented intelligent the customer experience here you we have these different examples so for example Clara I think Reena you posted on LinkedIn about Clara here on on tasking enhancement here I I think uh yeah I mean this this has just came out uh recently where Clara posted that they uh were able to leverage generative AI to do the work of something like hundreds of support agents in multiple languages and they found a lot of efficiency not just uh in terms of not having as many support staff needed to uh to to address the needs of their Market but uh the questions were answered with less time I think 2 minutes instead of 11 minutes and they had a lower repeat rate so the use case for businesses and for users it’s there it’s just finding the right one to Dean’s Point yeah and and to people who are concerned about replacing jobs my understanding is they’re going to take a portion of those those 700 and turn them into level two support So now you’ve got talented people who are able to to provide a lot more value from their knowledge work now by not having to do with some of the level one calls there’s some other type of these and you see these every day so for example another task type would be just open AI chat GPT uh it could be grammarly business that you use for your spell check here um descript has this wonderful audio product for for uh managing podcast taking out all the ums here optimizely does some things with that uh there’s other products that we use uh for example Expedia has a trip Optimizer that helps us and my point is is not to copy them but to learn from these plays that are similar to your opportunity see what you can learn to bake into your strategy so the reason why I say pick your playing field is because if you try to look at the whole try to boil the whole ocean you’re going to look at so many different uh implementations you’re not going to have time now if you happen to look at in task and realize there’s nothing there for me you can move over to like system improvements or wherever so for example we had the example of a of Amazon with proactive and preemptive order order routing uh and then Channel Partners in fact they’ve got all sorts of AI at the task level here but the point here is that you want to look at systems like that you want to look at systems like uh uh Salesforce Einstein which automates data Discovery uh uh you have products like otter that help you with your you with recording and and what do you call Voice the text …

Learning from Analogous AI Plays (Clara, Grammarly, Expedia, Salesforce, etc.)

Dean Peters | 26:30-30:59

… you have uh some other products out there there that you you may be familiar with as well um I would imagine in fact you know if you can think about some of these products put that in the chat that fit into some of these categories and lloy Hayden did ask in the chat Dean it’s like can it be all four topics I think you know over time yes but I think to Dean’s point right now you don’t want to boil the ocean you want to identify exactly what is the specific use case and and start there especially if you’re at a company that hasn’t used AI before you’re going to have so many learnings along the way and trying to do it all at once is not going to be effective yeah and and here’s I agree with that 100% and I’ll add to that if you try to do all four at once your engineers are going to build you so much complexity you’re not going to be able to scale all right so pick an area first you know pick a playing field pick an area that best suits you you know land and expand now even if you’re an existing product I would suggest find a place to land and expand all right uh otherwise you try boiling the the ocean your engineers will do their best job and it’s not their fault but they are going to build a lot of technical debt right so again you know find the playing area that you want to get started the conversation you don’t have to end the conversation here you might find in your discovery that you’re in the wrong area and that’s fine right learn from winning products here and once you’ve done that you’re going to sit there and start using that the frame your strategy but before we talk about that we got another poll so let’s get that poll loaded up here and see where some of you people are perhaps on where are you positioning your current AI winning play and it could be that you’re not sure or it could be that you got a place for it so Dean we have a question uh somebody posted anonymously where does field service help lie helping with troubleshooting I think that yeah and that’s interesting here um there it could be argumented that it’s a workflow I’m going to say it lands in task enhancement so I’m gonna say it’s in Quad three myself yeah I think it’s pretty similar to the use case we’re talking about with clarina with support inre so yeah I would say yeah I yeah I think yeah so so again it can be either it depends on how you look at the world and how your organization looks at the world um but yeah I I think you know pick that playing field but I I believe with that particular one I I think uh it lands in in Quad 3 again I’m not trying to so how we doing with polls here I think we have a pretty good so I’m going to end it and share the

results nice spread like you’re saying yeah 30% task enhancements and 30% customer experience so so focusing on those two looks like yeah I’m I’m I’m actually really encouraged to see that we have a good mix and that you like I said so you know as you start shaping your strategy here all right so and to your point I love that question can it be all four probably in the future you know downline but at initially or even with an existing product here you pick one of the playing fields let’s say we go with augmented intelligence let’s say we want to do a coaching system for bank tellers where instead of having to compete only on bank loan uh what do you call it um interest rates they can compete on the lifetime value of the loan and so there’s this bank teller who now has AI looking through gobs and gobs and in pounds and pounds and miles and miles of data very rapidly and says here are three loans that are comp comptitive with the interest rate even though you can’t beat them on interest rate you can beat them on lifetime value of the loan you are the human sitting across from the other human here are your three choices and so you know if let’s say I had that was an idea I wanted for a a play all right how would I without having to spend a lot of money because you can burn a lot of money fast how would I validate that idea what is the smallest and fastest way I can validate the idea which means I’ve got to Define some key metrics for Success on my play I’ve got to start with tiny acts of Discovery all right talking to that with my agile class today saying look sometimes you can just go to the customer with a screenshot four different views of the same screen and say which one makes the most sense for the job you’re trying to get done how do you measure incremental impact and how do you adjust based on your learnings this is is why I always tell people in my classes and and the other instructors here as well it’s like building the product is the most expensive way to discover whether you’re on the right path or not so what can we do first you know how can we validate our idea how can we get people to tell us the baby is ugly until until uh until we get it right here and so this is where we avoid uh what do you call it burning through all our Runway fast here I don’t know do you have any other point you wanted to add to this Arena yeah well I actually have a question here uh that’s related to this from hatal is if they launch an AI product and let’s say the first iteration comes up with metrics that are not the best you’re not quite hitting uh where you want to go but then it increases and gets better over time because the the model learns then how do you set expectations in terms of you know within that Loop of improvement uh where he talking about the zero data problem here all right yeah yeah and and that’s a tricky Beast that you know to tame here …

Validating Your AI Play: Metrics, Tiny Acts of Discovery, Avoiding Traps

Dean Peters | 31:00-35:29

… yeah I think you know I I I get your point here on that hat I think what I want to talk about first is we want to make sure that the problem we’re solving for the person is the right thing in other words we have a we have an idea that the model will make it happen can we get some early indicators that were actually answering the right questions for our customer that were actually solving the right problems for them all right we know that we’re going to have a zero data problem here so we are going to have to preach a little bit of patience but do we know at least it’s worth waiting for that data to start showing up so that’s what I would optimize validating on not so much that hey I can’t tell you if the models you know is is pristine models are always going to get updated or at least be should you know model should be in a situation where they can be adjusted based on that type of feedback but even before we build the model you know should we invest in building this model is the model going to answer the right questions for our customers and for our business yeah and Dean I think the point we’re making throughout this presentation is that the the core product management skills whether you’re building a nonaa product or an AI product they’re they’re the same we always need to start with these fundamentals and you need to test as cheaply as possible the only thing maybe I would also add and I think we’re going to get into it later is also understand the context of your organization again if you are building an AI product an organization who’s never done it before uh then there it’s like is your organization ready uh there are probably operationally things that you might need to think about that other uh other teams do not around you know costs and and platforms and talent even like do you have the engineering talent that can help Implement some of this so there’s other um other components here but these are definitely the best best places yeah and and so pick your PL so you you figured out your problem you found your opportunity you’ve picked your plan field that you’re going to experiment with first you found some plays that you know you find are interesting your data scientists will love you for you know framing it that way and then you’re going to validate these ideas all right now here’s some of the things that happen outside of your organization you need to be aware of because nothing kills hope of like a strategy or nothing kills a strategy faster I remember at one organization I came in there in January 3rd of 2020 they told me I had to you know create a a a strategy a vision a road map and get a $5 million budget to build this machine learning model uh to match patients to to um what do you call clinic clinical trials and so by March 10th of 2020 I had this beautiful road map I’d gotten the funding all approved everything we were going to start on St Patrick’s Day we were going to celebrate and kick off on St Patrick on March 17th 2020 all right and this is why I want to talk about external factors and you’ll notice for some of you have been around product manager yes we did shamelessly steal from pastel because what do I need to watch and what do I need to act on the two questions you need to answer regulatory changes changes in administration hey you know Sam Alman knew look what happened to him and think about the the the issues that caused there …

External Factors and Risk: Regulation, Cost, Trust, Bias, Privacy (PESTLE-Style View)

Dean Peters | 35:30-39:59

… um economic issues here the price tag on scaling AI all right if you think you know some of the cost some of the services you’re using now are are expensive here where do you see the bill for on some of this all right what is there a Workforce that can make it happen is your organization again in that position there’s social distrust of AI among some sectors here there’s impact of bias all right that we’ve seen recently in the news here so we have all these factors there’s technological challenges or technological things happening all right there’s a company fa you know Gro gr grq not not the uh Sam not the um uh what do you call it El musk version of this yeah this fa which is a processor that that handles the chat part of the chat GPT at blazing speed here just got about two billion I think in Venture that’s going to be a game changer here discoveries on our our models here how about environmental limited processing materials all right our limited capacity or energy consumption and then of course the people in our compliance office are going to want to make sure you know that you you’re obeying laws that you understand the Nuance between a local and a federal law here and that you understand that you’re including data privacy so make sure these are on your plan because then you’re in a position of socializing your great idea in fact that’s we like to say here is you get to try to tell people you try to you know above you who work what do you call it who work parallel to you and work below you you have to convince them if the Orange is worth the squeeze all right who do I need to get so as you socialize this you need to paint the vision it’s why I say start with the person the Persona tell the story of Marty or Maria or or Cari or whoever that person is at the middle of that and tell them how AI is going to improve their lives make make a case for it it based off these Playing Fields so as you learn from these other plays are those other plays lowering costs are they increasing Revenue are they nourishing the business model are they optimizing the operating model do they address the risks transparency we just talked about that do you have a plan for change management because change is going to come and have you considered using generative AI to help you frame your messaging yeah and I think we have a a bit of a demonstration for this uh I know Aon asked if we would get a chance to look at 280 groups built products so so 280 group we provide training and Consulting Services uh we will share a little bit about our AI course but first Dean’s going to also share uh some ways that you could be using this technology in your DayDay …

Socializing AI Internally: Vision, Outcomes, Business Case, and Change Management

Dean Peters | 40:00-44:59

… yeah so let’s say I’ve got this beautiful strategy you know this I’ve got my strategy framed here um now when we teach and thanks for for that Arena when we teach we actually teach in the using case studies here um if we’re teaching a public class we’ll use a a case study like Pet Care on demand if we’re you doing private we’ll find a case that that relates to your organization so here’s a case study here and we’ve just put a synopsis in a vision in a tagline and a positioning statement and then I answered a few questions so I said hey look just give me five bullet points and I put this into Gemini I put this into chat GPT we make that a little larger and I put this into Claude and so I think I got good results and I’ve created a session context so I want to socialize my ideas to my management using the Amazon working backwards process part of that process is a you is communicating via a press release and Via FAQ but before I can do that I need personas so what have I done I’ve gone ahead and created a personas template that I’m now going to ask Gemini to go ahead and build for a user and buyer and I’m going to ask chat GPT to do the same and I’m going to ask claw to do the same as well all right away we go here let’s see what happens here spinning who who’s going to win all right so there’s my user Persona Sarah so I got a user Persona and there’s my buyer Persona let’s see how and our system oh look at that I hate it when it does that to me well chat GPT you just look bad on a demo all right oh I think this is Claude 3 by the way this is it was definitely worth the 20 bucks a month there yeah definitely doing good here let’s go ahead and regenerate that all right so we see that we got our different personas and now with our personas we can go ahead and generate our FAQ and our press release to do the uh to go ahead and socialize our ideas so let’s go ahead and put this prompt in here for an FAQ n it’s still writing okay that’s what you get for being late all right you will go here put that in here so now it’s going to generate for us a vision of the future there it goes and it’s writing this and if you’re familiar with the Amazon working backwards process you use the press release to communicate the idea of the outcomes to dra to draw a glorious picture of the future both in an exciting press release but also in the form of an FAQ and let’s see it’s doing that good one there and now I can put this in here so chat GPT will do that and so you can see that now we’re getting an FAQ and it’s following this template here you’ll notice I wrote it in

markdown and that way I have consistent formatting and I make so for example my FAQ I make sure all my bases are covered general information key stakeholders potential

customers sales and marketing engineering yeah so Dean we’re getting a couple questions right now in terms of your process for prompting uh so I don’t think we’re going to be able to get to the details here but I’m not gonna be able to get to that so we probably need to have another conver but that maybe we need to have that conversation in another webinar yeah I think I think we definitely can uh if you could give a high level what are some maybe just three bullet Point best practices to consider when you’re writing prompts sure so I like writing them in markdown okay that gives hierarchy I like going ahead and it’s by using markdown I give it a Hier if you’ll notice I’ve got these brackets here chat GPT Gemini and Claude all interpret those as fill in the blanks and you’ll notice I started in a context block I give it all the templating and then I put the question at the end here after and then just ask my questions notice what I how I ask those questions based on the current session content given the business outcome you notice I gave it the business outcome of a million ARR given the product outcome of 10,000 people service and thinking like a product manager please provide me a following a future thinking so you can see how I struct and all my prompts are structured like this so hopefully that gives us a little bit of Clarity on on that process there thank you um Bruce does ask how does an AI generated prf AQ compared to a human created one is it logical so here yeah so here’s here’s what I teach in my classes here are any of my you know when it comes to this you know comes to the information we generate here is it is this information you know good enough to hand to my manager or present no absolutely not do not use any of these tools as a source of Truth they are ready for you to have a conversation with your team so if I were to generate a press release I would go to some of the other product managers on my team saying hey look I generated it based off of this context tell me if this thing is you know on target where it needs help where we need to modify it where we think there might be some hallucinations we need to correct so don’t use it for a source of truth remember I said scaffolding and drafting were the words I used so this is creating a scaffolding of of of the U the personas and is creating a draft of the P of the uh press release and of the FAQ it means you have to have human conversations afterwards right so and you’ll hear me preach that you know ad nauseum I have here from Zev Abrams in the chat another trick is to have the AI criticize itself uh I I have seen here’s a here’s a here’s a human con have have Claude criticize what chat GPT did and then have Gemini criticize what what Claude did you know and just have them argue among themselves so in using these tools Dean I know somebody also asked have you found any one of them to be more consistent in giving you uh good outputs depends on which day and how much how much they’ve updated I I’ve had some days where I’ve walked in and chat GPT is just well sub suboptimal but and but here’s my point again um it’s it’s less about that the reason why I got good results with the prompts was because I went ahead and gave told it what the business outcomes were what the product outcomes were what the human element was the pains gains and J be done the opportunity work and then I asked it draw me personas then I asked it you know so it doesn’t really matter I could have just said draw me a Persona the fact that I gave it that context of the problem I’m trying to solve for my business and my business strategy that was more important than how I format The

Prompt right yeah we’re gonna get to more questions uh at the end so please continue to Prov question I yeah Q&A at the end and like I said that that’s where you you get to go all right so let me ask you this question here a hippo walks into your backlog planning and Bellows drop what you’re doing and add generative AI to our product Pronto how do you respond do you keep calm and focus on the problem space do you feel the customers pains gains and jobs to be done do you stake out an AI playing field to start exploring do you borrow ideas from winning plays within those Playing Fields do you prepare for the unknown unknowns by using a little pastel analysis do you socialize the outcomes using a blueprint like Amazon working back backwards and then finally then finally do you build on Tiny bets for big wins because the next step is how do I build small you know how do I focus on less to to deliver more and how do I uh build in a way where I don’t break the bank or either through complex either through cost or through complexity

Demo: Using ChatGPT, Gemini, and Claude for Personas, PR/FAQ, and Messaging Scaffolding

Rina Alexin & Dean Peters | 45:00-51:59

here and something else that you could do of course we mentioned it at the beginning but today we are also launching our new course on AI Innovation for product managers this has been so excited about this oh so yes uh I I’m so excited I know Dean is Dean has been absolutely instrumental as one of the authors of this course as part of this course you’ve kind of experienced a little bit about the some of the magic and some of the questions we’re trying to answer in the course but we offer a framework for you to assess different AI plays you get to practice with that uh you get to learn from different use cases there is some prompt engineering as well and at the end of the day you have a workbook and a plan to present to your leadership on how do you want to go about in incorporating AI into your strategy is it the right strategy and how do you plan to experiment and validate uh so that you can provide the most benefits to your customers your users and your business so really excited about today our first our first cohort is launched on April 1st and 2nd I think we have Roger teaching it uh I know we have several other uh classes already scheduled so if you go on our website or use the QR code um that will direct you there uh yeah now we can go to I think our final poll yes our final poll starting today starting today what will you do differently let’s Lock and Load that poll and see what happens what will we do differently starting today by the way yeah we’ll be able to answer some questions here along the way yeah uh so is our poll

Poll: What Will You Do Differently After This Webinar?

Rina Alexin & Dean Peters | 52:00-54:29

up I think it’s coming here it is here it is uh starting today what will you do differently and then after the poll you you can ask me all sorts of crazy questions we got a lot Dean I know so are stay calm and focus on the problems pick a playing field learn from the anal analogous examples in real life keep an eye out for external influences or consider signing up for our AI course where you can dive deeper into all of these topics okay I think we have a quite a number of people who have answered I’m going to end the poll and about 43% are going to stay calm and focus on the customer problems thank you I I feel I can sleep tonight I can our job we we have you know Mission successful yeah so uh I’m going to go through some of the questions that people have asked uh I also want to encourage you again if there are topics or um just think things that you want to learn whether it’s in AI or whether it’s in product management uh please feel free to also send send a a comment or a question uh we really want to hear from you what you want to learn most all right so first question from Christine similar to something that you showed with the press release uh is how can we use AI to determine underserved needs that we have not yet discovered so yeah I think there’s some interesting ways to that here one of the things I didn’t show is sometimes I even before I go to chat GPT before I go to gemini or before I go to Claude I’ll actually go to Bing because it’s real time and I’ll start asking you questions about the market I’ll start asking you saying hey using the best US Census Data available can you tell me I’ll say hey using data on some type of uh uh industry let’s say you know Pizza Channel Partners here um you what can you can you tell me about how many pizzas are sold within a given area or how many pets you know are how many veterinary clinics do we have in a particular demographic so we can use all these other tools that we can then take what they provided and then feed those into other tools to go ahead and say like oh by the way here’s the US population or here’s the population in the EU here’s the number of of whatever so now you’re starting to shape your total available market and you can start asking some questions based off of that data so there are ways of doing that there’s all sorts of open data out there as well that you can explore if you’re trying to solve particular problems in the in the areas of workflow uh there’s all sorts of data that that’s available here and you could take a tool like Claude and actually just throw at it you know hundreds of pages of data uh and ask it to do that I think with the GPT you can use its um it’s a code interpreter and’ll actually give you I think an R notebook basically a a you know you know playback so it can help you do some data analysis so you know what are some ways of doing it the same way you do it in real life just faster and using more data available to you so we’re not changing you know what you do we’re just amplifying and augmenting what you should have been doing all along yeah I think the point here the key Point here really is that do you have the data that Maps out what you’re trying to ask AI to to solve for you right because if you just ask it directly I don’t think it’s going to get you to what you’re you’re looking for yeah I I I I so much of it I you know I did a fun little you know custom GPT back on Christmas to generate Hallmark movies and I went and collected all sorts of movie data and I collected data about oh what was it oh uh story plot lines and all sorts of story all sorts of stuff about you know Hallmark movies and movie generation there and so by the end of the day you could use that custom GPT to go ahead and create a script uh you know or movie poster or some other things based off of actual data of actual film titles and synopsises that they had so again even from something as silly as that I still had to go and grab data and do what I do normally in product thanks Dean so we have a question here from Gilbert who I hear is one of your former students Gilbert Hammer uh he’s asking how granular do you think a product manager owner should get into the core AI technology and is there a delineation between the product manager and AI technologist yeah it’s an interesting question here …

Introducing the “AI Innovation for Product Managers” Course

Dean Peters & Rina Alexin | 54:30-57:29

… uh in fact uh you our friend Jason Knight was were joking about that over the term AI product manager here I actually think that we all need to become product managers who are AI aware that’s why in our CL I talked today about very quickly about the different layers of tapestry that is is AI um we do need to become AI literate I don’t think we need to become look our job here is to help people you know is that is to basically create Pro delightful products that are differentiated and provide a high amount of return for both the customer and the business here and that’s what we need to hand off to our teams and let them own the how they’re trust me they’re using AI to help them on delivery of the how all right I’m seeing a lot of Docker scripts and a lot of other scripts and a lot of other things happening that are all generated so they’re going to be owning the how with some J AI assist I think a lot of things we do administratively that tire us out those are going to go away I would imagine tools like Ado and Jer are going to have um uh what would you call it the ability just to put in a couple sentences and boom out comes your user story that you you modify I think one thing on the horizon we’re not aware of is the rise of AI agents here all right autonomous agents where it won’t be just at a task level I mean user stories you know looking at data here that’s at a task level but these autonomous agents are going to be able to actually look at entire workflows so what if I wanted to look at an entire marketing campaign for a pharmaceutical company end to endend I could take that agent and tell it through you know I’d have still have to be the human mapping out the steps but then let it walk through the steps and basically start creating for me scenarios that we could gra uh create synthetic data from and learn from yeah uh so I I just want to add really quickly because Gilbert did ask in terms of the value proposition of our course uh we we do go into how to use some of the technology like I said there is just there is a bit of prompting because it is it’s it’s needed you do need to learn how to you know best practices of prompts I know Dean just went over high level some of them uh but in terms of what product managers I think are going to be expected to do Dean said it best you have to become AI literate you have to understand the the possibilities offered and also the risks offered by this technology ology but in the end the company’s going to be looking to the product manager to help them make decisions about where does this fit and what use cases and so that’s what our course is really going to help people do is think about what problems there are that are better fit for the use case of of using AI as a as a solution so that’s what the course really does is using core product management skills and then marrying it with the possibility of AI uh I’m going to move on because I think I want to talk about this a little bit Bruce asked I don’t think we’re going to five top AI Trends but uh you mentioned autonomous agents I think that absolutely is going to be a trend I think another Trend you kind of brought it up and I’ll I’ll I’ll let you see another one but uh I mentioned it earlier I think there’s going to be expectation of potentially doing some early prototypes without engineerings uh Talent yeah so I think that’s going to so in terms of learning not just how to prompt but how to promp to code and and use it to create MVPs that you could then go out and share with real human customers I would say real human customers um that’s probably going to be expected more of product yeah I I agree with that I think there’s going to be area one area to keep an eye on is on the processors that’s going to be able to help change it I think we need to keep an eye on some of the cloud providers right there’s being some interesting moves there I mean think about it a lot those of you who are in finance and those you in Pharma or those who in healthcare you have a lot of restrictions with regards to legislation coming up here um and so I could see where a shop would want to use a Azure as its interface into open AR into its interface or where companies don’t want to get you know they don’t want to get locked down to one particular model they might want to have different models they can go to or Le and so you know write their code in way against those servic in such a way where they’re not locked in so if something happens to Sam Alman and he gets fired again you know you’re not in a panic because you can switch over here so I think there there’s that uh area that we’re seeing in AI uh some things being moved as well so uh there’s a lot of uh more questions thanks so much I see there’s a lot going on in chat of people also sharing resources that’s awesome I think we will post uh on our LinkedIn as well just there’s a lot of different AI resources out there for you to start learning so we plan to do that as well …

Q&A: Underserved Needs, AI Depth for PMs, Trends, ROI, and PM “Laziness” Concerns

Rina Alexin & Dean Peters | 57:30-1:04:59

… uh Lorden asked when presenting the use case of implement of implementing AI what type of quantitative data should they present to provide the you know why this decision might be good for us I think some of it’s going to depend on the audience all right but at some point you need to be able to speak uh you know at some level of what does my market look like here you know how much how much will will how many people will find it valuable enough that they’re going to take money out of their wallets and put money into ours so we can afford to do this and keep and keep growing and and I that I know that sounds a little utilitarian here but at the end of the day we are running businesses here that’s part of our job as strategic product managers here so I think some of the data needs to be able while some of the you know I don’t know if a Chief Financial Officer is going to get really uh uh you know all all excited and and and happy by looking at various performance ratings you the engineering team will appreciate that for sure but that’s not our job our job is to sit there and let the CEO and the CFO and the CPO understand like look we’re going to invest this much into the into building this product we feel it’s going to touch the lives and behaviors of this many people and this is the return we’ll get so we can keep serving these people yeah so it’s like any other decision you need to have a framework that you bring to an executive uh so completely agree not going to be impressed they’re not going to be impressed with the technology yeah I mean I mean okay you might find that in some startups where they you know they come in engineer first but very quickly when they see their Runway burning up and I actually had a conversation with say you I do all these meetups here and I was talking to a meetup on a Meetup where they they’re actually showing a a nent product for beer brewers and I they were talking at the Meetup about all the technology their building I’m like do you have have you at least found enough Channel people you know involved who would buy this do you you feel like I like well we’re going to show them once we have it built four months later they’re out of Runway okay what I mean by out of money that means they out of you know they have no more money uh and they all have to go find different jobs and so so again it was just sort of you know yeah uh one of those situations where you know you you they fell in love with the pro you know the they fell in love with the solution and not the problem and Dean whenever somebody comes to me with an idea I always want to know you know what’s what’s the potential here how much is it going to cost and what’s the confidence level of both and how do you know I mean is the orange worth the squeeze yes you know all right all right you we have we have time for one more question and then uh we’ll wrap up so Bruce has asked this a few times so I’m gonna I’m gonna give him some air time uh you know it’s similar to if we’re going to let AI do all of the thinking for us is that that’s a you know are are PMS going to be lazy are they going to continue to be valuable uh or how do you avoid it because I think in the the purpose of the prfq is for the product manager to help them crystallize their thoughts I mean you do a lot of thinking when writing so I I understand the question yeah so I think first of all let’s look at some mat has some studies out and I think y had some studies there’s a few studies that come out that say that generative AI is upleveling the C and the B players up to a minus players so we see there’s already data that tells us that they are getting uplevel will it stop I would imagine some people are going to just you know use it and put it out there and glide by we it’s G to it it already it’s already happening at other levels okay so that’s going to happen but what what we’re really going to see is the rise of these of strategic product managers and we’re we’re going to get more pressure in our field to be able to sit there and take those results and first of all get the right results from how we ask it questions in other words have I given it enough data have I given it enough right data here have I given enough data so I’m not becoming I’m not part of the garbage in garbage out machine all right that requires thinking and then when I get it back having the conversations and looking at it in vetting it okay that’s going to take some thinking here and then I have to figure out how to present it and who I have to present it to because you know maybe I do have a Chief Financial Officer who is a former engineer and he gets keyed up so maybe I do have to throw throw her a few of Bones by putting in a uh uh you know some technology you know I’ve I’ve done that once or twice I’m a little Shameless in that way but you know we all have uh but again I I think we’re gonna have to keep thinking uh especially you know the state of AI right now you know we talk about a lot about prompt engineering now I don’t see that being a big thing five years from now I think the interface is be very very different five years from now yeah I agree we have no idea where this is exactly going but I I agree it’s going to be uh even more intuitive and just you’re going to be able to tell them the actions okay anyway we can talk about this for hours but I want to say thank you to Dean for taking us through so great uh I think just ideas and helping us frame a way in which we want to bring this back to our businesses in terms of our upcoming courses we told we told you it launched we’re offering everybody that joined us here as a thank you uh $200 off our new AI course uh the courses are taking place first ones in April April 1st and 2nd I think it starts at 1 pm eastern time uh and uh we just have a great lineup for you with our other courses as well check them out on our website uh we have a number of AI webinar and AI topics planned uh for for you all upcoming starting in April so also make sure to follow us on LinkedIn we’re going to be posting about all of the AI content coming out from 280 group uh in the next few months so stay tuned for that and I hope to see some of you at our inaugural class bye everyone all righty hey see you later and thanks for

Final Takeaways, Upcoming AI Content, and Closing Remarks

Rina Alexin & Dean Peters | 1:05:00-1:11:59

connecting that was fun it was a lot of fun bye

guys har dot yeah har my best student he he was the guy with me with seven legs while we were slugging it

out he took over when I left there really all right gonna close this out and I’ll see you