← Scrum Master Toolbox Podcast: Agile storytelling from the trenches
Scrum Master Toolbox Podcast: Agile storytelling from the trenches
Substack Week: AI in Product Management, Enhancing Product Development Through Artificial Intelligence | Toni Dos Santos
00:35:23
Substack Week: AI in Product Management, Enhancing Product Development Through Artificial Intelligence with Toni Dos Santos In this , we explore how artificial intelligence is transforming product management with Toni Dos Santos, co-author of The...
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- [00:02]
Pasco Duarte
Hi there, Pasco Duarte here, your host. I wanted to share a story with you. You know how sometimes Agile just feels like following another checklist when like processes and frameworks feel more important than what we are trying to achieve and sometimes even like handcuffs. I was talking to a customer of the Global Agile Summit and he used a term that kind of stuck in my he said, I have Agile fatigue. And I've heard that a lot from people since then. But here's the thing, it doesn't have to be this way. So we started thinking and at the Global Agile Summit, which is happening this May, we're bringing together practitioners who've actually done that, who've broken free from this, you know, install the framework kind of mindset. We want to focus the summit on real life, first person stories of Agile all succeeding that inspire you to action. We're talking real experiences, practical solutions, and of course, amazing insights from leaders like Gojkoacic, who will be one of the keynote speakers, and Jurgen Apelo, who will be one of the keynote speakers as well. If you're ready to leave the Agile fatigue behind, just join us in Dalit. The early Birth tickets are now available@the globalagilesummit.com and mark your calendar. We will have workshops on May 18th, that's a Sunday. And then the conference itself will happen on May 19th and 20th of 2025 in Tallinn, Estonia. So let's make Agile exciting again. And remember, go to agile globalagilesummit.com that is, and get your early birth ticket.
- [01:56]
Tony Do Santos
Now.
- [01:57]
Pasco Duarte
It will only be available until early March, so grab it now. And now onto the episode. Hello everybody. Welcome to one more Substack Week episode. This episode we have with us Tony Do Santos. Hey Tony, welcome to the show.
- [02:18]
Tony Do Santos
Hi, thanks for having me.
- [02:19]
Pasco Duarte
Absolutely. So Tony is the author or one of the authors of the Product Courier, which tackles AI for product management. He's also a seasoned B2B product strategist with more than 15 years of experience, having guided over 250 different SMEs and large enterprises. And as a former SaaS product founder, Tony specializes in accelerating time to market, driving sustainable product growth and aligning product strategies with business goals. His tailored approach empowers leaders to prioritize impactful solutions and boost revenue. Now, Tony, that is a short intro you write. You create a newsletter on substack. The link is in the show notes, so check it out everybody. The Product Courier and you decided to take on the AI in product management. So to kick us off, could you share a little bit about your background and how you became passionate about using AI in product management.
- [03:26]
Tony Do Santos
Sure. I'll try to make it short because as you said, it's been 15 years, so it's been quite a while. So basically I started my career in the music business producing and working with jazz musicians touring or around the world. But at some point I decided to move something because I was already interested for a long time in innovation. So I went to the bank, to the banking world in France. But in France you have to start by sales if you want to work in product in big corporations like banks. But right, right then when I wanted to join the bank at the time, I remember reading a book by a futurist called Brett King who was saying banking is not somewhere you go, it's something you do. And his idea, it was in 2012 was already how do we embed the usage of technology and banking services as seamlessly as possible? So it was like 14 years ago, 12 years ago. And it really struck a chord with me and I wanted to work in that area to find ways to put innovation to service of the consumers and making it like as invincible as possible. So I went, I did a few years in sales, I became an account executive, a branch manager for startups at the time. And while I was working in the bank then I became a lead product in another French bank. And I decided because I had seen that a lot of data was available for banks because obviously you manage day to day operations of everyone when they pay whatever, so you know everything about their life and all that data was not used or just a little bit on the surface of what could be done with it. So I passed a degree in data analytics at the time and by then it was 2019, we were already doing AI because it was a lot of machine learning, deep learning, identifying patterns in big data. And that was something that really interested me because I thought, okay, in the product leadership world that I have in the bank, I think that's something that can be useful in the future. So that's when I became acquainted with AI at the time. And then Scar GPT came and genai came in 2022 and so I dove deep into it directly and tried all the new stuff that came out. And when I joined Lemlist, so a French startup that does sales automation and that there's 30 million AR nowadays, they were also into AI right away because they were basically, since they do email sequences for outreach, you can do a lot of stuff with AI because it's all text. So they were very interested in it. So again, working on in product, I got even more invested in that. Then as you said, I launched my own startup which has AI in it. And what I realized when I was working and talking with all the product managers is that they were fantasizing what I could do in their work and in the products that they were building. And so that's why I decided to dive even deeper and build the product career, to share what I knew, to show them actionable use cases of AI. Because I think there's a lot we can do and we're going to talk about it. There's a lot of stuff we can do with AI and it's just the beginning as of today. So that's why it got me interested and that's why I'm so passionate about it because it can help me in my day to day work and it can help me build better products faster and more efficiently.
- [06:41]
Pasco Duarte
Yeah. So I'm sure everybody can hear the passion in your voice and tell us a little bit more about the product career. You have quite a clear concrete idea of what it is there to do. So tell us a little bit more about that.
- [06:57]
Tony Do Santos
With Lucas Michael, the co founder and co writer on the substack, we decided like about a year ago we were talking about this passion that we had for AI and we had seen that online, we wanted to do something in the area and we had seen online many already many newsletters talking about AI in general terms, in theoretical terms and they were great. But we couldn't find anything actionable about how to use AI in the day to day work. Even at the time, Lenny's newsletter, Lenny Rachiski's newsletter was not talking about that in that practical way. So we decided, okay, let's give it a shot and let's share because we use it daily and he does also in the product marketing area. Let's share the way we do prompts, let's share the way we use AI to build products, to write user stories as we're going to talk about too, other things like that in a very concrete way and focus really on that. And that would be the value proposition is one tutorial every week and nothing less, nothing more.
- [07:53]
Pasco Duarte
Yeah, absolutely. And there's quite a few already, I believe more than 40 at the time of recording. And one of them is about how you can use AI to write user stories. So can you open a little bit the Veil and tell us a little bit more about what you cover in that specific tutorial?
- [08:13]
Tony Do Santos
Yeah. So obviously user stories is a big pain And a big part of the job, but also a big pain for many product managers, particularly junior ones. And so the idea was, how can I use AI in this particular task that I have to do that is recurring task, and that is not with very, lots of quotes is not the most valuable part of my job. I mean in the writing part per se, not the concept itself. So how can I automate it? And obviously AI is good at recurring tasks and low value tasks. So I decided to look into it. And so the idea is that you provide the AI with a prd, for example, or the description of the product that you have, the features that you have, and it's going to write user stories based on the best practice of how to write user stories that you can find online and in articles and in books, etc. And give you also acceptance criteria already written. So to save you the time of writing all that. And as Jeff Patton was saying, because I know, and some people criticized the, the article about that saying, okay, but a user story is not, is not just about writing the stuff, it's about thinking and it's, it's a journey. And I agree. And Jeff Button was saying in his user story mapping book, it's to start conversations, it's not the end of it. But the idea of using AI in this case is particularly for that is you have the written stuff provided to you based on what you gave it. And then from then you thought and you think with the tech team, with the designers and whoever, okay, what are we going to do with those user stories? How can we find them? How can we go beyond that and so on.
- [09:53]
Pasco Duarte
Well, one of the things that clearly crossed my mind when I saw that particular tutorial was that there's a lot of thinking that goes into writing a user story, right? Like the user story is just the outcome. That's why originally it was called the three Cs, right? So it's a card, so a visual reminder that we need to talk about that confirmation. So the acceptance criteria that we can use to confirm that it has been delivered. And finally the conversation bit, which is that it's a constantly evolving understanding of what needs to be developed by the team together with the product owner. And one of the things that came to mind is that AI is potentially a great partner to have that conversation ahead of going and then sharing it with everybody. Right? I'm thinking, like the phrase, I've heard it before, you know, everybody makes mistakes, but not everybody needs to know you've made mistakes, right? And having a conversation with The AI can, can help us uncover those simple, easy mistakes that we can then avoid and, and not spend any time on it. But you talk about other aspects as well. Can you highlight for us what are the key aspects you think that product managers can benefit from when using AI to write user stories?
- [11:10]
Tony Do Santos
Yeah, sure, as you say. Well, the brainstorming part is actually important one as well because one of the things that AI often can help you once you provided it with the information, it writes the user story from the prompt that I share, for example. And then you can ask, okay, what are the edge cases that you envision for that? And often, and it happened to me in real life as well, it suggests potential edge cases that you would not have thought of. Sometimes they're not relevant, obviously, but sometimes they raise a good question and that's a good starter to go further and think, okay, yeah, this is an option that I haven't thought of. Maybe I need to dig deeper than that. Also in terms of the way, because it writes automatically and it puts the acceptance criteria on itself, particularly for junior PMs, it's a good way to, to have a clearer thinking. Like I see it written that way. If it's what I had in mind. Well, that way I have a clear vision of what is written because it's structured the proper way. If not, that means that my thought and what I gave AI was not clear enough. So maybe I have to rethink myself the way I approach that. Because obviously stories written, okay, it's just the output. But the thing is, many juniors or many POS in companies don't even have the time to think anymore. They're just there to do delivery and writers stories. So obviously on an intellectual level, it's great to say, no, this is a starter point because you need to think. Okay, it's true. But the reality is, most of the time they don't have that time nowadays. So AI here is a good way to save you the time to do that boring part. And then, okay, now I save 20 minutes writing the user stories. Now those 20 minutes, maybe with the output that I got from AI, maybe I can think and see and brainstorm with it and interact with it how I can go beyond the basic stuff and the dull part, which is just transcribing a PRD into a user's node.
- [13:11]
Pasco Duarte
Yeah. One aspect that is really interesting for me is that with the use of AI, let's say you're a product manager and let's say you're not a junior anymore, right, like mid experience or large experience. You already have a body of knowledge. You can easily fit that into the AI as kind of preparation for what a user story should look like when you write it. And it will get your writing style, it will get the type of things you usually add to the user stories. And most importantly, I think it would be a great advantage for us product people is that it allows us to give that LLM, customized LLM to the team and say, here, you write the user stories. I'll just check that they are actually what I thought they should be. And from now on, let's focus on what the customer needs. Let's talk more about that. And then you guys can write the user stories because you already have the LLM that could do it. And then I can validate. Right. It also can help us to kind of offload some of that detailed documentation that is necessary for the team, but doesn't necessarily cover the most important aspect, which is like to be in touch with what the customer needs, their workflows, you know, all of that thing.
- [14:27]
Tony Do Santos
What do you think? Yeah, you're opening up to the way I like to describe the benefits of AI because many people say I will replace product managers that don't know how to use AI. To me, it's not true. I will replace bad product managers in the sense of what you're saying, which is if you're a PM and all you do is write user stories, write documentation all day long and never think, never have time to go with a talk to users or, or think strategically or be creative. Yeah, AI can do your work because as you say, and actually I do it myself. I said, I have a prompt that I'll share in the newsletter. I can share it with you so that I can share with the people that are listening. I have a prompt, and in the prompt there's a structure written off. Write the user story this way, using the gherking, et cetera, classical stuff. But you can say, okay, write it this way, with this tone, with this kind of language. My company does this specific kind of work, so I want to add that so you can specify. So that part really is the heavy load and the less important. But that's why I was saying it's not valuable per se, because it's recurring, it's automated. You basically always just write the same thing or the same structures, so that can be automated. And as you say, once we've done that, okay, now I have time to do what AI cannot do, which is align people, talk to people beyond, because we're Going to talk about it, probably, but you can. User interviews, you can summarize them, you can extract very interesting insights with AI, but what you cannot do is extract sentiment and feelings and ways of people, how people behave beyond the words. Meaning when you're interacting with someone, you can tell me, oh yeah, your product is great. It's not the same as yeah, your product is great, and that you cannot have in a transcript nowadays, maybe in the future, but nowadays you can. And that's where being a good PM is important. To understand the why and the deep feeling of the users and think strategically, think creatively, because the product sense beyond generic stuff, you need to be creative. And let's keep in mind that AI models and LLMs are probabilistic models, meaning that you're going to get the most generic and most common response. But if you're common, then you're not exceptional. So what's the point of choosing you instead of another product? So to me, yeah, that's what you were saying is very important, that the AV load can be replaced and can be done by AI. And it should be. Because nowadays, what's the point if we have a tool that is better than us in that way? Same as writing, for example. Market research. Yes. Okay, I'm a great market researcher. I don't need AI. Yeah, but AI has read and knows 100 million documents that you've never read before. So what's your added value in that specific part, which is summarize generic news and generic information? Maybe your added value is understand the market and how it functions beyond what's written and the trends that everybody sees and have that feeling, that product sense, to go beyond that.
- [17:24]
Pasco Duarte
For example, following that thread, one of the things that is really important for product managers is to get that essence of what the users need. You referred to it just now. So how do you use AI to ensure that the stories it generates with you are actually meaningful and aligned with this user needs?
- [17:47]
Tony Do Santos
Yeah, well, most of the time what I do, because I use AI on the whole chain of value when I build a product is use all the transcripts, the feedback from the user interviews that I have, feed it to AI and retrieve from it the key pain points, the major patterns that it identifies. The major, yeah, the top three pain points, the words that are most recurring along those interviews that I did, along the feedback tickets, et cetera that I had. And then when I write the user stories and fit it, my PRD or documentation, I often add those summaries too, so that it can understand. Okay, Those are the pain points that we identified. This is my prd, the way I understand and I feel that we're going to need to approach this, write the user story and often I say raise questions, identify gaps in my reasoning that you can, that we can discuss. And that way I'm sure I tried to make sure with it that I'm aligned with what I had identified as the essence of the needs of the user when I wrote the prd, all the documentation that I needed for the user story and have AI double check with me and brainstorm and challenge me on what I thought.
- [19:02]
Pasco Duarte
Well, one of the things that you just said is actually for me quite a great shortcut for product managers and product owners because we will need to discuss these user stories with a lot of people, of course, obviously the developers and testers, but also maybe other product managers, other teams, whatever that might be. And you can start by having that practice by asking the AI to challenge, think of different angles, find gaps and so on. And especially if you have all of that transcripts and user interview data that you can use. So besides feeding it the transcripts and user interview data that you have, how do you use AI to uncompress cover to clarify user needs?
- [19:47]
Tony Do Santos
Well, obviously that's to analyze something that I've done with always keeping in mind that you need to double check and make sure what you're giving it. Because as I said recently on a person stack, it's wrong 20% of the time, we know it. So the idea is, okay, would you give the responsibility of deciding to put a feature out for someone that you know that is going to be wrong one time out of five? Probably not. So always double check what AI gives you. That's the first thing obviously. But beyond obviously transcripts, which is now the norm. For example, one way I used AI working for a French company called Blah Blah Car, which does like car transportation. They have an app and it's a huge consumer app in France. So what I did is ask AI. Okay, build me a script to scrape all the reviews from the online Apple Store app stores from Google and from Apple and from there. So it was like, like 7,000 reviews from there. List the key words that re that the most common and the recurring pain points that come up. So that way it could help me check with the interviews, qualitative interviews that I've done if there were patterns emerging and if there were things that were coming in both of them. And another way that I use it, and it goes back to the when I was a data analyst and it's something that goes beyond Gen AI is I give it all those reviews, I'll give it the transcripts, I give it the tickets, etc, is identify patterns or clusters of users that we can segment that have shared pains and have the same problems. And that way when you have a lot of interviews or a lot of data, because it's not just interviews, it can be also one thing I use it for is with amplitude or mixpanel, to have quantitative data like logs, certain triggers, how many times they open a feature or whatever, giving that to AI. AI can define patterns, clusters of users in a way that I could not do, or I could do, but it would take me weeks to do. So that's a good way for me to uncover pains. But always, it's always to confirm or infirm the thoughts and the needs and the pains that I had identified from my qualitative work and my own analysis of the things, never just relying blindly on what it gives me.
- [22:07]
Pasco Duarte
And that's a very important caveat. Right. Like always double check what AI gives you. But one thing that I would say based on my own experience, is that you want to be surprised, right? Like if, if I'm using AI to help me think and reflect and I'm never surprised, then I'm probably not asking the right questions. So what do you think about that? Like the, the surprise effect? I mean, it can be that it's wrong, but if it's not surprising, it's not really pushing our thinking further.
- [22:36]
Tony Do Santos
Yeah, yeah. And that's why, as I said, I often ask when I ask it to generate something, identify gaps. One of the simple prompts that I like to use is, okay, you generated a prd, a user story, a document, a transcript, summary. Okay, now identify the gaps in my conclusions or in what we identified as pain points here and what potential gaps I might be, what potential things I might have missed. And that's always a good way to challenge even yourself. Like sometimes you say, okay, you gave me three gaps, one of them is totally irrelevant or totally absurd, but two others might be interesting to dig into.
- [23:13]
Pasco Duarte
Yeah, yeah.
- [23:14]
Tony Do Santos
Because that's the basic one. Yeah, yeah.
- [23:15]
Pasco Duarte
If it gives you five things and one doesn't make sense, but at least one of the other four is surprising, we're winning. Right?
- [23:24]
Tony Do Santos
Exactly. Yeah. And the idea is that again, it's to save time, it's to have more time to do more interesting stuff or to open doors that would not have thought about what you were saying before we had Shana, I'll share it with you also one of the prompts that we had shared in an article is to use AI to interact and act like a board meeting about a feature. For example, we're launching a new feature about, I don't know, lemlist about inbox rotation for, for outreach generation. Okay, you're going to be the cmo, you're going to be the CRO, you're going to be the CEO and the customer support service. And now we're going to talk about it. And each one have their own obviously priorities, etc. So now challenge me and ask me questions like they would. And that's a great exercise when you're trying to make a presentation or again, to challenge your point of view. Because when you're in the tech and the product world, sometimes you overlook other aspects, as we all do, as marketing does on their side, et cetera. And it's a good way to have challenging ideas.
- [24:30]
Pasco Duarte
Also, yeah, talking about supporting our work and also to have leadership thinking. Many leaders in the software industry, at least up to now, maybe that will change. But at least up to now a lot of them talk about AI as a tool for automation or document generation in the case of product management. But I'm curious, like, how do you see it playing a more strategic role, specifically for leaders, whether it's product leaders, tech leaders, organizational leaders in the software industry?
- [25:03]
Tony Do Santos
Yeah, well, actually, yeah, that's one of the big gaps that I've seen is that many people think that we replace like blue collar or low level people. And actually what we see is that it replaces a lot of work of eye level or white collar people. Why? Because again, most of it is based on documentation and texts and we know that what's most common is text about strategy, it's about leadership with hair, tons of stuff like that. Whereas operational things or creativity things are more complicated to grasp from AI. So for me, for product leaders actually and leaders in general, they should be the ones thinking about, okay, how is AI going to affect my work? Because to define a strategy, to define a roadmap, AI can summarize tons of data, tons of information that you can note yourself. So that's to me, for leaders, it's a great tool. Again, I always like to use it. And when I coach founders, that's what I tell them. Use it as a sparring partner for your own creativity. When I launched my SaaS, for example, I used it to do the marketing strategy, the product roadmap, the product vision, to write it down. I had my own vision, but I wanted something really Structured to work with me on the automation process, of course, but more on the strategic level, on the positioning, the branding. Tons of things that you do when you're founder, when you're a leader, and again, you often need teams to help you or specialists to do that. Well, now, with AI, you can do not the best thing, but you can get started very easily with just one tool. Using an LLM, for example.
- [26:38]
Pasco Duarte
Yeah. We interviewed Marshall Goldsmith a few months ago on the podcast, and one of the things that he said is exactly that, that, you know, I can never compete with this machine. He's developed his own AI because it has immediate access to everything I've ever written and it has perfect recollection. I mean, it will hallucinate, but it has access to the actual text all the time. So there's no way I'm going to be better than it at that. But what I can do is use it for that. So immediate access to a huge amount of information and then of course, treat it as only I can, which is giving my personal insights and ability to reflect that. Of course, the AI will not have, because it can only correlate information, it cannot create information. Right. Because it's based on existing text. It's not based on text that has not been written.
- [27:31]
Tony Do Santos
Exactly. And another thing is, particularly when you're a leadership position. So now, because AI is based on text, on image and things like that, one of the big aspects of leadership is how you align people with your vision, how you make sure that this team works well with this team in product, mostly. How can I align sales and marketing because they're always fighting. How can I make sure everyone is on the same page? And AI cannot do that because obviously it's human interaction, it's live interactions, and it involves psychology, lots of things that for now, AI cannot do.
- [28:05]
Pasco Duarte
Yeah, absolutely. And talking about that, one of the key questions for me is how can we start taking advantage of AI in supporting decision making, strategy development, team collaboration? Have you been running some experiments on those aspects, Tony?
- [28:22]
Tony Do Santos
Yeah, well, one of the things, obviously for meetings, for example, it's a great way because you can interact with AI in a meeting. So it can be a good way to prepare for meetings. For example, it's a good way to create alignment because it creates the topics of the day. I say, I want to talk, for example, we're going to launch a feature, write me the agenda for the meeting. And he writes, there's going to be the medium, there's going to be the marketing, there's going to be the sales, there's going to be the VP of support and then it can create an agenda that's relevant and that appeals to everyone, for example. So that's a good way to align people because we know meetings, nobody wants to go into them usually even though everyone does. But yeah. So decision making again for me, for now at least it's a good, good way to brainstorm and get ideas on. Okay, these are the options that I can have because as you say, it has a lot of data available, these are my options and then I'm still the decision maker because again, I wouldn't trust someone that's wrong 20% of the time. And that's one of the big issues with agents today because everybody is talking with AI agents nowadays is AI agents is good for low level tasks that don't involve any critical decision making. I wouldn't give the decision to make to build this feature or another feature to a tool that's wrong 20% of the time. So for now, to me it can be very helpful to give me options to suggest ways of doing things. And again, one of the things I use it most is to do mock ups interviews or for example, I coach PMs when they do job interviews. Built a little boat for them to help them. Okay, you're going to be interviewed by a CPO from this company. Share the information about the company, share the information about your own resume and it helps you practice that way and that's a good way to be better at decision making and at leadership because it helps you practice your, your skills.
- [30:20]
Pasco Duarte
Yeah, absolutely. I totally agree. I think one of the key uses for me of AI has been exactly to prepare conversations, whether it is to have a sparring partner or whether it is to find gaps in my reasoning. All of that just to prepare conversations that I'm going to have exactly to do what you just said, which is to align different people, align different parts of the organization. So Tony, of course you're one of the authors at the Product Courier and the link will be in the show notes everybody. So check it out. Make sure you go and read the newsletter that Tony and his colleague Lucas. Right, the Product Courier. But for product managers and leaders that are interested in exploring more this world of AI, what's one resource could be a book, a video, a podcast, whatever that is. Other than your own product career, what's one other resource you could recommend for product managers that want to take advantage of AI in their work?
- [31:24]
Tony Do Santos
Well, to me, because unlike concepts, it's very a change in the way we work. To me, the best resource is to go into it. Basically it's just practice. It will make you better because you can learn all the theories in the world. It won't be good enough. There are tons of free courses online, so you can take them, but the best way is just to get a ChatGPT, Gemini, whatever, and just dive into it and try and get learning and start practicing right away. One resource, if I had to recommend resource to be, particularly if you want to go into AI product management, is the Arman Re course, which is the vp, is VP about AI VPI at IBM. And he built a free online course about AI. But it goes really deep. Like you even how to do data management with AI. Very specific, very clear. He explains what gen is, what deep learning is, what the different kinds of AI in a very technical way. And to me, it's the best resource because first it's free. When you take the course, I think it lasts like it's like 12 or 15 hours. I mean, it's really, really extensive. And you can take over the course of two or three weeks. And it teaches you everything you need to know to understand how AI works and how you can use it to build products, which to me is the most important part. Aside from that, and even again, I have a list of 80 free courses that I categorize so I can share with you. You can find free resources online very easily. And the best way is just, okay, open chatgpt. Think of something you want to do, ask it, you'll get an answer. You'll say, okay, this is not good. Okay, well, try again, adapt with it. Because one of the things that one key advice that I would give anyone wants to go into AI, what hasn't already is it's called conversational AI for a reason. Meaning that many people that I've seen just, oh, I tried a prompt, it gave me a bad answer, I gave up. It's not good, I don't need it. But because it's conversational, so you need to have a conversation with it. So you give it something, it answers, you answer back, et cetera. And that's if you understand that you already better than 60% of the world, I think.
- [33:42]
Pasco Duarte
Yeah. And this conversational part is actually very important because that's how we do our work as product leaders. We have conversations all the time, whether, whether it's with users, customers, colleagues, teams, whatever. Right. Like we're in conversations all the time. So practice that for sure.
- [34:01]
Tony Do Santos
Yeah, exactly.
- [34:03]
Pasco Duarte
So Tony, about, about you.
- [34:05]
Tony Do Santos
Where.
- [34:06]
Pasco Duarte
Where could people go if they want to get in touch and know more about you and the work that you're doing.
- [34:10]
Tony Do Santos
Well, the best way is to contact me on on LinkedIn because that's where I'm the most active. So I post stuff about AI and product management regularly. So reach out to me on LinkedIn or just subscribe to the product career and there's a contact there so they can reach out to me and that's the best way. And I'm always happy to discuss and to share some knowledge if I can with the private people. So feel free to DM me and send me a message. I'll answer everyone.
- [34:39]
Pasco Duarte
Absolutely. Absolutely. A pleasure to have you. Tony. Thank you very much for your generosity with your time and your knowledge.
- [34:47]
Tony Do Santos
Thanks a lot. It was great, great talk.
- [34:53]
Pasco Duarte
We really hope you liked our show and if you did, why not rate this podcast on Stitcher or itunes, share this podcast and let other Scrum masters know about this valuable resource for their work. Remember that sharing is car.