Namaskar. I'm Professor Devde Purkayastha from IIT Bombay and I welcome you to my course, Business Fundamental for Entrepreneurs Part 2, External Operations. This is a guest lecture by Mr. Ashok Balasupramanian who is the founder and CEO of Open Weaver and who focuses on emerging technologies to further the digital space. He has supported clients across the world in North America, Europe and Asia in their digital transformation initiatives. After his graduation, he did his MBA from I am Bangalore and he has served as a global CTO of ATOS. So, with that over to Mr. Ashok. Welcome to the module. Glad to be sharing my experiences and insights with you all. Thanks to Professor Devde, IIT Bombay and NPTEL for inviting me for this. We have got an exciting module ahead of us. So, it's a pretty insightful and engaging topic. As we all say, the proof of the pudding is an eating. So, if you look at this topic, there are two key parts to it. Starting with the bottom part of it that says rapid prototyping. Why rapid? Today's business world is fast. The sooner that you can create your idea, demonstrate your user, get feedback and improve your product. So, rapid, extremely important. And the first half is even more important. It essentially says winning with customers. You create a product and that product is successful if the customer is successful in solving his or her pain points. So, extremely important for you to think of can the customer win with your product? And that's why we coined this module as winning with customers through rapid prototyping. So, very exciting topic. We look forward to share more insights with you. As we go into this, right, so as we think about rapid prototyping for winning with customers, what's important? How do you leverage? How do you go about it? There are multiple opportunities ahead of us. And the first opportunity is digital. So, the way the industry has evolved. So, if you look at it three decades ago or two decades ago, it used to be called as management information services. So, there were computers, there was management and then the job was, you know, getting some weekly reports, monthly reports to management. And then if you're lucky, you had something like an ATM or a stock trading which was near real time transactions. So, that was about two decades or thereof three decades ago. If you look at the past decade, we said this technology, information is becoming key for everyone. So, you could kind of, you know, take this information and its technology and give it to everyone. And then you look at last decade, we called it IT or information technology, where the information was available to everyone that executed operations. So, all knowledge workers had IT and computers. So, we looked at the era of something like an e-commerce, online trading and so on and so forth. But if you look at the past decade, things have changed in a very big way. So, look at it today, the way you're looking at this course fully online, the way you probably streamed the World Cup match, the way you probably bought your lunch today. Everything is online, you know, everything is online and you really cannot separate. Is Uber a business if there is no mobile? Is Zepto a business if there is no mobile?  So, very important as we move into this era of rapid prototyping for winning with customers for you to think digital first. And when you think digital first, it kind of gives us three large opportunities. First one is it deeply embeds the product or the experience with the customer. So, typically I think this is a very subtle but very important. When you typically think of a prototype, you kind of say bring the customer to the prototype and let them do something. But when you kind of think of it as a digital experience, you're already on the customer's phone, you're on their device, you're probably on their watch and so on and so forth. So, you're already deeply embedded in the customer's workflow. So, you don't need to think of, you know, how do I get a customer? How shall I have her try this? You're already in the customer. So, first advantage of thinking of your digital prototype is to make sure that, you know, you're able to be in the customer's workflow or daily activities in some sense. Second opportunity that it gives you is what is scale because typically if you look at physical prototypes, you think of standalone prototypes which are not connected, they significantly limit the access to the physical market that you can reach. Think of it as a digital experience. It kind of opens the whole world as a market place to you. And in that scenario, even, you know, if a product is physical, even if you think it's an electric vehicle or some sort of creatinine chip that you're making, think of how you can create a user experience for the customer to say, can she check her creatinine levels on her phone? Can she onboard? And based on those creatinine levels, can it recommend diet for her? Can it, you know, kind of book a doctor appointment or the next dialysis appointment? So, think of how you can gradually expand the boundaries of not thinking of it as an isolated physical experience, but more of a fully permeable digital experience that kind of sets the tone that, you know, the whole world is your marketplace. So, second important advantage is the whole world is your marketplace and towards the end, you know, I think we'll go through some demos and see how you can leverage digital marketing to kind of get to the whole world is your marketplace. So, third part of it, again, you know, you could look at it as significant disruptions, but where we are startups, right? So, disruption is an opportunity, right? So, wherever there's a disruption, that is an opportunity for you to change the game. And the disruption of the decade is, of course, generative AI. So, there are infinite opportunities opening up in generative AI across, you know, anything from claims processing to a digital scribe for a healthcare, all the way to citizen services from a government perspective, where, you know, complex documents can be explained to users. So, there are infinite opportunities across each vertical, each microvertical that ensures that there is significant opportunity for you to change the way the world works. So, digital, again, embracing digital, like I said, a creatorship is a physical product. But if you think of it that there is a dialysis mentor sitting on the phone talking to the chip, which is using generative AI to say, hey, if you are a strictly vegetarian, what should you be eating based on your creatinine levels today morning? That kind of, you know, increases the stickiness of your product with that customer and can significantly make you successful. So, three amazing things on why you should think digital first when kind of, you know, we go through rapid prototyping to win with customers. So, those are aspects on, you know, how you could go about doing things. One other critical aspect, I think, of what, you know, you could think differently. And this is based on significant experience, having worked in technology and technology products over the last 25 odd years. Typically, in a legacy world, we go and we can have asked the customer saying, hey, I think you have this problem. If I do A, will it solve it for you? If I do B, will it solve it for you? If I do C, will it solve it for you?  But there are two inherent challenges there. We, lot of us come from, you know, engineering background, idea background, our communication may not be the best. So, what essentially happens is we may not be able to paint that magic to the customer on what he or she is actually going to get. So, one, that communication gap of what they are going to get could distort their feedback. So, they may infer that, you know, you are maybe giving some idea A, B, C versus for them, you know, they might have thought it's something else and then they could give you feedback on based on what they think. So, that's one distortion. Second, I think the other biggest mistake that we entrepreneurs do is we talk to people whom we know. So, that's the other mistake, right? So, you may get a soft feedback. Someone says, okay, you know, let me not spoil his enthusiasm. Let's say, okay, this may look good and something works and it may work. And of all people, right? I think Steve Jobs summarized it well. Customer does not know what he wants unless you give them something, you know. So, that's a critical part of it. And again, that's where the prototyping becomes critical. But even in that concept of prototyping, don't separate the prototype on the customer. Don't say, hey, customer, you're here. And my prototype has feature A, feature B, feature C. Look at it and tell me what to do is where things can go wrong. What you could do again, you know, I think these are advantages of digital. What you could do based on digital is this concept called minimum viable product. What it essentially says, build your prototype to a functioning level. So, if you thought of prototype as something that is just clickable, navigable, but does not do something, bring features into it that does something, you know, that does the bare minimum that the customer needs to solve her problem and give it to the customer, right? So, instead of saying, hey, customer, this is what I have. Can you look at it and tell me? We're doing two things, right? One, we're actually building a product which is as small as possible. And instead of showing it to them, we're giving it to them. And since we have thought digital now, you don't need any special interface to give it to them. You're going to maybe deploy it in their phone, deploy it in their web browser, so on and so forth. So, it's so easy. So, now it becomes more of an observability for us rather than an interview. Now, you let the customer use your minimum viable product and you can get feedback from them digitally. You can observe them digitally to see what they're doing. And are they able to, you know, solve the problem that you intended this product or the service to do? You can watch it. So, extremely, you know, again, a very soft separation but extremely important. So, we're essentially saying prototype, absolutely important, add core functionality to prototype. And instead of demonstrating it to customer, give it to the customer to use it. Let the customer use it to solve the problem. And since we're deploying digitally, you can deploy it into the customer's workflow and get feedback, you know, both direct as well as observable feedback on how she is able to solve the problem. So, extremely useful concept called minimum viable product in the digital age of how you could, you know, rapidly prototype, something that is significantly testable. Now, if you look at the MVP approach, what is important here, right? So, important is for us to understand what the problem is. And of course, you know, as entrepreneurs, we set out to solve a problem. But sometimes, you know, we get carried away by four or five new ideas that may come in. So, strip the idea to the barest minimum form to say, hey, this is the core idea. And then look at, you know, what is the core person of the user?  Because again, if you think about it in six months, 12 months, two years, of course, you might have a unicorn idea where you'll have millions of users. Of course, that's there. But today, this week, next week, next four weeks, who would you want to test that core idea with? So, that's again, a very important part of how you'd go about it. Then the third part that comes in as, you know, because we don't want to take too long, right? So, we said, we want to give something that is functional into the hands of the user, into the digital device of the user, you want to try it. We absolutely cannot afford in this digital world to take, you know, two months, three months, six months to get that feedback. We need that feedback in one week, two weeks, or whatever time that shortest possible. So, think about it in weeks and not in terms of months, or of course, you know, very long, it kind of loses the flavor and the world changes fastly. And last important point is, don't fall in love with the solution. So, whatever you created as a solution or a minimum viable product, don't love it. Let's say we thought of a problem that the customer faces are a market opportunity that exists today. And we kind of came up with a solution. That solution is just one way of addressing the problem. So, of course, you know, I think some may work, some may not work, but feel free that, you know, it may not work and you will be ready to throw it away. So, this is a great concept, right? So, now if we think of it and say, hey, let's put some boundaries around it. Let's take maybe an example. And since we said digital and you know, there is so much changing in generative AI, I worked with a few startups who came up with some similar idea. So, you may know an Etsy or an artsy. So, these are all large online market places focusing on handmade art and craft.  So, group of young folks who were kind of into arts essentially said, hey, you know, we have an amazing idea, we looked at it, we want to reinvent in some sort of a modern art perspective.  So, then, you know, they ideated and said, hey, let's use generative AI because AI can today, you know, paint and draw, right. So, think about it many years ago, we said the bots will do menial tasks and humans will do imaginative. This past year has actually shown that bots can actually do a lot of the imaginative, it writes poems, it draws. So, this team kind of got, you know, a founding team got excited and said, hey, let's disrupt this market. Let's bring in a concept like what McDee did, right. So, McDee said, this is fast customization. So, there are pre-built blocks, but you can build your own burger, but it is not a fine-dined restaurant where everything is cooked from scratch. So, there the, they clearly set out the problem that said there is a one-end high-end art collector market, which will really look at named artists, excellent paintings, which are in tens or lakhs of rupees or even much more crores of rupees. Then there is your bottom of the pyramid where you already have pre-printed, maybe a few hundred to maybe a few thousand rupees where, you know, you have pre-printed card stock available that you can use as art. In between they said, hey, let's create a market where the user can describe something and then it solves the problem. So, very clear clarity that said, hey, we are going after a market which is willing to pay maybe a few thousand rupees for art, something that they feel that is part of, you know, what they created and something that is customized to their taste, but may not have the wherewithal to, you know, commission a real human artist to paint. So, very good clarity in terms of having saying, you know, what you are trying to solve, what is that part that you are trying to solve and who is that customer who is going to be your test customer for that point of time. So, now even if you have that clarity that says, here is a set of customers who are going to, you know, benefit from that amazing idea that you have. As entrepreneurs, we again, you know, get carried away, say, hey, beautiful, you know, I have generative AI, I looked up generative AI, generative AI can do image to image, text to image, voice to image, video to image, idea to image, it can do so many things.  So, we all get super excited, right. So, and of course, as startups that enthusiasm is what keeps us going. So, nothing wrong with it, but time, right. So, as startups, we cannot fail in two things, right. So, one is not addressing that market fit quickly. And then of course, if you don't do it in the right time, you run out of funding. So, this whole part of actually winning with customers with rapid prototyping will solve both. In very less funding, you can create a minimum viable product. And by giving that minimum viable product to the smallest customer segment, you will test your market fit very easily. So, again, it becomes critical for us to create that most robust prototype in a rapid manner. It is extremely important for us to prioritize features. So, we cannot go back and say, you know, there are infinite features that will come out and that may take months to build. So, think about what is absolutely the users need. So, here our example where we said there is a generative art and maybe let's call it me Picasso, maybe I want to be like Picasso is what we are trying the users that you are as good as Picasso. So, let's say you know this me Picasso that's there, it has to test that need, right. And what is that need? The most basic need we are saying is users are willing to pay, right. So, willingness to pay is absolutely critical, right. So, you want someone to pay for it. And what is it that we want them to pay for? We want them to pay for an art that is generated based on the user's idea, right. Very simple. So, if you think of that as the core idea and then we call, you know, there is a beautiful concept and minimum viable product called needs met criteria. So, we are essentially saying create a prototype that is functional, that will make sure that these needs are met, that needs are just twofold. One user is willing to pay and two user is willing to pay for some art that is generated based on what the user told to be. Then beyond that you will have, you know, many ideas you will say maybe the user will sign on it or maybe the user will see one picture and then, you know, draw something according to it or maybe the user will speak, the user will sing, all those things will come later. So, important part of prioritizing features is the time scale. Of course, in three months, six months, 12 months, everything is important. But think about what is important in the next two weeks to actually show that criteria that says customer is willing to pay for an art that is generated. So, that is a very critical way to think about it. And we would not go through it in detail here. I would recommend you to kind of, you know, look it up. So, there are two beautiful, you know, structured models. One is called the Moscow matrix and second is called the Karnov model. Both are fairly similar. I brought both because they bring slightly different flavors. Moscow is very clinical in the way it addresses. It says here is a must have, should have, good to have, kind of.  And then you will get a very clinical analysis to say, you know, I had 50 features. At this point of time, these are the three features that are essential for a customer to absolutely try that core needs met criteria. So, it is one way to look at it and that is absolutely correct. But what we also found useful in the Karnov model is it takes one step further. It says absolutely do what Moscow said. I think go after the big blocks, go after the important ones at this point of time. But since these are digital, look at what can create user excitement. We want the user to be happy. If the user is happy, one, they should absolutely solve their problem. But can you make them excited about solving the problem? Because there are two ways, right? You could take them through a very methodical way to solve the problem. Of course, the problem will be solved. It will be a transactional success. But if you can give them a little bit of joy that says, hey, my prototype also made them sit back and said, wow, right? So, think of our example. Our example says, me Picasso says, the user is going to be an artist. So, can you motivate them? Can you tell them, saying, hey, you are now like a world-renowned artist? They feel happy about it. Maybe can you do two steps further? One, maybe can they share it on Instagram, whatever they painted on Instagram so that their friends will say, wow, you are a great artist. And it also gives you advocacy, right? Because if your first users share it on Instagram and said, hey, I built it on mepicasso.com, that is going to be free advertisement and free word of mouth for you. So think of points of joy for the customer where she or he not just solves their problem, but also feels good about solving it and feels good telling someone else that their problem was solved with your prototype. So, about 90, 95% spend on the logical grouping, spend 5 to 10% in kind of seeing if you can bring those features that will bring joy or excitement or stickiness to that user. And last important one, of course, customers are our best teachers. We learn from customers, but don't shy learning from competition. I think what worked well for them, get inspired by it. What didn't work so well for them? Of course, you can plan ahead. You don't need to repeat the same mistake. You can plan ahead and fix things from there. So while you focus on needs met, so this again becomes critical, right? So think about it. We talked on the previous section on how do you go through it? You could use a Moscow model or a Kano model to go through and pick your needs met. This is another view that kind of pictorially represents. And this is where some of us go wrong. I come from an engineering background. I get happy that says, hey, this product is built on this cloud technology. It can scale to millions of users. It uses some llama model of generation, so on, so forth. Who cares? The customer doesn't care or it doesn't directly impact the customer's outcome, right? So don't think of needs met or your minimum viable product as features that you're using to build the product. So let's say, for example, if you're going to use OpenWeaver Studio to build the product, that is not something that you should tell your customer. If you can't tell your customer, I use this technology, so please use my product. I don't think they will find use in that. But if you tell them, hey, you can be an artist using this. It solves the need of you being an artist and it solves the need of you exhibiting it. Maybe you can print it and ship it your home or you can share on Instagram. You're able to exhibit it. So needs met criteria are focused primarily on features or experiences that solve the customer's problem and are not based on internal features of a product. So again, think through very deeply here. Many of us go wrong there by spending too much time on how to build something versus what addresses the customer's problem. You can, of course, build a platform that will scale to lakhs of users maybe in three months, six months. But if you want to test that idea, that says if someone is willing to pay for an art that is generated, use the shortest possible path to get there and focus on those two needs. If someone willing to pay, if someone willing to draw something through generative way and don't spend too much time to say my UI has this jazzy feature, second drag, drop, do this, do that. My cloud is so secure. It doesn't matter in this state. Once you become scalable, once you become super successful, a lot of things will make sense. But using the principle, we said startups very important market fit and time and money. So, you want to get market fit with the shortest time and the shortest or smallest budget possible. So, these two will kind of make us stay true to, can I build something quick which will focus on needs met criteria for my user? And you don't need to be too shy about it. Because we all say, hey, no, no, I have such a big idea and unless I build all these things, my customer will just throw my idea away. No, it is not. And that's very, like we said, look at competition, look at mentors. And mentor doesn't need to be your mentor in incubator or someone whom you are talking to everyday. Mentors can be, of course, industry leaders. So, look at what the largest of largest providers and digital leaders did. So, if you look at Airbnb, their minimum viable product just tested one thing which said, are people willing to share maybe some part of their home and is some customer willing to pay for it? Very simple. Website, very simple listing, does not do payment, does not have maps, users transact separately. And it started with just air beds for events, which means there is an event that is happening, let's say in Mumbai today. And if I have a spare bedroom, I inflate an air bed and I say this is maybe 1000 rupees for a night and then someone does it. So, super simple. We could have think of it, you would have gone all over the place, trying to create an amazing website which does so many things, not required. So, think of minimum viable product and that rapid prototype to say, is customer willing to pay for a shared accommodation, nothing else. Next, fintech, darling, Stripe from fintech, one of the biggest inline payments that is there and most of us startups that want worldwide payments use Stripe, so successful. But if you look at their first product or even their minimum viable product that came out fully manual, except it kind of showed them saying, there is a product that is available. Once you sign up, someone manually onboard you does the manual integration and then you are on your own. But it just tested saying that there are customers who are willing to pay for alternative inline payments to what typical merchant model that existed at that point of time. So, very simple. The third one, one of the most customer centric organizations in the world, Zappos. So, at that point in time when people bought books and then Amazon said, hey, you can also buy electronics online, they came out and said, hey, why can't people buy something like shoes and in that time the concept was things like shoes and apparel are things that you need to touch, feel, fit, look, feel, all those needs to be there. So, people will not buy. So, their minimum viable product was very simple, a simple website that listed shoes, then someone places an order, someone in the back end actually runs to a store, buys the shoe and ships it to you and then you pay for it. So, super simple, but what did it do? The needs met criteria that essentially said someone is going to pay and buy something that is experiential like a shoe online. So, it tested that part of it. So, extremely important for you to crystallize your prototype to the smallest factor which makes sure that the user is successful or your hypothesis of how the user is successful is met very well because that will make sure that if you crystallize it so small, we will be able to launch it in days and weeks and not months which is critical for any startup to succeed. And of course, I think while we talked about, we will do it digital, we are going to use a generative AI. What becomes critical is digital has also come along. Zappos tried these were like 5 years, 8 years back when they were much smaller, but the concept of minimum viable product is still today true. So, for example, this World Cup, I was looking to order t-shirts for me and my friends on Zepto because the World Cup match has started and we wanted the fan t-shirt. Some of us did not have it. So, we said, hey, let us look for a large, medium, this size, that size. And if you look at it, each one is a different product. Small is a product, medium is a product, large is a product. If I had thought of it as an engineer, I would have said, hey, it has to be one product. This style has to be a part of it. Size has to be part of it. Then men, women, unisex has to be part of it. I would have imagined and created a very complex solution to it. But think about it, such an amazing leader in quick commerce, they said, hey, no problem.  You do not need to complicate it so much by bringing in 10 options into that buying procedure. So, even if it is not little bit, few years older like stripe, even today you will see minimum bible product in action in every part of what you do. Another example from this great product, Zepto. Others said, you need to track. You can see the motorcycle coming next to your street and all.  That is all it has.  They do not expect you to see where the bike is, but they say it comes fast, it comes fast. So, you can always, you know, you do not need to go to the nth feature level. You can always look at it to say, how can you optimize and build with the minimum features. But what good thing that is available in digital today is the ability to build an app is much more easier. And that is what we will see in the demo as well of how we can actually easily build a product using OpenWeaver Studio. But even when you build, even if the product allows you to build something easy, there are some critical considerations for you. You really need to think through in terms of the whole user experience. Essentially, they say humans' attention span is anywhere between a few seconds to about seven seconds. So, in that seven seconds, you have to kind of get the user to say, okay, I looked at it, okay, I think I may find it useful. And then the seven seconds, if they like what they see, maybe they will invest maybe 60 seconds with you. And then if they see something good in that 60 seconds, maybe they will invest 20 minutes on your product. So, that idea that, you know, that user experience, that customer journey, that message structure and call to action, which essentially says, you cannot tell the customer, I have A, B, C, D, E, F, G at one shot. They will say, it is too complicated, I don't have time. But if you say, hey, I have A and B, which is most important to this, wow, let me see. Then you say, by the way, there is C, D and E. And then once they get invested into it, tell them there is X, Y, Z also. So, take steps, you know, that's extremely important in that message structure and call to action. And then supporting things, right? I think being digital today, you know, you can reach a larger scale, softer things in terms of, you know, your brand elements, if you choose a color, you know, do you associate with the color, do you associate with a certain imagery, hierarchy, all these messages cannot be at one level. So, you can say, this is message 1, ok. If you got it, here is message 2, then here is message 3, extremely important. And we will kind of look at this in a quick demo of how we could build this product, R prototype. What we said is Mi Picasso, which is going to be a generative art generative product, which customers will buy, you know, their custom art, you know, using a design first no code tool from OpenWeaver Studio. So, we said we will create, you know, R rapid prototyping for R idea, right? So, Mi Picasso, which is a generative art product that users are going to use to, you know, build their own custom art and buy it online, right? So, part of the course, you can sign up for your free trial at studio.openweaver.com. So, you go ahead and create new, which means let us say we create R product. So, you get a cool interface where you can, you know, kind of create your product. And what did we say? We said, you know, you need to look at form factor, you need to look at design elements and so on so forth. So, most of the digital technology and the only reason that we started OpenWeaver was to make sure that, you know, things are easy for people to build. These support, you know, all form factors are native. So, you do not need to worry about, you know, do I build it for a mobile? Do I build it for a web application and so on so forth? So, it becomes kind of, you know, easy for you to build any product that works on all form factors. So, to some degree, you know, we definitely want to brand, right? So, we want to say, hey, this is my product. So, you will kind of put an header that says, you know, this is what my company is and so on so forth. You can generate your logo also and we will come to it. You know, we will talk about it when we go to the generative AI part of it. A lot of tools today, you know, will help you build your logo online as well. And what do we want to do in this product? We want to call this as, you know, maybe our home page. So, the first page for me, Picasso is our home page and in this page, we want to keep it simple. We do not want to confuse the users with too many things. So, let us take out, you know, for the prototype, maybe we do not need the user to sign up. We do not need the user to sign in and all that stuff. So, let us get rid of whatever is not critical. Maybe we do not have a product also. We just have a service called the generative. So, let us say that is a service. Then what do we want to do? We said we want to kind of excite the user. We want to show them something that says, you know, I am excited about what is here. So, that concept is called as a hero section in a product. It is called a hero or a welcome message that essentially sets the mood for the user. So, you can drag drop and put in a hero section that says what is it that you want to communicate about your product of the user. So, you say, so we are essentially, you know, motivating the user. We are saying, hey, you can be a Picasso as well because we said there is only seven seconds and in that seven seconds, of course, you know, you will have better ideas than me. But think about what is that first call to action.  And then maybe, you know, you can explain it a little bit. Some people may not understand it fully. So, you could kind of, explain it by saying, let us say, you can imagine new keyboard. So, I am kind of, you know, it is taking a bit of trials. Imagine paint showcase. So, we are essentially saying the user saying, hey, you imagine and it paints and you can showcase it. So, we are actually telling them a little bit because if you do not understand it very clearly, you are telling them, you can do that also. Maybe at this point of time, maybe if you have a demo, you can show a demo or let us say we want the user to try it because in digital, in seven seconds, you are telling, hey, you can bring out the Picasso in you and why do not you try it because trying is what we want people to do in the prototype. So, let us say, you know, we call this as try now.  Because sometimes, you know, I think people respond to some of these implicit things pretty well too. So, then maybe what, let us say you are on the page and then we are telling the user saying you can do it. But not all users respond to it. So, this is your happiest path where you are telling the user saying you can try generative art. But maybe some users like to scroll, they like to see, okay, what does it mean, right? What could it look like? So, maybe there you can show some proof, right? You can maybe show some things you can say, you know, some samples that says trending. So, you are saying, hey, there is trending art from this week, which essentially tells them that, you know, someone has built something, someone has painted something like this to you. Of course, you can change these pictures based on what people will do.   So, again, look at the message hierarchy. We kind of put in a header to kind of say, hey, what is the brand about so that people know that there is a company called Ni Picasso and so on and so forth. Then you directly get to the message. You are saying you are meeting that need that makes everyone an artist and they can try it immediately. And of course, softer things, you are actually showing them some examples that says, you know, how you can paint. And this is almost there, right? I think it is almost there for most people, but some people may say, you know, okay, I may not want to paint right now. Maybe later, you know, I like the idea, but I am not going to do it now. Maybe you give them some sort of a subscription that says, you know, you could sign up now and kind of watch it. So maybe if you wanted to paint today, but you know, you didn't have time or you kind of didn't understand it well, you need to go somewhere, you can join a mailing list. So if you look at it, we created the first slice of, you know, what we call the prototype, maybe the marketing version of prototype, you can hit, you know, preview at any point of time. And if you hit deploy, it goes live. So if you hit preview, it kind of shows your, you know, application on what it is.   It kind of works on all form factors that users may end up using. And what it does right now, it says, here is a product, here is what you can do. Here are some examples. And at this point of time, if you just want to keep in touch, subscribe. So three simple things it does. But we still need to do our important thing, right? Our important thing is seeing if the user can paint using Generative AI, and if the user will buy it from you, right? So those are what we called as the needs material. So right now, we have created the connection with the user saying, hey, why should you try this product? Now we will create that step where they can try the product. So since we created a common header, you know, I can just duplicate this page, it'll create a copy of the page.  So this is where the user will paint. So for painting, we don't need this section, we don't need the user to, you know, kind of go through the hero section, we don't need this, we don't need subscribe because the user is going to paint here, right? So the user is going to paint that Generative image that they want. Here you can select, if you want something small, if you want to create a low fidelity prototype, you can select from here. But let's say we want the user to, you know, directly get into the product and paint. Let me pick a Generative AI template for image generation. So this is something that will help them paint, right? So it tells them saying, hey, if you type something here, that picture will come here. So this again is at that static prototype level, there is text, there is input, but nothing will happen so far. And then what do we want to do? We maybe want to kind of, you know, make sure that the user is able to kind of, you know, also buy it, right? We said two things, the user has to paint and the user has to buy. So maybe we'll create a very simple experience for the user to buy. Maybe we'll take an order form and tell the user to buy it from us, right? So it says, hey, this is the painting you can buy from us. So again, still it's a static prototype level. So if you preview this page, it essentially says, hey, there is me Picasso, it has services, and they have something to generate an art and you can buy. But the customer cannot use it right now. It still is at that prototype comma customer model. It used kind of show it to them. They cannot buy right now, but they can of course give you comments that says, hey, I didn't understand this. I wanted something else on second page and so on so forth. So now let's make it a navigational prototype. So right now if you look at it, these are like static pictures. You could have drawn it on hand. You could have drawn it on PowerPoint, on Canva. We drew it on OpenWeaver. Now let's make it clickable, right? So we want to connect the flow. So let's say when you click on services, we want to connect it to the next page, right? So we wanted to go to the page called paint and it opens in the same tab. Maybe when the user clicks on try now, we want to do the same thing on click of the button. We want to go to that page. So on click of the button, we're saying, hey user navigate to page and go to paint. And then in paint, let's say user clicks on home, you want them to come to home, right? So this is done. So now if you maybe let me get excited and deployed, right? So let's say I want to deploy. So this URL is globally available. So if you kind of create and if you're trying it at home, you hit this URL, you'll be able to see this application. So now I click on services. It takes me to this service and I have a full prototype where I can say generate, I can submit, I can buy or I want to go home. I can do all these things, right? But still it is what we call as a static prototype. I think on home we said. So now the flow is there. The users can kind of go through it. Users can navigate, understand what your product does, come back, look at what others did, joining or mailing lists, so on so forth. Now we need to add the magic behind it, right? So we want to make sure because this is what we said is okay. It's a great first step. You created an amazing prototype for something that is going to reinvent a market like XC or RTC in a very large way. But it is still what I call as a navigable prototype or interactive prototype. Let's take it to a minimum viable product in next few minutes so that the user can use it and maybe even buy from it, right? So what do we need to do that, right? We need the generative technology for that, right? So what is there? We said we want to add something called user gives a text and you want to create an image. So let's add something called as a text image and what the no code platform does it makes it so easy.  It gets added and you can do some magic with it, right? So we said we wanted to create a logo because we didn't have a logo. I wouldn't digress too much, but I just wanted to show for your startup, you can, your prototype, you can do that. You can say create a square logo.  So it's created a beautiful logo for you.  So this can become, you know, your startup. So you can tell it to do anything. You can say, put that text in it for me, do something for me, it'll do all those for you and you can create. But that's not the fun. Let's focus on the user's need matter, right? We're not focusing on our vanity of what our logo looks like. So let's say we added this resource and this resource is going to be used by the user and the user is going to paint something for herself and, you know, buy it off you. So we need to create some logic, right? So when the user wants to paint something, we create a logic that says let's call this image gen flow. So this flow is what is going to trigger, which is going to, you know, do that back end magic that is going to create that image for you. To create the image, what do we need? We just need one simple technology called text to image. Anyway, we added in the resource.  So we're saying once the user starts, we need to generate an image and using the text that the user inputted, and you're done. You give it back to the user and then she will buy it in that order form that we created. So first simple step we're saying, hey, which page we wanted from, we wanted from the page called paint. In that page called paint, she's going to enter the input. And the moment you select a one page called paint, it gives you what all is there. These are from the order, the delivery address. We don't need delivery address for generating the image. Maybe once you want to kind of, you know, get to the get to the order, you can use the delivery address, but let's keep it simple. You know, we can delete whatever is not required. So we'll just use the text input that the user gave, the prompt input 54, which is what the user will type saying, hey, this is the picture that I want. So you have that picture. And then you just need to pass it to the text to image. We're saying, I want to do text to image. And the data is coming from the page input called input 54. And of course, as you do it in a slightly longer, you spend two, three hours, you can actually give right names to it. So it is easy for you. For want of time, I'm just using the default names that are there. You think that is the input and output automatically comes. You don't need to do anything. And then at the end, what do you want? You want that output. So you took the user's input 54, you sent it to the algorithm that generates the picture. And then you need to send it back to the user. So at end, you're going to say, I need a global variable that image that the user created from this action called text to image should be available to me at the end. So that's all. So now the logic has created that backend. We just need to stitch it to the front end. From the front end flow, we need to make sure that you're able to generate it from what the user says. So what have we not done? When the user clicks on this, we need to trigger that action. So when we said, try now, we said go to this page. In this page, when the user creates generate image, we're going to say, unclick, execute a flow. And what is the flow we created? We created a flow called image and flow. So when the user clicks on this button, it is going to trigger that nice small logic that we wrote in the backend that says call generative AI and take that input 54 that the user gave, which is this, right? So this is called input 54, the input 54 that the user gave and generate that picture. So now it is doing that. So the picture needs to come here. So currently, if you look at it is a nice picture, but it is still a static picture. So we want the user's image to come here. So let me give it a title as well. And let me remove this static picture and make it dynamic. So we wanted to come from the backend. So we make it dynamic. We select a flow output. And this flow is called image and flow. And we use the data from there. We are all done. So we created a page, the home page with a marketing message that says, you know, this is what you can do. If you click try now, it will take you to the page. It shows you what others have done. If you are interested, you can subscribe. And if you go to the next page, we said you can unleash what you do. And if you type something here, your picture will come here. And you can order from here and it will reach home, right? So simplest technology, hit deploy. Your full application is ready. So let's say, you know, I am the user. I say, wow, I want to bring the Picasso in me. Let's say I want to try now. And I want to be zen like. So let's say, so that's the art that I want to create. So let the, let the generative AI digital technology work for you. It goes out. It starts looking at, you know, different things. And it creates a beautiful unique image. So this image is absolutely unique.  So this is created for you. So as a minimum viable product, we said this is what it is later, you know, when we said prioritizing needs make, you can add, you know, you can add modifications, you can add signatures, you can add swatches, colors, so on so forth. And the user can say, hey, I, this is ABC, ship it to my home and hit submit. They will buy the product from you. So you're all set in terms of, you know, we created a nice high fidelity prototype. We added the base needs make criteria of having a generative AI that generates art. And we also had the needs make criteria that this art can be delivered to the user and they can pay for it. So we kind of went out and created a cool little minimum viable product that the user is able to use. So now you have to think in terms of customer feedback, you know, I think, so we spent a lot of time and energy in creating that minimum viable product. And where we all go wrong is we say, man, I created something amazing. That's what I told you before we started. Do not love your solution. Love the customer. Love the customer's problem. There'll be many other ways to solve it. So expect the first thing to fail, you know, like we launched this me Picasso site in a few minutes. Customer might say, hey, I don't understand or maybe I wanted to speak and it has to draw, you know, I wanted to pay online or something, you know, you may get a lot of feedback. So expect multiple iterations possible, launch to the smallest segment, right? Because sometimes that's something that we do very wrong. Also, we get so excited because now with this platform that you have access to, you can launch something that is available global. So many of us do that mistake that says, hey, I created MVP. Now let me send it to, you know, 50,000 people, then it becomes very difficult for you because 50,000 people say different things because each of them may come from a different persona. So maybe find, you know, maybe the first 100 people from a very clear persona that you have mapped and then get feedback from them, you know, I think as your first few iterations of product, it is extremely important for you to do that. And with each iteration measure, saying is the customer's feedback improving and is the customer succeeding because for us succeeding as customers to generate more images, customers to add to delivery for all those images, that means they're successful. So one, of course, the feedback keeps coming in, but then you have to look at the needs met criteria that says how many customers have actually generated and how many have actually placed the order, which will actually give you a good idea of what it is. And at very early stage, it's good for you to have a few thousand customers that love the product than maybe tens or hundreds of thousands of visitors who don't understand what your product is. So extremely important for you to kind of, you know, scale gradually as you succeed because in a digital product, it is easy to open out to a lot of people. But opening out a product that does not meet the needs is not a desirable outcome for us. The last thing is as you scale, so now let's say we created an amazing minimum viable product, it's good with a few thousand users. Now take the next step of going to the tens of thousands of users or customers who may allow this idea. So there we have found digital marketing to kind of, you know, as the product is digital, digital marketing also is amazing. So think about social, social gives you again, you know, you will find user groups. So for example, you will find art appreciation group in maybe a age segment or in a geographical segment, you can join that group and put a message saying here is an amazing service or product that I have.  And most important, you can expect advocate from this. Like we said earlier, if someone says I generated this migrating Buddha in front of a temple, if someone shares it and says, hey, this is built on me Picasso, you will get your next thousand customers directly. So you can use social media for getting your customers, for getting crowd testing as well as, you know, for word of mouth advertising from your first aid of customers. Then also look at other angles. You can look at, you know, maybe doing knowledge articles because in digital marketing, one of course, you will directly promote your product. You can also indirectly use, you know, content. You can write blogs, you can write newsletters to say, you know, in 2024, these are the art trends that are there. Can you, you can create art using trends like these. You can use YouTube to run a video channel to show, you know, maybe the top 100 arts that has been created on your product. You can show to, you know, users who can get excited to say, how did you do. So you can do a lot of those surrogate content-led marketing as well to scale your product to, you know, next tens and hundreds of thousands of customers. So we looked at, you know, a good concept that says, you know, rapid, very important because our runways as startups are short and winning with the customer because if the customer does not win, our product or service does not win. And then we looked at it to say, you know, how do you, you know, use the digital way to create a rapid prototype or what is called as a minimum viable product where you can actually give it to the customer and make them succeed using OpenWeaver Studio. I would recommend all of you to kind of, you know, create your trial ideas while you go through the course and, you know, take your product to the first 1000 customers as well as, you know, the next lakhs of customers and win with the customers. So all the very best and talk to you soon. Cheers. Bye-bye.


What's up guys we're back with another Ghost Hunters video and not just any Ghost Hunters guys. We have another chance at the Duelist Genesis Stardust Dragon. This one's for Volk. Volk got this on Ruxen34.com. He wants to pull the Duelist Genesis Stardust Dragon. It's gonna be crazy. Hopefully we can pull it. We also have a giveaway. I'll be giving away this majestic red dragon from the tin. We actually pulled this. It's a little dusty because I've actually been used it. I've just been displaying it up there but this guy was pulled straight out of the pack.  Be subscribed. Give us good juju in the comments to pull the Ghost Stardust Dragon. Hopefully we will do it. And speaking of giveaways, if you are one of those people who's like why do you never announce the giveaways? Where are the giveaways announced? YouTube community tab. Check it out. I'm gonna post it on the screen. Go to my channel. Click community on the little tab at the top and it'll bring you to all the winners. I announce all of them on post there. Follow me there. We don't follow me but like follow that I'm posting there. You will see who wins the giveaways. Make sure you claim them so I can give them to you. Let's get into this booster box. Ghost rares. This is gonna be insane. Purchase on Ruxen34.com. I often have packs. Sometimes booster boxes like this available. You guys can pick up and then we can open some epic stuff.  It doesn't have to be opened on the channel though. You guys can open it. You know buy it and have me ship it to you as well. So that works. Let's see if we can get this thing popped open. There we go. All right 24 packs. I just have a good feeling that Stardust Ghost Rare. This might be the day. This might be the time that we finally pull it. We've pulled. What have we pulled? We've pulled Ultimate Rare. We pulled that last time. We've pulled Ultra Rare. So now's the time to get the Ghost Rare. I am ready. Genesis Light Sworn Miner. Psychic Rejuvenation. And Fighting Spirit. Oh Mecha Bunny. I thought we had something behind it for a second. Okay. We have 24 packs. There are no first edition the Dual Genesis booster boxes. So this is as good as it gets when it comes to a booster box. The first edition only came in like 10s and pre-releases. It was weird. It was a weird time. So that's why the Stardust Dragon first edition Ghost Rare is so expensive. Turbo Booster. Graceful Revival. And a Psychic Snail. Okay. Kanoga. Battletoom. Also 5D's packs were not reprinted so they don't have like a ton of reprints. So like the biggest expensive cards are pretty expensive. Like Ghost Rare Unlimited Stardust is still pretty crazy. Even though it's an unlimited Mirror of Yatta. We got the small piece Golem. Oh the Ruxen Special right off the bat. And a Kinkaboyo. This is the guy that's worth like $8 or $9. I thought he was, I was like, uh, not the card you're looking for. And I was like, wait, this is the card you're looking for. This card's worth a ton of money. Okay. So not a bad start with a pretty good Super Rare right there. I mean, that's not bad. All right. We have Genesis Light Sworn Miner. We got the Orb of Yasaka. Yasaka. Yeah. Light Sworn Barrier. Psychic Commander. Mind over matter. Oh. Is this sticking? What is this? What? You guys see this? This reminds me of the Enemy of Justice. That was horrifying sound, but somehow it didn't like come off or anything. Wow. A Psychic Overload Ultra Rare? Wow. Somehow it didn't damage it at all. That's a relief. I thought it was an Ultimate Rare. If you guys remember, if you've been here, you know, since the old days, when we were opening Enemy of Justice, nine boxes, we had these boxes where the Ultimate Rears would stick to the card in front of them. I actually graded like four, four or five tens out of this. So that was interesting that that happened, but it was weird. Genesis Light Sworn Miner. That probably means this box was not properly stored at some point. Psychic Commander. Light Sworn Barrier. And a Herbal Orange Light is a few dollar, not common, Rare. That's a pretty good pull. So not a bad start. I think Psychic Overload is not a great Ultra, but good Super, good Rare, not bad. Now we just need an Ultra Rare, Ghost Rare, Secret Rare. We will see what we can get. Psychic Rejuvenation. Juve Fighter. Cyan Pulse. Beast of the Pharaoh. And an Izanami and a Space Gate. Okay. Noisy Nat. All right, guys. Do you believe that we can get the Ghost for our Stardust? Ghost Hunter Video. Let's see if we can pull it for him. I believe Psychic Rejuvenation. Juve Fighter. One day we're going to pull this, and it's going to be today. Beast of the Pharaoh. Maiden of Macabre. And the Mime Protector. Oh, can I Mime Protector? Can we do this? Can we pull the Great Stardust Dragon? Dr. Cranium. Remote Revenge. Book of Eclipse. Medium Peace Golem. Grapple Blocker. Oh, it's doing it again. Synchro Magical Android. If there's a Ghost Stardust stuck to something, I'm going to flip out. Okay, somehow these are sticking. That's very weird. Fortunately, it's not damaging the cards. Magical Android. That's a funny one. This is the very first set with synchros. This is the very first 5D set. The very first time they had synchros. Not the first Ghost set. They had a Ghost before synchros, but some of the most iconic Ghost rares are from the 5D era. Remote Revenge. Here we go. Book of Eclipse. Medium Peace Golem. Telekinetic Charging Cell. So we've already pulled two Ultras out of this box. That's kind of weird. They're just leading us up to the epicness at the end. They're like super rare, a couple Ultra rares, and then it's like boom. Ultimate Rare. Ghost Rare. Seeker Rare. All that stuff. Small Peace Golem. Crebons. Tricky Spell 4. Psychic Commander. And the Tricky. Tricky Spell and the Tricky. Judgment of Thunder. And good old recycling batteries, guys. I wonder how many Dualist Genesis packs we have opened in general, like total. I bet it's been close to 288, the ratio for Stardust. Tricky Spell 4. Psychic Commander. Trap of Darkness. And a Mind Protector. Metbunny. A noisy nap. Last pack on the right side. Stardust Dragon. Let's get the Ultra, the Ultimate, and the Ghost. I guess that's technically possible, right? In one box it'd be insane, but we've got Dark the Dark Charmer. John Garage. I think Dark the Dark Charmer is a good one. Fish Depth. Then we got Noah's Ark. Nice. Oh, Power Filter. Another sticky one. We got ourselves an Ojama. They're in the washing machine. That's really interesting. They're hanging out in the washing machine. Okay, another foil. Not bad. But not the big boy. We are looking for a large pull. A very large pull. Also want to remind you guys, you guys didn't see. We're opening a full box of Retro Pack 2 when I hit 100k. Plus more. Subscribe. Subscribe for that epicness. Overworked. Turbo Booster. Tricky Spell 4. Defense Draw. And a Gladiator Beast Warcher. This is an okay one. Pretty decent card so far. We haven't pulled too many duds. That's nice. I don't know, Power Filter might be a dud, but they're in the washing machine. Come on. All right. A few more packs. A lot more packs. Like 10 more packs actually. For the Ghost Rare. We have yet to hit a secret. An ultimate ore ghost. We got an oyster mice to wait. What is that? You guys see that? Look at that. What is that? There's a big old crease in it. It's like right down the middle. Oh, it's like that. It's like in the Tactical Evolution Special Editions where they had that. Based on what was a lot worse on those. That's interesting. It's a little bit on there. Watch there be a ghost in here. Okay, there's nothing on that one. That's good. Tricky Spell 4 and Mind of a Matter with a Shingro Deflector. Okay. Twin Shield Defender. That was an interesting little print error there. Looks like they got a little dent at some point. Not a good print error for sure. Oyster Meister. We got the Needlebug Nest Peace Golem. Tricky. Herald of the Orange Light. That's a good one. Sword of Kusanage. Twin Shield Defender. Okay. A few packs left. Ghost Rare Stardust Dragon is waiting for us. Right? Right? Remote Revenge. We got a Jute Fighter. Oh, Rock's the Special. Dark through Dark Charm. That's not bad. Ezename and Gladiator Beast. A Quest. Ghost Gardener. Oh, oh, don't drop it. We almost dropped it. That would definitely have a Ghost Rare if we dropped it. Remote Revenge. Jute Fighter. Light Wave Tuning. Oh, Dark through Dark Charmer. Maiden of Makov. And an Intercept. Oh, they keep getting stuck. Intercept with Riza, the Storm Monarch on the artwork. Nice. Pretty cool. You can take control of the Tribute Summon Monster. That's definitely an anti-monarch card. 100% Remote Revenge. Crebons. Medium Peace Golem. Junkabedish. Grapple Blocker. Uh-oh. Uh-oh. I can't even tell if there's a card there. There is, I think. A Goyo Guardian. Oh my goodness. That's a good pull. Also, that's a third Ultra. What? What? That's not usual. Okay, somehow we got that off. That was like plastered on there. Wait a second. Okay, we've pulled, never mind. Why did I think this was an Ultra? Wait, that's the only two Ultras. Okay, we've pulled two Ultras. Okay, Light Wave Tuning. All right, another nice Ultra stuck to it. That was scary. That was really scary. But we got it off without damaging anything. Okay. Next back. Only Ultras and Supers so far. No Secret Ultimate or Ghost. I'm really scared if there is a ghost in here. That is going to be stuck on their Crebons. Oh, Ruxen Special. Jung Barrage. Telekinetic Charging Cell. And a Telepathic Power. I think they just want me to Ruxen Special. They have the cards sticking together. That is not fair. Okay. Come on. Beast of the Pharaoh. Oh, there's something weird going on here. Something stuck back there. Beast of the Pharaoh. Light Wave Tuning. Dark the Dark Charmer. Weirdness is going on. Oyster Meister. The Tricky. Oh gosh. Oh, it's a fusion. Ultimate Rare. Medium Beast Golem. All right, check it out. Somehow these are coming out clean. And I'm horrified about the next one. Ultimate Rare. Okay. You don't always get an Ultimate Rare in these. So that's pretty cool. I don't think it's a fantastic one, but it's definitely pretty cool. Medium Beast Golem. Okay. Okay. Not a bad box so far, but the only way to top it off is with that Stardust Dragon. Let's do it. Ghost Rare. Beast of the Pharaoh. Light Wave Tuning. Dark the Dark Charmer. Oyster Meister. Trap of Darkness. And a Psychic Snail. Okay. Global Tide Jump. A few packs left. Like three packs, I think. Three total packs left in this box. Like button for luck, guys. If you're enjoying the video, go ahead and subscribe. 100k is going to be crazy. That's all I'm saying. Junk Barrage, Nose Art, and Gear Town. Okay. Two more packs. This one's a little bent up. Hopefully they didn't damage the Ghost Rare. Get that open. Okay. Being a little weird here. We've got the Orb of Ysaka. Genus. Psychic Rejuven. Junk Barrage. Golden Chinner. Uh-oh. Uh-oh. A Counselor Lily. Literally every the duelist genus' opening has Counselor Lily in it. That is crazy. We always pull that one. And it's always an end too. That is weird. Okay. Final pack. Ghost Rare in the pack. Not stick. Not sticky. Not stick. There's no stickiness. Okay. Mirror of Yhanna. Like button for luck. Here we go. Small Peace Golem. Turbo Booster. Light Sworn Barrier. Big Peace Golem. And Ghost Gardener. When it came off smooth, you knew it was nothing. Okay. All right. So that was a fun box. Not bad.  That's pretty good. No Secret Rare though. That was pretty fun. Hope you guys enjoyed it. If you did, like the video. Subscribe for more. We've got more epic openings coming up. And that's it for this video. I'll see you guys later. Peace.


And we're now turning carbon emissions, combining them with air and turning them into plastic. So we launched this with Sprint back in May. So this phone case is actually over 50% captured air and carbon emissions. And what's really, really exciting about this product is it's actually less expensive than its alternative, which would be made from fossil fuels.


Okay. Hello, everyone. My name is Robyn de Moura. Thank you already. I'm glad to be here. So today I will be the spokesperson for myself but also Audrey Banex with whom we prepared this talk together but who couldn't join, unfortunately. So I will talk about interdisciplinarity, multi-tasking and what working in the interdisciplinary research environments does to decision-making processes and also to open research tools development. So the context I'm speaking from is a lab called the Media Lab of Sciences Po which is an interdisciplinary laboratory and which explores the relationships between digital technologies and society. So this lab is made by individuals who come from very different backgrounds the interdisciplinarity. But this interdisciplinarity has two scales, so to speak, because also each individual is himself or herself the spokesperson for a variety of cultures of intellectual interests and also of lines of expertise. So here is what these people look like. Here is where Audrey stands and here is where I stand. So all of these people do things together and because or thanks to this diversity they have variegated activities. So they do social sciences inquiries of course but they also teach and produce tools whether they be code libraries or other shelf applications. And often one person is involved in more than one of these activities. So they do these activities in a variety of contexts. Some of them are clearly and precisely defined like collectively funded research projects. Others like PhD research for instance are more open-ended and have less defined boundaries and aims. So we build tools, papers and experiments for a variety of publics. So first our colleagues and fellow researchers but also students and several professional groups like library specialists. All the activities we do are linked and feed each other and this talk will be a description of how at Media Lab we cope with this intertwining. It will focus on describing what are the consequences and modalities of doing things in the same place and often with the same persons. Underlying this description I will make is a methodological reflection for which I hope to foster some discussion which is the fact that we all know methodologies coming from the industry and or software production culture like agile methods, UX research, UX design the difference between proof of concept and the production ready products but my question is how do these established methods and labels dialogue with our specific research context. So to do so the description will focus on two nodes of methodological tension and two sets of practices. The first one will be the question of writing in social sciences and it will address the relationship between prototypes and products research and development or what it means to be at the same time the users and the makers of the software positions we make. The second will be the question of social inquiry on the web and it will address decision making processes and the question of how we cope with the separation of concerns and responsibilities between individuals within this interdisciplinary context. So first we'll look at how tools making and experiments are intertwined and how the mix of context described before allows to trace a complex interweaving between inquiry practices, experimentation and open research tools stabilization so to speak. So to situate this concern I will address the question of writing and publishing in social sciences which is my privileged area of research and interests. So the past decade has been marked by a lot of brilliant initiatives, technologies and tools that try to establish new standards to leverage digital technologies in the service of better editorial processes of polymorphic publishing but also sometimes to question what it means to write digitally as a social science researcher. So in that regard Medialab has been structured since its inception 10 years ago by the pedagogical activity of what we call controversy mapping. So controversy mapping is a specific kind of sociological inquiry which consists in describing the different point of view and at stake in a social technical dispute or controversy like for instance ungrowth as you will see in the example I will show. And in these courses students are asked to produce as outcome of their websites of their research sorry not reports not papers but websites. So why do we ask them that? It's because by using hypertext they are allowed to express the multiplicity of point of view which controversy description requires. So first reason hypertext and the second reason is that it allows students to write closer to the inquiry documents that they use for instance images, interviews, official documents by staging them directly inside the websites. So in parallel to this activity, these pedagogical activities Medialab was also structured by the practice of data scapes which are research endeavors that consists in building at the same time data sets, research questions and a web publication which combines hypertextual navigation and data visualization. So these two prior experiences gave practical and intellectual basis to another project in the lab called AIM. AIM stands for an inquiry into modes of existence. So it's a project grounded in 30 years of field study by a single researcher which is called Bruno Latour and this project consisted among other activities in creating a platform allowing to read both the text written by Bruno Latour but also to browse the documents, so videos, images, references he gathered during his career and used to produce his arguments. The platform also allowed readers to participate by proposing contributions in the same document-based writing mindset. So on this project I was a PhD student at the time in a situation of participant observation and with the designer of the project who is called Donato Ricci we quickly started to think about ways to reuse and translate this platform, this structure or to fork its way of writing close to the materials to other research projects. For that we wrote a grant request that asks funding to build an open source technology to do that but it was rejected, twice. But it was not a big deal because at the same time I published the first results of my inquiry on the AIM project in a co-written paper with members of the team Donato Ricci but also Christophe Lecair and Bruno Latour and it was not just an account of my results but also an experimental format on itself based on what some called scroll detailing which means that things appear while you are scrolling and reading the article and it was, so to speak, a way to test some ideas that we were before asking money for but didn't have. So this first experiment was also the occasion of first technical experiments, a custom document generation system using Mardin and Biptext languages to allow us, so as a team of co-writers to directly write the article but also its visualizations specification and to iterate and collectively interact in this kind of writing. So in parallel in the lab at the same time controversy mapping courses were scaled up because of their success and this asked to develop an open source solution that would allow to build social sciences websites in an easier way while not being captive of commercial platforms and also while mitigating technological obsolescence problems that we saw arising with the students' productions. So out of this the team made a solution which is called driving and which consists in allowing to turn a Google Drive folder into a static website. So on my side after having left Medialab to continue my PhD I developed on my side some processes, I developed some of the processes I observed and tested around the M-project and it came out as something called Peritext which is a series of hypothesis about what document structures and modes of presentation would address better interweaving between empirical materials writing and scholarly publication and to make a meaningful use of polymorphic, polyformat contemporary context of scholarly publishing. I mean by that publishing on the web but also in various editorial contexts. So to do that I wonder what would be a thinking of writing at the contextualization of some resources and I wondered what would happen if researchers had the opportunity to specify more finely those contextualizations and how they should look like depending on their position in the text but also depending on the output formats. A second hypothesis was to think about these resources as all possible points of departure for writing activities instead of just considering texts so chapters and sections as the backbone of what scholarly publishing could be. So this would allow to generate a variety of editions for a given production and to very points of view and the roles for the documents being produced depending on the research stage or its aim. So once I formulated this hypothesis I wanted to test them but that would have required the insight project of creating yet another ecosystem of JavaScript libraries so I did it and started to experiment with this at first but after my, so yeah, these are an example of the modules that are inside this ecosystem. So after my PhD funding ended I came back to Medialab to cope with the change of controversy mapping scaling up and this was eventually the occasion to actually test this hypothesis on a real use case. So out of this came FONIO, which is this time collective effort and which is a collaborative editor, so open source, everything is open source in what you see here, a collaborative editor allowing to write digital dissertations and download them as static websites. So it's built for social sciences in the sense that it allows to write footnotes to use bibliographic references and the diversity of resources and it allows to write hypothetically through interactive lexicon and internal links. It also allows students to design their websites within the interface. So while doing that my PhD continued at the same time I developed a new editor called Ovid which is a single user, more experimental and advanced tests of the peri-text hypothesis. So Ovid is a turn towards practices which are not necessarily relevant for students, for instance data visualization, but also advanced grocery production like entity definitions, places, a person, etc. And it also allows to go further in the design of the outputs and to create multiple editions both for screens and printers. So these two projects of course were developed together and have a lot in common, but their code base remains separated mostly because they address different contexts and goals. So FONIO has been used by students by more than 2,000 students so far and now they are conducting and doing their own experiments on top of that framework. And concerning Ovid, a document which happens to be a hypothesis should be out someday soon. Here is a prediction from the students. So now I will zoom at a closer level and rather than talking about temporal dynamics I will focus on relations between people at stake in tools development. How does the decision about our tools evolution is made and implemented? And for that I will take the example of a software called HiveRazor. But before speaking about it, I must speak about Hive. So for which HiveRazor is a kind of interface if you want. So Hive is a tool made for a very specific research practice which embeds in its working strong methodological assumptions. It's a tool allowing researchers to build corpuses of web pages about a specific topic. So for instance I don't know coronavirus or palm oil. So the idea is that these web pages are selected and regrouped by researchers as web entities which represents the different actors of the issues. So organizations, persons. And then analyze the relationship between actors through the relationships between web pages corresponding to them. So it is quite quantitative in the sense that it allows researchers to really choose which websites they want to add to their corpus. But also by analyzing the contents of these web pages to generate automatic processes to fetch new website suggestions and then work iteratively between the machine and the researcher. So now HiveRazor in this qualitative frame is a student oriented interface to Hive. And it allows to browse the web while constituting the website's corpus. And students have a way to both read the websites and see how their corpus evolves through visualization. Sorry for my voice. So after two years of use we decided that we should continue the development of the project and make it evolve in harmony with what it was used for. So to do that we started with a series of conversations with all the persons in contact with the app. So students, teachers, but also engineers, researchers and so on. So we discussed with them in which context they use HiveRazor but I also asked them to perform some activities while being interviewed and encouraged to explain what they were doing, understanding and feeling. So from that a series of remarks were defined then turned into cards and collectively discussed with all of the actors participating to that redesign. Out of these discussions some wireframes were made and from these wireframes these propositions came out new discussions and new iterations. So these meetings were interesting because they revealed the diversity of interests and priorities within the lab. They allowed to carry a peaceful negotiation process but also to reveal the diverging attachments and concerns at hand in this process. So who are on this battlefield? Which is the redesign meeting. We have the original designers or the spokesperson who designed a clue methodology and its embodiment in the tool and don't want the tool to evolve in order to risk of confusing the initial methodological message so to speak that the tool is supposed to carry. We have also the developers who are worried about refactoring avalanches that would be triggered by new propositions and evolutions of the tool. We have also of course the teachers who are using this in the classroom and they want to voice out non-conventional uses of the tool such as for high-brother teaching through the tool how such engines work or using it as a tool for building scholarly cytographies formatted in the complying bibliographical norms. We have also researchers who use the tool even if it's made for students initially and they want to be able to discuss and twitch methodological embeddings in the tool. We have specialists who bring their also their strong archiving culture and background to the discussion.  So people whose role is to promote, explain, document and who are actually articulating the tool with different practical contexts. So two remarks about this situation. The first is that these mediating roles are quite important to allow distributed negotiation concerning the evolution of the tool. But second is also that several persons that you see listed here are in multiple positions and this is the feature of an interdisciplinary laboratory. And this is very useful to mitigate misunderstanding and also to enhance dialogue between functions and responsibilities who are however not shared. So as a conclusion developing from the field means being situated in a diversity of negotiation processes between experiment and query and software stabilizations but also between multiple interests, voices and responsibilities. That way of doing allows us to improve the relevance of the tool we make but also to foster important conversations, scientific conversations concerning the methodological assumptions that we embed in the tool we make. It also allows to create an environment, an open environment of tools which correspond to each other. And to finish I will just add that one of, so I present two of the parts of this environment and one other which is called TESEL will be presented tomorrow by Arnaud Pichon at length and I will end on that. Thank you. So is this available in other languages than French? So both HiveBrother, Phonio but also Ovid are bilingual in French and English in their interface. Thank you.


I'm so happy to be back in Saskatoon today at the St. Anne's Senior Citizens' Village. It's great to be here with provincial minister Hindley. Thank you very much for being part of this today. Each Canadian deserves to be safe, regardless of their age or where they live. The pandemic was very difficult for the A&E, especially those who live in long-term care centers. It's important to have been there for them, but it's always important to continue to be there for them. Here at St. Anne's, the facility just upgraded its rooms and washrooms and made the building more accessible. That's good news for people who live here. As we recover from this pandemic, we must all continue to work together to improve care for our seniors. That's exactly why we're here today. We've reached an agreement with the government of Saskatchewan through the Safe Long-Term Care Fund. The federal government will provide $32 million to the province to help improve care for seniors. This investment will support, for example, safer dining practices and increased cleaning and housekeeping. It will also support enhanced screening protocols for staff. During the past years, I've had the opportunity to talk with many long-term care workers to thank them and hear their stories, but also their concerns. I know that for caregivers and managers here at St. Anne's, teamwork is at the center of everything you do to support residents. Well, our government will continue to be here for you because it's clear that better conditions of work for caregivers lead directly to better conditions of care for residents. Now, including Saskatchewan, our government has signed and announced agreements through the Safe Long-Term Care Fund with nine provinces and territories. Saskatchewan, BC, New Brunswick, Newfoundland, Nova Scotia, Ontario, PEI, Yukon and Northwest Territories. These investments are making a real difference for people and for caregivers. We're also continuing our work with the other provinces and territories to be there for seniors right across the country. Whether it's with investments to support residents of long-term care centers, to do research and innovate in the field of brain health, or to improve access to health care for rural and remote regions, we continue our work to ensure that no one is left to account and to build a better future for everyone. One of the things that has characterized these past two difficult years is the extent to which Canadians have been there for each other. We got reminded of that during the pandemic, but I know that we also know that that's the path forward. As we deal with new challenges, as we continue, as this pandemic runs its course, we need to continue to be there to support each other, to listen to each other, to be there for each other just like Canadians, particularly here in Saskatchewan, have always been there for their neighbours.