Gestion de patrimoine Di Iorio

Épisode 7: Une discussion sur l'automatisation

Avec l'invité spécial Mohannad El-Barachi, investisseur et créateur d'entreprise, cofondateur de l'entreprise Wrk

Disponsible uniquement en anglais

And so when we started thinking about automation and we started thinking about businesses and how they deliver their work, it became very clear that there's a gap in the marketplace, that people use this term, "automation," to mean a lot of things. In tech-- well, you guys will know this, but perhaps for your listeners-- technologists have a great ability to overcomplicate and oversimplify everything.

Either everything is so unbelievably complex that you have no idea what it is or how it'll work, or so unbelievably oversimplified that it doesn't tell you the full story of what it will do. And so you end up having these buckets of terms that emerge like AI and machine learning and big data, but when you start really digging beneath the surface to try and understand what they do, it's a lot of just hubbubs.

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Hi, everyone, and welcome to episode seven of Behind the Numbers podcast. As always I'm here with my co-host Jeff, my associate portfolio manager.

How's it going, Rob?

I'm pretty good, thank you. How are you?

Good.

And we have a really interesting guest who I'm going to intro in a second. But before I do, I just wanted to reiterate why we do these podcasts. It's always based on making our clients and everybody around us into better investors. That's essentially what we're trying to do, educate and teach. And we do this through various forms. The podcast is the latest form where we have a very interesting guest. And today of course, we have somebody really special on the program.

And we also do blogs. We're just about to release our latest blog, which is going to talk about the metaverse. And today's kind of related to that. And we also do educational videos. If you haven't checked out those as well, they are available on the Behind the Numbers education part of our website. And we also do webcasts only for clients. So if you are a client and you're listening to this, please check out the webcast we sent you a week or two ago, which essentially explains how we're managing the portfolios and what our takes are besides what you see on your quarterly packages.

So the inspiration for these podcasts is always from clients. So we field a lot of questions in client meetings. We do advise some very smart people mostly in the business community, many in the tech community. So a lot of the questions that we've been getting lately last quarter were mostly about inflation. Now this quarter, as we see emerging growth starting to come back, we're getting questions on automation, AI.

This is the week of-- it's actually November 18. Rivian just did their IPO a few days ago. EV stocks are going crazy. So we're getting a lot of questions about those as well. So it's all part of what we're going to tackle today.

Well, without further ado, I just want to intro our guest, Mohannad El-Barachi. Mo is a co-founder of SweetIQ. Mo is also a serial tech entrepreneur, active venture capital investor, and most recently he co-founded a company called Wrk, which we're going to talk about today. Mo, welcome to the Behind the Numbers podcast.

Nice to see you, Rob. What's up, Jeff?

Good to see you, too, man. Jeff doesn't talk much, Mo. So please, you have to understand how he operates.

I see him on the screen so I have to acknowledge his presence.

Perfect. So Mo, we have a ton of things to tackle today. And I think we'll start with Wrk. So obviously we're going to talk about automation. Wrk is an automation company. But in your words, what is Wrk and why did you recently found the company with somebody else and why?

Yeah, so I think it's important to just get a little bit of background and history to understand why this is important now. Whenever you're building technology companies, timing is almost everything. Facebook five years earlier or five years later wouldn't be Facebook. And the same could be true about basically every company in the world, but very specifically with tech because there are various trends that emerge at specific inflection points in the industry. And it just so happens that automation right now is the hot one.

So historically speaking-- so I've been in the tech industry for almost 20 years. And my background is computer science. I came at this industry with the lens of a programmer who knows how to build code and build software. In 2009, 2010, when I co-founded my last company, SweetIQ, we were in hypergrowth mode after a couple of years. And we had all of these internal manual processes that needed to be scaled. The company was doing really well. We were building listings for clients. So the data that was powering the little pin that appears in Google Maps was being powered by my software for businesses all over the world.

And so the challenge is synchronizing this data across systems can be done using automation, using what's called APIs. But in some cases on platforms like Bing or even Yelp, there was no such API. So we had to do manual preparation of information in Google Sheets and loading data into forms and so on, just work that was just very manual and repetitive.

We tried to build some automation for it but the challenge with a lot of these businesses and these platforms is they change over time. And so maintaining this internal code becomes a challenge. And we needed to find a more systematic way of being able to have automation. There really was no solution in the marketplace. And similarly after we got acquired by Gannett in 2017, we saw that the problem that we had with 200 employees was multiplied multitudes at 14,000 employees across 120 offices, that people use this term "automation" to mean a lot of things.

In tech-- well, you guys will know this, but perhaps for your listeners-- technologists have a great ability to overcomplicate and oversimplify everything. Either everything is so unbelievably complex that you have no idea what it is or how it'll work, or so unbelievably oversimplified that it doesn't tell you the full story of what it will do. And so you end up having these buckets of terms that emerge like AI and machine learning and big data. But when you start really digging beneath the surface to try and understand what they do, it's a lot of just hubbubs.

So the reason that we started Wrk is because we really couldn't find a solution to help us deliver our work at scale. And we'll dig into what this means a little bit later. But the reality is automation right now was one of the hottest trends in the tech industry. Timing is key. Organizations, especially post-COVID, are trying to find ways to maintain business continuity despite all the disruptions. And the reality is a lot of the work that we do behind a computer screen today can be automated using technologies that exist. But the challenge is how do you decide which one to use? How do you integrate it? How do you just adopt it internally within the organization? That's effectively why we started Wrk.

So we're going to come back to that. We're going to talk about how automation and AI is going to change everything. We've already been speaking about that for years. But I think today having you on is going to be really good. So we'll talk about that. We'll come back to that. We'll come back to the metaverse. We'll talk about autonomous, how they're all kind of interrelated, and highlight the importance of understanding what real automation is and what you're talking about versus kind of like the fake stuff that's out there now. But before we do, what are you working on right now at this moment? Is there something in particular that you're doing at Wrk or something you're really excited about?

Yeah, so the Wrk platform is actually not specifically an automation platform. The Wrk platform is a work delivery engine that sits as a layer on top of automation. So automation is a tool in our shed and not the only tool in our shed. And so going back to the point I was making earlier about these big buckets where people like to sort of throw certain types of technologies, automation is in its purest form a piece of software where you give it an instruction and it'll just do that same step over and over and over again.

So it could be something like filling out a form on your website. And imagine that you have an Excel spreadsheet with 10,000 entries and you need to submit every single one of these entries into this form 10,000 times. Well, you can build a little robot to do that. Or taking a bunch of data from an image and data from Excel, generating a chart, and putting it into a Google presentation or a PowerPoint presentation.

So these are sort of manual repetitive tasks for which you can build automation. What we decided to do is we built the software that will use bots along with humans to build a hybrid automation model. So Wrk will deliver your work for you at scale using a library of pre-built, pre-configured robots. And some of these robots actually will deliver the work purely through automation.

And others will do it through a combination of humans and machines together. Because the one thing that we've come to learn is in today's day and age not everyone is fully ready to trust the machine 100%. So we provide the layer of cognition on top of the machine to make sure that you are finally sort of comfortable with the results that are being outputted. So that's what we're excited about right now.

So I'm glad you explained that. Because a lot of people don't understand what we're talking about when we say automation. In the recent podcast we talked about how we're not too concerned about inflation over time. And everybody's screaming about the price of containers and the price of lumber. But in reality there's forces at play here. And your company is essentially at the forefront of this where automation brings down costs of everything.

Because once things are automated, we don't need humans to do these tasks that are monotonous, right? And we can scale. Scale is a big word. But you can essentially scale everything you do on a daily basis. So we're going to talk about how we're investing in companies that automate now. You know one of the companies, the public companies. We'll mention it later. We'll talk about that. But why don't we talk a little bit about the importance of understanding kind of not to get fooled with what seems to be automated and what really isn't? Maybe just go a little more into detail about that.

Yeah, well, first I want to mention something relative to what you just said in that I think there's an apprehension with automation in that it's going to displace the human. And that's not true. I think that it's important to put it in perspective that automation is there to remove the mundane and monotonous so that the human can work on higher level tasks.

That's right.

If you have an employee that's sitting there on staff all day and all they're doing is copy pasting or they're filling a form or they're generating the same document or report 10,000 times a day, it's a waste of their God-given talent, right? If you can remove that burden from them and allow them to work on something more meaningful, you're optimizing your workforce, not reducing your workforce. I think that's a really important distinction. Because people are afraid of well, what's going to happen to my staff? The robots are going to render humans useless. That's not true at all.

So that's aspect number one. Number two, in terms of cost reduction, It's actually really quite obscene. So I'll give you a very specific tangible example. We have a company, without naming names, that is in the wine monitoring business. And so they have sommeliers that will help you manage your cellars of wine, so if you're a restaurant and you have thousands and thousands of wines or you're a private collector and so forth.

So in order for the sommelier to be aware of what your stuff is, because it's all digital remote, you have to take a picture of the label of your wine. And then they recommend the temperature that it needs to be stored at and so forth. They manage something like about 100 million wines annually all over the world. But they have these sommeliers that are sitting there trying to match a label that you're going to send from a picture from your phone across a database that they have. And it would cost them about $1.20 per wine matched for the sommelier to start doing their work.

We've now taken on the job of just doing the matching of the images, bringing down their cost from $1.20 to $0.17 per wine matched. So when you reduce your costs by 90% and now your sommeliers who have spent years and years and years training on the stuff that they've gotten trained at, now again, you've optimized the output and the yield of your business. And then your margins are really quite significant, right? So I think it's just important to set that foundation.

Specifically to the question around AI, look, like I said, technologists have an ability to overcomplicate and oversimplify everything. AI is not the it all and be all. You have to understand that these are categories of study. AI is not some random machine that's going to come and figure out everything for you.

In order for you to have true artificial intelligence, you need to do something called building a data model, which means that you take a very large set of information-- phone calls, the way that people click on certain things, written scripts that you have transcribed, and so forth, and you feed this massive amount of data into the machine. And the machine starts to learn how to detect something.

So for example, one of the largest applications of artificial intelligence is what we call optical character recognition. So that's you give me any document in any format, a PDF, a handwritten note, and the machine will be able to extract the text out of that. That's an AI-trained model that can do that. So this example, as you can see, is exactly what AI is. AI gets trained to do one thing, extract text from document, extract sentiment from something, generate documents at scale that do something specific.

So it's important to state that AI and machine learning is a one direction thing. It'll do one thing really, really well. So I just want to frame that when you're thinking about AI, don't think that it will solve for everything. It'll solve for one thing. Now you can layer multiple AIs together and start building. But it takes a long time for you to be able to train the machine into a machine to figure things out in itself over time.

We're not yet at the level where AI can self-learn. There are companies that claim that they can. I have yet to see an end-to-end application that is fully done by AI. So I think it's just important that tech organizations deploy very aggressive B2B sales playbooks. And they go after the jugular, right? They'll try and find your pain point. And then they'll give you these big topics and say AI because it's overly complicated and you're not going to understand what it means.

And they'll tell you AI is going to solve it. Because the news out there is AI solves everything. That's not true. If you want to cut through the BS, ask them to show you a real tangible example today and not something that will take six months to train a model to do the thing that you need it to do. So just be careful around consulting AI, which is what most of the AI is today, and actual true AI, which is a machine that has already been pre-trained to do the thing that you need.

Really cool. Mo, so I wanted to actually circle back to something that you kind of opened with there just talking about-- because it is a concern we've heard from clients when we talk about AI or when we talk about replacing, I guess, some tasks and RPA and things like that. We often get the question, like you mentioned, about like, is this going to replace human workers? What's this going to do to unemployment rate? What's this going to do to economic factors, which obviously play a pretty important role in the economy of today?

So I wanted to share some data that I kind of recently saw in an article that I was reading. This is automation, but this is maybe more, let's say, the older version of automation where you kind of use robotics to just do things at larger scale, so thinking of like the agriculture industry or something like that, farming, which is one of the, believe it or not, one of the industries that probably adopted robotics and things to replace humans in certain roles earliest and most extensively.

And so there was actually a study that was done that was looking at the purchasing power of farm workers, So. The actual labor of human workers on farms over the last 50 years as automation has kind of taken over a lot of the tasks. And it's actually, believe it or not, farm workers are one of the few areas where, let's say a manual labor job has actually kept up with the overall inflation since, I think, the data went from back to 1950, and looked at now and looked at the wages. And basically it's actually kept up with inflation, which is not something you can say about a lot of, if you want to call it, more manual labor areas of the economy that are still there.

So it's quite interesting. So obviously that all comes down to productivity, right? So this stuff, this automation or these machines that they've brought on, have just allowed them to be so much more productive that they still need workers. They're still employing almost as many people. But the income that's being generated by the companies and by the farms is so much higher because of productivity that the actual purchasing power or the wages they're getting paid has actually kept up with inflation.

So it's a pretty interesting kind of thing. And in the same study, they were also looking at which major companies or which industries today have the most, if you want to call it, robots per employee or per 10,000 employees. And at the top of the list was Amazon, which is, I think, they had something like 3,000 robots, if you want to call them that, per 10,000 employees. And it hasn't replaced human workers. Amazon's one of the largest employers in America.

And that's actually a really important point, Jeff, as well as you think about the younger generation that is coming into the workforce today. They're not interested in doing that type of work. They're not interested in doing the menial, the repetitive, the mundane, the tasks that will pay the minimum wage and a little bit more. That generation unfortunately suffered through all of that, like the older generation that is now sort of going into the latter stages of their years. But the younger generation coming in would rather stay at home, mine Bitcoin, or work on NFTs, or do gig work than go and do that type of a job, right? So I think it's important that we recognize that trend as well.

Absolutely. So we gave examples of business process automation, robotic process automation, AI, machine learning. We talked about how that kind of keeps inflation in check, increases productivity of workforce-- Jeff just mentioned that; Mo, you gave examples of it-- and makes task-driven jobs obviously more obsolete so people can focus on better and more important, meaningful things, which we've been talking about.

So why don't we talk about how-- so Wrk is a private company, right? Just want to make that clear. We didn't say that at the beginning. We wish it was a public company. It would be good for you. And we can invest in it. But it's still a private company, which is awesome. One of the fastest growing companies in the country for sure in your space in automation, so congrats on that, Mo. We're going to talk about how we play this in the public space, OK?

So now we're going to talk about a company called UiPath. And Mo, I'll give you credit for this. Because obviously we talk to you often. And you brought UiPath to our attention when the IPO-- obviously we see all the IPOs. But having you on to understand more of the relevance of this company has been good for us. So maybe Jeff's going to want to talk about UiPath, kind of what they do.

There's a good example on the website where they take a healthcare service kind of provider and they say, OK, normally you'd call in and it'd take five minutes to assess what the issue is. But if we use RPAs, or as Mo called it, robots, to assess the situation, it takes one minute. So again, productivity increase, less time on menial tasks, more time on meaningful tasks. So maybe Jeff, you talk about where we see UiPath going and why we're interested in this company.

Yeah, for sure. So from an investment standpoint, like everything, it was something that we got interested in because it was kind of brought to our attention. And it's in a space that we've been looking for, or a trend you can say, a secular growth trend, that we've been interested in for a while.

And then when you started kind of looking at the company or just looking at it today, for example, I think it has around a $28 or $30 billion market cap probably right now, and I think sales growth of 40% that's projected to continue for several years into the future, and I think even faster if you look at what's the portion of their revenue that's recurring, so like the ARR, Annual Recurring Revenue, that their revenue is actually growing faster than 40%.

So we look at different things. Kind of one thing that, I guess, shows the success that they have with companies is one, not only-- I think they have 60% or over 60% of the Fortune Global 500 companies as customers right now. So that's obviously a pretty good customer base to be dealing with, big partnerships with companies like Snowflake and other things like that.

And what really drew our attention or kind of highlighted the success that they're having-- at the end of the day, pleasing customers and growing a relationship with customers is very important-- they have 144% dollar-based net retention rates. So basically what that means is their average customer will spend 44% more each year as time goes by because they're expanding their relationships. They're adding new processes.

And the whole thing about automation, what's really interesting about the field, and in their particular case, RPA, is basically the total addressable market that they can hope to capture, it only increases over time as the sophistication of their software and as their abilities to complete more, take more complex tasks that still need some intervention now, maybe in the future that doesn't. That's no longer the case.

So they can almost create more of an addressable market as their product develops. So a lot of things kind of got us interested in it. And it's a name we added more recently. It's down quite a bit from the IPO. I think there's several kind of factors that were at play for that. But we're quite optimistic about it. And we added it maybe a couple of months ago.

Yeah, and of course, this is the purest play, right? There's other ways to invest. You can invest in the company who makes the AI chips like Nvidia, et cetera, which is another holding we have. So not here to talk about holdings, but just giving live examples of real public companies that you can invest in that are in the space.

Yeah, so UiPath is an interesting one. So when we started off Wrk, obviously we went out and did a ton of due diligence in the space. And what became clear is there's sort of a handful of players that are really worth looking into. Don't get fooled. RPA is yet another term for automation. RPA stands for Robotic Process Automation. And all it is is imagine you have a virtual-- well, your computer and a mouse and a keyboard that moves on its own.

And so what RPA will do is it'll record the work that your employees are doing repetitively and then replay back those sessions over and over again until it learns. So imagine that you have the call center example. And so when a call comes in, you have to go in your CRM or ERP and look for the phone number of the caller or the name and then pull up their record. Well, you can build a little macro effectively to do that. And that saves maybe a minute from the rep's time. But over tens of millions of phone calls, you can appreciate that that's quite scalable.

So the challenge with RPA today is that it has been predominantly really only been deployed by very large corps. So yes, the total addressable market for this is, in fact, infinite, in my opinion. Because it's every single organization that is going to automate at some point. But in today's day and age, it's focused predominantly-- it used to be the Fortune 100. Then it was like the Fortune 1,000. Now it's like the Fortune 5,000. And slowly it's starting to become more and more into the big mid-market and then eventually you go into the mid-market.

I actually met the chief strategy officer of UiPath, who is partially originally from Montreal, by the way. He's Moroccan-Canadian but moved to Romania a long time ago. And so they started off in Romania against a very large incumbent called Blue Prism, which was based out of the UK. And both of these organizations really represent a pretty large sort of portion of the market share.

And the reason that they're so successful is because they can go into these large organizations, deploy a piece of automation that will boost productivity like no one has ever seen before. And so in the same way-- you have to understand the decision-making process of these large organizations-- there's a hot trend that emerges. The CEO, CFO, CIO, comes in and says, we need to invest in x, in big data, in machine learning, in security and whatever.

And so lately the trend has been in automation. And they go and say, OK, Gartner, OK, whoever the McKinsey or whichever management consulting firm they're dealing with, which organization should we go talk to? And then they're always going to name the top 3. And to UiPath's credit, what they've done is they've built a platform that is slightly easier to use than the others, that has a little bit more bells and whistles, and that is slightly newer than their British counterparts at Blue Prism.

And so what ended up happening is they got a little bit more adoption. And then they were smart in trying to cover an international market a lot faster than their incumbents as well. And so when you compare UiPath versus Blue Prism, Blue Prism that is older and was generating more or less the same level of revenues, just got acquired or is in the process of being acquired by Vista for $1.5 billion. So that gives you the scale of difference of what these guys have been able to achieve.

But to Jeff's point, and it's the same thing that I'm seeing in my company as well, when we launch with a client, within the first three months we see that they go from one workflow to three to four workflows within that first three months period. So it's a land and expand strategy, which means for them growth isn't predicated on net new acquisition of clients, it's also just going to be internal growth from existing accounts, which traditionally in software, expansion of revenue internally within an organization is so much cheaper in terms of cost of acquisition.

Because you're not going out there and sending new reps. It's already an existing client and they're just growing. So for me, looking at the multiples of an organization like that versus a traditional [? SaaS, ?] we're going to see that skyrocket over time. That's why I'm in this industry. And to your point, Rob, maybe the stock is down since the highs. But you look at the volume in terms of the amount of trading that's been happening on that stock, it's doubled over the course of the last couple of months. There's going to be a lot of activity on this stock for sure.

Yeah, and I love how you're giving the high level management view of things. We talk about the "what" a lot. OK, this is what this company does. This is how they do it. But you're giving another perspective, which is amazing. That's why we invited you on. So let's finish off-- because we're already at 26 minutes, and I think you're a busy man and I appreciate the time you allocated to us-- let's finish off talking about big companies. And so we'll talk about ours. We'll talk about RBC. And so you were invited at a roundtable experience with our CEO, is that correct?

Yeah, yeah, it was a good call.

OK, great. So I want you to talk about-- I don't know-- what you felt and what you saw there and what you heard, if you got to speak about automation at all in the banking sector, and where you think that's going.

Yeah, I'll try not to disparage too much but--

Oh, go ahead. It's fine. It's our podcast. This is not-- no, I'm just joking.

[INAUDIBLE] So first off, I think your CEO came off as highly intelligent. And I think he's very smart in terms of understanding and knowing the global trends and the macro patterns and all the stuff that's going on. But the reality with RBC, like almost every single large organization that is sort of too big, is shifting the course of direction is very, very difficult.

That's right.

And I think that the general consensus is-- like, I pressed him pretty hard on where is the bank going to take a stance on things like cryptocurrencies, on the evolution of automation, on the trends that are happening in the marketplace with gig workers. We are, for example, leading the charge in transitioning how individuals get compensated from a time-based model-- I pay you $50 bucks an hour-- to a delivery-based model. I pay you $50 bucks when you deliver the thing that you need to deliver.

And we feel like that over-optimizes for outputs because if you're very good at what you're doing and you deliver the thing that I need in 5 minutes versus an hour then why should I pay you less for the hour that you've given me if your yield is much higher than someone else? And so I prodded hard on those. And I've been doing this across organizations left, right, and center. And the answer is almost always the same. When that trend becomes large enough, we'll sort of get there, which is almost always too late.

So look, it's like everything. Moving a big ship is very, very difficult. Having CEOs who are willing to take a big risk at an early stage like that almost never happens, which is unfortunate because organizations have an ability to make massive shifts in the ecosystem whether it's business or cultural or local. And so I think that corporations have an obligation to help create the catalysts for change to happen.

And so when I was speaking with your CEO I was trying to prod him to make any kind of public statement to say, this is the position that we will take on x. And I don't think it'll ever happen. And it's unfortunate because RBC is if not the most recognizable, definitely one of the most recognizable brands in Canada, one of the ones that has so much clout and credibility that people will follow it if someone just had the-- what's the politically correct way of saying it-- but the gall of actually taking a position and standing behind it in the same way that Elon is doing, for example, and leading the charge on a few things.

Yeah, we love Elon. And I agree with every point you make. Maybe one day when I'm CEO of the company-- that's not going to happen. Maybe Jeffrey. One day when Jeffrey's CEO of the company things will change. But until then we'll continue to manage our portfolios. Mo, you've been awesome today. Thank you so much. This is one of the best podcasts we've had. I always say that. But this time it's true. And I also want to just say that good luck with Wrk. I think Wrk is-- obviously we're going to follow it very closely. We're friends with Mo.

So if anybody wants to speak to Mo, get in contact, reach out to us. We can definitely hook you up. Also just want to say that check out our other content. We are hell-bent on communicating with our clients and making sure that you guys have the best perspective on what we believe and how we're going to execute on what we believe. So this podcast is part of that.

I also want to mention just a little plug for philanthropic reasons. I am going to be-- don't laugh, Jeff-- I'm going to be dancing with the stars on February 7th for the JFK Foundation. Mo is nodding his head. And so yes, along with the boxing and the cycling and everything else that I try and do and the drums-- by the way, I play the drums, just a plug for myself-- I am always trying to do things that I'm uncomfortable with. And this is definitely something I am uncomfortable with.

But I'm going to be raising money for a great cause. So check out LinkedIn. We've posted on it. If you guys want to donate, please go ahead. And so if not, just laugh when you see my videos and wish me luck. Because this is one of the most challenging things I've ever done in my life. So thanks again, Mo, for being with us. And we'll see you guys next time.

Thanks, Mo.

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Podcast

Épisode 13: L'épisode "kibitzing"

Épisode 12 : L’intersection de la technologie et les soins de santé

Épisode 11: Pourquoi tout entrepreneur accompli a besoin de conseils financiers

Épisode 10: Le guide complet des régimes de retraite individuels

Épisode 9: Une discussion sur la gestion de portefeuille et la stratégie

Épisode 8: Une discussion sur l'esprit d'entreprise, la philanthropie et ce qu'il faut rechercher dans une équipe de conseillers.

Épisode 7: Une discussion sur l'automatisation

Épisode 6: Une discussion sur l'avenir de l'économie

Épisode 5: Réponses aux questions fréquemment posées par les clients et discussion sur la croissance séculaire

Épisode 4: Une discussion sur l'avenir des soins de santé

Épisode 3: Comprendre votre exposition aux droits de succession américains et les stratégies pour les minimiser.

Épisode 2: Une discussion ouverte sur les impôts, la dette, le Bitcoin, et plus encore.

Épisode 1: "Pourquoi" investir dans la croissance ?

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