218. Teaching Truths & Tactics: Live Lessons From Stanford in Capetown

[00:00:00] Matt Abrahams: You can catalyze community through compelling communication. My name is Matt Abrahams, and I teach strategic communication at Stanford Graduate School of Business. Welcome to this live episode of Think Fast Talk Smart, the podcast. The power of community to enhance learning, entrepreneurship, and connection is truly amazing. I witnessed this firsthand at the recent Stanford SEED summit in Cape Town, South Africa. I invite you to listen in as Stanford professors Jesper Sørensen, Christian Wheeler and incoming GSB Dean Sarah Soule share their thoughts with and answer questions from the close to five hundred SEED members in our audience. So let's get started.

[00:00:46] Jesper, thank you for joining us. Excited to have you. When you and I spoke earlier on the podcast, we talked about strategy and telling stories around strategy, and I know that you've done some recent work that continues that line where you've done research with your colleague, Glenn Carroll, on the use of analogies in being effective in the work that you do? Can you share a little bit more about that? 

[00:01:10] Jesper Sørensen: Sure. As many of you know, Glenn and I published a book a few years ago, and the paper that we recently wrote on analogies, we think of this as the missing chapter. The chapter that didn't get done in the book, and we use analogies all the time. So we say this is kind of like that when we're trying to explain something, right? So we think sound is like a wave, right? There's a classic way of thinking about explaining principles in physics, for example. And we use this all the time in business as well. So I think what most familiar to people would be, we use it in startup pitches, right? All the time. So we'll say, my company is the Uber of, or something like that. And then what we're doing is we're trying to persuade people that our organization and that analogy has the same potential and maybe even the same business model as the source organization. So that's a much more common way of reasoning, I think that people do.

[00:02:03] It's particularly powerful for idea generation and it's also particularly powerful for persuasion. As a form of communication it's really quite compelling. Uh, at the same time, it's super dangerous as a basis for strategic thinking. So what our article is about is basically about how can you think about what makes for a good analogy from a strategic perspective. And I think one element of this is we tend to think about analogies as being about what we call horizontal comparisons. So we're capturing features and comparing them to each other, but we actually think that the more important thing to do is what we think about as the vertical relationships, which is really about what's the logic underlying each. When you say that your business is the Uber of something else, what is it about Uber's business model that you are saying applies in your business? And so the article really tries to flesh those ideas out. 

[00:02:56] Matt Abrahams: I like that idea of, it's not horizontal but the vertical logic that's really important. That answer was as good as your previous answers, so thank you. Sarah, I recently had the pleasure of hearing you give a lecture where you talked about some recent research you were doing on how corporations respond to societal issues. Would you share for all of us a little bit about that research and what we can take away from it?

[00:03:18] Sarah Soule: Sure. Absolutely, Matt. One of my PhD students and I got very interested in corporate political statements, and some of you maybe have made these statements before. Many of you have read these statements before, but we were interested in these as a growing phenomenon, at least in the US case. And we collected a number of these around a lot of different social and political issues, and we started to notice some very interesting patterns in some of these. And in particular, one of the things that we noticed is that usually organizations and companies, they usually put forward and put out very positive information about themselves. In extreme cases, we may call this greenwashing or some other kind of pinkwashing and so on, but typically we think about companies putting forth something positive about themselves.

[00:04:10] But in these political statements, we noticed that companies were doing something very different, and that we came to call confession. They were releasing negative information about themselves with respect to whatever the political or social issue is. So for example, in the environmental space, rather than putting out something that might resemble something on the spectrum of greenwashing, companies would put something out talking about how dirty their supply chains are, things like this. And so we came, as I said, to refer to this as confession, company confessions, but we were also interested in understanding how people, the general public, consumers, might react to those statements. And so we conducted a number of online experiments and asked people to rate these companies with respect to different dimensions of corporate social responsibility.

[00:05:02] And the way this worked is that we created some vignettes, some sort of fake statements that a company might put out based on some of the company statements that we had collected. And we asked people a series of questions. And what we were manipulating in the experiment was the extent to which they confess something negative about themselves versus neutral versus positive. And what we found was that companies that confess something were rated more highly with respect to corporate social responsibility than those that just put a neutral statement out or a positive statement out. But there's a little wrinkle in this finding, and that's that if the company was confessing something that was particularly surprising or might seem counter to what an individual's priors might be, they were discounted very heavily and believed to be not at all responsible with respect to corporate social responsibility.

[00:05:58] So for example, if we have a lumber company that confesses to something with respect to deforestation, they get a bump in how people perceive them in terms of their level of corporate social responsibility. But if the lumber company confesses to using sweatshop labor in an emerging market, that they are discounted very heavily. So in a sense, I think what we are picking up on is hypocrisy, and that's that consumers and general public is very astute at picking up something that feels like it could be hypocritical or feels like it could be an empty statement that doesn't connect to their general business and so on. So that's the gist of what we've been doing.

[00:06:39] Matt Abrahams: Which I find really interesting. I'm curious, do you think that this notion of corporate confession is something that companies should be thinking about in terms of how they present themselves in the world? 

[00:06:51] Sarah Soule: I think I would say that, and this is maybe obvious, but it's astounding to me how many of these corporate statements we saw, which really did seem a bit performative and seem quite hypocritical, I think the takeaway for me is that we can tease out something that feels like individuals sensing that there's something awry in what the company is saying. And so I think what I would say is that when one, if a company is going to use this strategy of releasing corporate statements, they really need to be very careful about what they're doing. That whatever they're confessing to is directly related to their line of business, their values, their mission, their strategy, and not weighed into political issues that are far afield from where they play and what they do. 

[00:07:34] Matt Abrahams: So stay close to what you know and what you do.

[00:07:36] Sarah Soule: Yes.

[00:07:36] Matt Abrahams: Thank you. So Christian, you co-teach a class on spontaneous management, I love that idea, where you blend ideas from your area of study and improvisation. What are one or two of the ideas you can share that you teach in your class that can help all of us in the ever-changing environment we live in today? 

[00:07:53] Christian Wheeler: Sure. I'll say a couple of things. We get used to postponing judgment. We have a tendency to rush to categorization, to assume that we understand things before we really do, because it saves us cognitive energy. It makes us feel that we have an understanding and a confidence about the way things are. But what it takes away from us is a curiosity about things around us, the ability to notice things that might peak our interest, and it also leads to inaccurate judgments. We also have a tendency to judge ourselves often in a moment. Right now, I may be having some self-talk thinking about whether this is a good answer or people liking this answer. I don't know. This is not the time for me to be judging this answer because the more I'm in my head, judging this answer I'm giving, the less I'm thinking about what I'm gonna say next. So I can listen to the podcast when it's out, reflect on my performance, think about how I could do better, but now is not the time for me to be judging my answer.

[00:08:47] Then I would also say another thing is being present. A lot of the class talks about capitalizing on serendipity, about being attentive to nonverbal signals from other people. This requires that we are in the moment. If we're honest about how we spend much of our time, it's like this, right? Staring at our telephones. You can't be present if you're staring at your telephone. And what it does is it has all of these effects on being able to capitalize on chance circumstances, being able to notice things that might capture our interest, but it also takes us out of this interaction that you're having with other people. And research shows that not only does it diminish the quality of your interactions, but it actually lowers your cognitive capabilities. If you have a telephone in front of you, switched off, then if it's out of the room, so it doesn't even need to be turned on, just merely having it present distracts us from the moment, and it lowers our ability to think carefully.

[00:09:39] Matt Abrahams: So our phones are making us dumber. 

[00:09:41] Christian Wheeler: Absolutely.

[00:09:42] Matt Abrahams: Interesting. So I want to dive a little deeper. I, 'cause I see being present and non-judgmental sort of together. I mean, what are some things we can do to be more present oriented? It's one thing to want to be, it's another thing to actually do it. 

[00:09:55] Christian Wheeler: Well, a simple thing is put your phone in your bag, turn it off. But I think more, we often use our cell phones as a sort of security blanket, right? The moment we have an unoccupied second of time we have this sense of existential, oh, here I am alone with my thoughts. What will I do now? You can overcome this feeling. And in fact, I was alive at a time when we didn't have such devices and we just had to wait for the train with nothing to do, and we were okay. 

[00:10:23] Matt Abrahams: And you can actually have a conversation with somebody instead of,

[00:10:26] Christian Wheeler: You actually can. And for example, that even though many of us have the hypothesis, the lay belief, that it would be unpleasant to have a conversation with a stranger at the train, research shows quite the opposite. That if you strike up a conversation with someone on the train, I think they did this on buses in Chicago, you like that conversation not only more than you thought that you would, but that it improves your quality of life. So having this ability to interact with your environment in an uninhibited way from your devices is something that it takes a while to get used to, but it can improve your quality of life.

[00:10:56] Matt Abrahams: Excellent. And I wanna pick up on a thread that Christian mentioned about not in the moment ruminating on what's happening. There's a difference, to my mind, between rumination and reflection. A lot of us get in our head in the moment when something doesn't go right and that prevents us from being in that moment or what comes next. But it does make sense after the fact to reflect. That's how we learn. So that separation between rumination and reflection, I think is important. But I want us to spend a few moments talking about AI, artificial intelligence, and I'm curious to learn from each of you, how is it impacting the work that you do with your students, in the research you do? Sarah, do you mind talking about AI first for us? 

[00:11:35] Sarah Soule: Sure. Happy to. I think probably everybody in the room understands that this is impacting all of us in ways that we probably even a year ago, didn't think possible. But a few things that come to my mind in terms of research, one of the things that I've been using it for is to run some of these corporate statements that I mentioned through an AI to pick up on the sentiment of the speaker, the writer, and to see, and we haven't done much with this yet, but we plan to look at the emotionality of these statements and see if we can pick up in any way that might impact how people rate these companies in terms of their level of corporate social responsibility. So that's one way that we're using this in research.

[00:12:14] In teaching, I was thinking about this just the other day, I was preparing an exercise for use in a classroom for people to map their social network. And so I prepared the exercise and I said, well, I wonder what ChatGPT would say about this exercise. It gave me some amazing suggestions for reflection questions, things I hadn't even thought about, and I've been doing this for many years now. So that was humbling, but also very helpful as well. I've asked ChatGPT recently to create menus for me of higher protein, vegetarian or plant-based diets that meet a certain number of grams of protein per day. And I was, again, astounded at how quickly it would spit out these very, I haven't tried them yet, but very reasonable sounding kinds of ideas and diets. And so I think that this is, while at times terrifying, I think it's also been very helpful, in at least those aspects of my life and work these days.

[00:13:14] Matt Abrahams: Excellent. So you're using it in research, in your teaching, and even in your personal life. Christian, how are you leveraging AI for what you do? 

[00:13:21] Christian Wheeler: Yeah. I don't use it so much for my teaching for reasons related to what we were just discussing, but I do use it quite a bit for my research. A new thing that I'm excited about is having participants engage in conversations with AI. So some of the things that we do, we are interested in having people think about their attitudes or their thoughts or their beliefs in a different way than they might spontaneously do so, or ordinarily do so. And back in the day, what we would do is we would give them instructions to, to think about it in a certain way. But what you can do now is have people have a conversation with the chatbot. They will encourage them over a series of rounds to think about something in a particular way. We'll ask them follow up questions designed to have them have this sort of realization about their thoughts or beliefs. And so I think that's an exciting new direction for manipulation of psychological constructs.

[00:14:10] Matt Abrahams: So you're using it a lot in research and actually having people using the tool to help people reflect on their communication and their thoughts. Excellent. Very good. Jesper, how are you using AI? 

[00:14:20] Jesper Sørensen: I would say the extent that I use it, I use it in, in teaching. So one of the things that I have always struggled with in teaching is examples and ways of illustrating ideas. And so I was recently working with some colleagues on a, developing a new course where we needed to come up with some kind of hypothetical examples to be able to explain certain basic principles in economics and strategy. And I'm just terrible at doing that myself, right? I just, I cannot do it. I can give you all the theory in the world, but being connected to the real world is really hard. So, that's because I like my phone. So stay away, Christian. Leave me alone.

[00:14:58] But I did use ChatGPT for this, where I basically wrote a prompt saying, okay, you're an expert in this particular topic, and I think in economics for example, and then I had like a broad outline of what I wanted. I wanted to be a luxury hotel that had an HR management problem and was thinking about incentives and all that other stuff. The amount of creativity that just popped up like, immediately was amazing. And I feel more comfortable using it in that way 'cause I do worry about these models hallucinating, but these are fictitious examples. So hallucination is fine, right? But what we want is to make sure that they can be used to illustrate the concepts that we're doing. And I thought that was actually a really powerful use case for me. 

[00:15:41] Matt Abrahams: I like how you're leveraging its ability to be creative, to be creative for you. In the work I do around spontaneous speaking, I'll often have my students go to an LLM if they're preparing to give a presentation, or some other interaction, and have the LLM serve up spontaneous things for them to respond to. For example, my students might be giving a presentation and they can say, imagine I'm giving a presentation to fellow MBA students. What are three questions they might ask? And then the students practice answering those questions that are served up. So it serves as a way of generating questions so they can practice. And talking to someone else on the podcast who is an expert on AI, we had a similar conversation, and the recommendation he gave me is, if you don't know how to use it, ask it and it can tell you. I told ChatGPT that I was interested in doing this particular assignment. How could it help me? And it gave me lots of interesting ideas about how it could help me. And we actually executed on a few of those. So sometimes if you don't know how to use AI, maybe AI can help you figure out how you could use it.

[00:16:42] So this will be our final question for the panel. Christian, let me start with you. I'd like for you to share something you're working on that you're currently really excited about, and I'll give you some extra credit, imaginary extra credit, if you can apply what you're working on to everybody in the audience and how they could leverage it. 

[00:16:58] Christian Wheeler: A lot of my research projects are a bit in the weeds, so I'm gonna give you something very simple, that most of you should be able to apply. For a lot of the things that we do, we need to generate a title or a heading to what we're doing, and we have a choice to make. We could frame that title as a statement, or we could frame that title as a question. So for example, if I have a newspaper article about green tea, I could say green tea has health benefits, question mark. Or I could say green tea has health benefits, period. Which one is better? Question mark. I thought so too. You're wrong. Yeah. Isn't that interesting? As it turns out, statements work better. We've tested this over multiple domains. We've tested it with actual newspaper headlines, millions and millions of newspaper headlines. We've tested it with things like Reddit posts and seeing how many up votes they get. We've tested it with academic articles and seeing how many citations those academic articles get. In all of those cases, question marks perform worse than statements. The effect isn't huge. If it were too big, we would be a little suspicious of it. It's a little effect, but it's a reliable effect. 

[00:18:05] Matt Abrahams: That was a great answer, exclamation point. I don't know how that plays, but good. Jesper, what's something you're working on that we can all benefit from? 

[00:18:13] Jesper Sørensen: We recently at the GSB, we've been, I've been working with some colleagues on developing a new asynchronous course called Stanford Business Essentials, and this is a product that's targeted at early career professionals. So these are basically people who have graduated from university or something like that, and they're starting out in their careers. And one of the inspirations for this product is I look at my own children who have been in this situation and they are just befuddled right by what's going on in their organizations. Like, why do things happen this way, et cetera, et cetera. I think this is a great tool for really getting people up to speed. 

[00:18:50] Matt Abrahams: I was recently being interviewed for a Korean outlet because my book was just translated into Korean, and the interviewer told me that at the university level, they are teaching a class on how to make phone calls because students at that age don't know how to actually speak on the phone to somebody. And so this notion of providing foundational skills, I don't know that we have to get that foundational, but really rings the cord for sure. Sarah, how about something you're working on? I know you've got a lot going on.

[00:19:20] Sarah Soule: Coming back to the project that I mentioned before about these corporate statements, one of the other things that we've been looking at is whether or not elements of those statements will induce people to donate money to the particular issue at hand. Also to write voluntary letters on behalf of the issue at hand. And so we wanna try to see if these things can mobilize people to do something. So if we have a statement, a fictitious statement about a lumber company, and it's just confessed to deforestation, will people who see a confession actually be more willing to give money to an environmental cause, or write a letter, volunteer to write a letter, a longer letter.

[00:20:01] But one of the things that we've been playing with comes back to something that you have taught me, Matt, and that is the what, so what, now what, framework that you all now also know. And it turns out that framework has been used in studies of getting people to mobilize, and it's usually referred to as a kind of collective active action frame where you name the problem, you say why it's important, and then you mobilize people. You ask people to do something. So we are looking at that exact same structure and wondering, and looking, and we will test, to see whether or not that particular structure is more or less likely to induce people to mobilize on behalf of the cause. So that's something new, another piece of that project. 

[00:20:45] Matt Abrahams: That's really fascinating. Persuasion is so interesting, but I like that you're playing with, does the structure of the message actually impact? One of the things I'm researching and interested in is the role of in strategic communication. So if you think about it, everything I've talked about while I've been with you is about fidelity, accuracy and clarity. But often we use ambiguity to achieve our goals. Think about this. If I cooked a meal for you, I've already told you I'm a lousy cook, and I give it to you, and I say, what do you think? You could tell me the truth. It's awful, but that might hurt my feelings. So you might say something wonderfully ambiguous, like, I've never quite tried anything like this before, right? And so you fulfilled the strategic obligation of responding, but doing so in a way that doesn't hurt my feelings. So I'm really interested in times where fidelity isn't the goal, where we're purposely ambiguous and what that means for our communication. So thank you for all of you sharing, not just your insights into your research, but also for sharing ideas that we can all deploy.

[00:21:45] So this is the fun part. So I'd love to invite those of you who have questions to wait for the microphone to show up. I see a hand over here. 

[00:21:54] Audience Member 1: Hi there. Thank you to all the panelists. Wonderful to hear all the different insights. My name is Gary Struble. I run a media company in Namibia. And just perhaps linking back into the AI question, you are all quite specific about answering it in a way about how AI makes your life easier, but I imagine AI is also going to make your lives much more difficult if it isn't already. And I perhaps just address the question to anyone on the panel, is from an academic perspective, from perhaps even strategizing as to how academia remains relevant in how it's currently structured, how are you grappling with the problems of AI in grading students and creating the funnels that academia relies upon?

[00:22:35] Christian Wheeler: Well, my challenges are perhaps a little different from some of the others. Most of the assignments in my class are self-reflections, and I want them to think about what that experience was like. What did they learn from that? How are they going to apply that? And perhaps not surprisingly, there's a non-trivial subset of participants or students who have AI self-reflect about an experience that the AI did not have. So that's a challenge and it's a little discouraging. So, the, the solution to that is to have them do it in person and have them talk about it. But I think it is a subset of a more general problem that I think you're hinting at, is that people offloading the intellectual work that they might do, whether it's introspective intellectual work or creating a new product off the AI. And in my case, it's just, um, preventing introspection. 

[00:23:24] Sarah Soule: I think another space that we worry a lot about this is in using some sort of AI tool to write academic papers, even if the research findings are in fact valid and true, and actual research findings, asking an AI to actually write the results up is worrisome. And so I think those of us who serve as journal editors, who serve as reviewers, have to be ever more vigilant to try to figure out ways to try to detect this kind of use of AI. I don't think anybody would worry too much if anybody used an AI to give them feedback on the writing, but to have an AI generate the writing is more problematic, I think.

[00:24:04] Jesper Sørensen: Yeah, I would just say that I think it's definitely a problem in the context of giving exams and so on and so forth, as Christian was referring to as well. I think professors and then teachers are still, I think, struggling with the nature of the problem, which I think actually has less to do with the technology per se than with the equilibrium we reach with respect to what an exam serves to do. And I actually think it's gonna require faculty and instructors everywhere to think more deeply about what they're trying to accomplish and make those kinds of assessments more meaningful. Because I think a lot of students, they end up using these kinds of tools to answer questions because they are not actually interested in the introspection or the learning or the development. They know that would be something they would get out of it if they wrote the work themselves, but they think that the whole exercise is just pointless. But that's a flaw on our part, and that's what we have to address, right? So there are some fixes that are around. Having people take exams by hand and in person and so on and so forth. And I think that's also part of it. But at the end of the day, I also think we need to really think about what assessment is and what we're trying to accomplish with assessment. 

[00:25:14] Matt Abrahams: One of the things my co-teacher and I are thinking about doing is using the communication we have with AI as a way of reinforcing some of the communication skills we have. When you're typing in a prompt, you're writing a message. Now the audience happens to be an LLM instead of a person. But we can actually reinforce some of the ideas that we're trying to talk about when we actually have human to human communication. So actually using the way we interact with AI as another avenue to teach some of the skills is something we're toying with.

[00:25:41] Audience Member 2: Um, my name is Tana Tutu from Ethiopia. I'm in manufacturing, but by training I'm a psychologist, but I don't practice. But instead of saying I don't practice, I practice because I live with people. So I deal with people. So my question is regarding AI. I know it's going to take over some of the jobs and positions. And regarding having a chat with a chatbot, when you give it a prompt, you have to give it, you are a psychologist, a socialist like that. So for somebody who's lost their parents, can you just give them a prompt by, you are my mom, so you'll be speaking to me like this, speaking to me like that. So in a positive way, I see that in overcoming grief. That's one of the questions. I want you to give us a view. The other one is, in having a discussion with AI, like with the chatbot, how safe is our secrets with AI? You know, with humans, you're scared. Oh, I can trust that. And then there will be another version of it, which is gossip. So just give us few dimensions in that respect. Thank you. 

[00:26:53] Matt Abrahams: So I don't know how to answer either of those questions except to say that my sense is as somebody who is always very concerned about privacy, that I would be very concerned sharing very personal information with it. That said, I certainly know that we are far deficient in the number of therapists that we have in the world. And people have lots of serious mental illness and challenges, and there might be an opportunity for AI to help some people in some ways. So we have to think about what that means. I can tell you from my perspective, I think there's great opportunity to share information through LLMs and chatbots. So for example, we're in the process of creating a chatbot for the podcast where you can go and you can ask a question just like you did, and it will scour all of the wonderful guests that we have. And it will say that question is very similar to something Jesper said in this episode, you might wanna listen to it. So I see it as a mechanism to help people learn as well. But I think it's really early days. I don't know if others of you have opinions on this, but I don't know how to answer those questions except to say they're good questions and we should look at it. 

[00:28:02] Christian Wheeler: Yeah, I don't have a ton to add. I mean, there's research on, you know, there are a number of AI companions now that can take on various characteristics. The research shows that people get very emotionally attached to these AI companions. Whether that's a good thing or a bad thing, I don't know. I don't have research on that particular aspect, but for me personally, I will take a person over a screen any day. 

[00:28:25] Audience Member 3: Uh, my name is Leslie Meringue from Glytime Time Foods, Zimbabwe, and we run the Kelloggs of Africa. But now my question is, if we are competing neck to neck with that particular business in a particular region, and you compare yourself with that particular business, does it not come with legal connotations to it?

[00:28:43] Jesper Sørensen: To legal connotations? Is that what you said? Yes. Yes. I would not encourage the use of analogies like that in a marketing context. Um, and that's not really what we were focused on, right? So we were focused on how do you concisely and effectively communicate what your company is about to somebody else. Now you need to be careful. So for example, I was once teaching some of these ideas to executives and, and they were a group of Australian executives. And so I told 'em, I asked them about a company that's based in Silicon Valley called Rover, Rover.com. And Rover is the Uber of dog walking. It's a very Silicon Valley idea. And so I asked them what, like when you hear the phrase the Uber of dog walk, none of them were familiar with this company, what does that mean to you? And one of the first answers was, oh, that means that I can get a dog walker on demand, okay?

[00:29:36] Because when you think about an Uber, one of the characteristics of an Uber is you pull out your app and you say, I want a car right now. And it shows up. That's not at all what Rover does, right? The analogy is about it's gig working, right? So they have a bunch of people who have too much time on their hand and not enough money, and a bunch of people who have too much money and too many dogs, right? And they're, they're trying to get them aligned with each other. And that's also what Uber is like. But again, so the reason you need to be careful with analogies is there can be that kind of miss because people have their own mental models of what's going on. So when you compare yourself to another company you need to be careful about what it is your audience is actually hearing when you're making that comparison. 'Cause otherwise it can really lead to misunderstandings. 

[00:30:21] Matt Abrahams: Thank you for being part of our live audience. And with that I end, I'll ask you to thank our amazing guests and I appreciate the questions that you all ask. Thank you very much.

[00:30:32] Thank you for joining us for this special Think Fast Talk Smart podcast episode, recorded live as part of the biannual Stanford SEED Conference. To hear another live episode like this, please listen to episode 194. This episode was produced by Katherine Reed, Ryan Campos, and me, Matt Abrahams. Our music is from Floyd Wonder. With thanks to Podium Podcast Company. Please find us on YouTube and wherever you get your podcasts. Be sure to subscribe and rate us. Also follow us on LinkedIn and Instagram. And check out FasterSmarter.io for deep dive videos, English language learning content and our newsletter. Please consider our premium offering with extended Deep Thinks episodes AMAs, Ask Matt Anything, and much more at FasterSmarter.io/premium.