Welcome to, welcome to, we did end up on the double shot.  Welcome to the shows of tomorrow. My name is Jamie Higginbotham, um, we are trying a whole bunch of new things inside of our Eevee Mux today, so who knows how this is going to work, uh, how well this will actually look. So yay, look at this, I just want to point out, Ryan, there you go, he's this way, no he's this way, he's, I can't do it, ah! He's actually framed correctly and it is killing him. He's dead a little bit on the inside. Um, well, alright, let's get straight into it, there was a, I saw that India was, I think it's for the third time now, uh, sending, they're trying to send a payload to the moon, is that correct? Yes. Uh, let me call that back up, sorry I didn't have my note handy, I was so busy cropping shots that, uh, but they've only launched, they haven't actually tried to land anything and if I remember correctly, their previous shots for going to the moon were not successful. Like the rocket launches themselves were fine, but then like, actually, landy, landy, um, yeah, no work. This is the third attempt, they've attempted to land once before, this is their third, this is their third Chandrayaan mission, their third moon mission, they've tried to land once before, uh, didn't go too well, um, uh, trying again, they've got a, they've got an orbiter, uh, a lander and a rover on, a rover on the lander, um, so three different components of the mission and they're going to try and land, lander and then roll out a rover to rove. I just want to say didn't go too well, in aerospace, didn't go too well is, um, I feel like that's a very understated way of saying made an impact crater or, uh, hard landing. It wouldn't be litho breaking, it would be, uh, regolith breaking, regular break, lute regolitho, my, my, my breaking, wouldn't litho break, isn't litho earth? Yeah, but I feel like it's a, it's a, it's a planetary surface. So I feel like litho breaking still applies. All right. All right. Fair enough. So I guess if we wanted to pull like the Latin prefix for it, then I guess it should be like salina breaking or something like that. They also signed the Artemis, Artemis accords, uh, moderately recently. So, uh, Artemis is like getting bigger and batter and more awesome. Um, like just, that was just a random, random thought. That was India that just recently signed, right? Yeah. And they're also doing some space station stuff in, uh, 2024, I think soonish, some missions and the things. So collaborate, more collaboration between, um, the US and India. So around the room, uh, you know, landing something on another planet, well, I'm just going to say planetary body. And then I realized that Jared would get very angry for me calling the moon a planet. Um, but another, uh, what am I trying to say, slash your body? Um, what do we think the chances of, um, defining success in aerospace is hard, right? Because it's almost never 100%. But what do we think the chances of them at least meeting main objectives are around the room? We'll start with you, Jared. Okay. Jared is this way. Mine is this way. I got it. I got it. It's all just reversed for me. Well, Jamie, I just wanted to say first off, I don't think anybody's going to be mad about you throwing planetary science at the moon because it's called planetary science for a reason. Also, if you want to be like me and you want to make, uh, planetary science is really, really mad. Uh, you could call the earth and the moon a binary planet system because it's big enough that it just is. Uh, so, uh, what do I think this, the Chandra on three. I think it'll be, I'm going to throw 70% out there. I think the chances are definitely higher than Chandra on two. Uh, well, we'll have to see, we'll have to see if all of the data that they were able to get back, uh, years ago from that mission has been applied and understood and learned. And I feel like if anybody's going to be able to do it, um, this rose pretty good at that. Uh, they have a good track record on their missions after their first attempts, uh, simply because they're excellent at figuring things out. Uh, and I feel like that's one of ISRO strengths, which is that they don't necessarily get it right on the first mission, but they are really good at the analysis, the, the failure analysis and looking at everything after that and then figuring out how to apply that to their, their future and subsequent missions that come after that. So I'd say this is the 70%. I feel like there's a really good chance that they're actually going to get this when the land on the moon. So Darren Green says in the comments in the chat room, a hundred percent this time. That's a good, that's aggressive. Darren, a hundred percent. That's a lot, um, question though. So, you know, doing post failure analysis is one thing, but you don't know what you don't know, right? So like, let's just say they had a failure previously, but there were three things that would have failed after that failure. You don't know about those other things. And so who knows what else is, you know, the universe is a cold, hostile place, right? Like you hold it 70% with the idea that, like, you know, maybe there's more that could have failed. Yeah. And to ISRO, as far as I understand, success is simply landing on the moon. Anything after that is a bonus, uh, because that was what Chandra on two is about. Chandra on one was simply an orbiter, which was successful. Chandra on two was an orbiter and a lander combined together. Orbiter was successful still at the moon. Lander didn't work. This one is also the exact same thing. We have another orbiter and a lander involved. So, um, as far as I know, the payloads are relatively the same on the lander as well. There's like a very small rover, uh, from the United Arab Emirates and a few other instruments that ISRO has developed themselves. So, uh, yeah, I feel like the, the we landed is the real success and then anything beyond that, you know, that's kind of, that's kind of how it goes. So. Darren is backing up the comment, yet you have to be optimistic. And yes, landing is the objective. And Larry King, Larry King is also agreeing 100% the engineer in me, the engineer in me cannot give you 100%. I refuse to do it. I'll give you, I'll give you five nines. I'll give you five nines. I'm not giving you 100% of 95%. Oh God, Ryan, why do you hurt me? You purposely hurt me. Uh, all right, I'll give you 100% of five nines. How's that? Ryan, wait, wait, I think I can turn. I think I'll read this out. Ryan, what do you think the percentage is? Uh, I don't know. I don't, I don't want to speculate and then be wrong. And then people go back and say, you are wrong. But if I had to make it, but Jamie's forcing me to make a guess. So I'm going to guess 68% successful. And that is a percentage of another percentage. Jamie is forcing me. We're going to make sure it's to say Jamie is four. By the way, chat room, when we were on the single shot of Ryan and I was talking, could you hear the first part of my sentence or did that get cut off? Cause I'm not sure. So I don't know if they could either. Really? Mm hmm. Mm hmm. So you can only hear me when I'm on the screen. I think so. This is going to be an interesting show. Uh, cool. Thank you, Mac. All right. All right. Uh, understood. So, um, all right, we're going to make sure it's lost my train of thought. Welcome to technology. Um, doing technology, you live. Yeah.  Okay, uh, Jared, how about we hand it over to you? What, what, what inspired you in space this week? Uh, well, I don't know if I would call it inspiration, but it was definitely more of that sort of like reality check, uh, that ends up happening with space flight every once in a while, or should I say all the time? Um, which is that we're looking at doing Mars sample return as like the next big thing, right? Like that is the absolute, that is one of the holy grail missions for us to want to do. And that's going to be a very complicated beast. Like there is no way to get around the fact that that is going to be a incredibly difficult mission, um, for us to pull off. Uh, but one of the things, uh, wait, what's so hard about going to a foreign planet millions of miles away, landing, grabbing something, lifting back off and coming back to earth and then successfully deploying that on earth. Also, that is for the record. How the zombie apocalypse starts. Oh, okay. Uh, well, well, you know, Jamie, somebody's got to get it started after all. Uh, but the, the thing about, uh, Mars sample return with it is, is all of those elements, there's really a lot of elements, right? Like I pulled it up on my screen here for you to take a look at, which are all of the elements that we're thinking about. So one of those elements is already there, which is perseverance and perseverance does have a system that allows, will be called sample caching, but there's a lot of things that have to go into this as well. We have to develop a orbiter that can go to Mars. We have to. Jared, Jared, are you sharing your screen? Yeah, it should be. No. So no, it's not, no, welcome to the technology show. This one's going to be less about space than all about technology. Yeah. All right, cool. Well, let me, oh, it says that, uh, oh, okay. It says EVMUX doesn't support it on my operating system. Good stuff. On, are you on Mac? Yes. That's what it says. Are you on Safari? No. All right. No, good times. Thank you, EVMUX. Uh, if they ever, if they ever need real time feedback, they should watch our show. Um, but, um, you know, you're having to build a. Orbiter to get to Mars, you having to build a lander to land on Mars, you having to build a lander or a rocket that can fit on your lander as well. That's still potent enough to get your samples into orbit around Mars. You also have to have something to retrieve the samples, which right now, uh, the leading retriever, I guess, the leading dog, uh, for doing that is, uh, a, a upgraded version of ingenuity, the Mars helicopter, um, in addition to that, you got to have an ability, you got to have the ability with your orbiter to be able to burn back to the earth. And then you got to be able to make sure those samples get to earth. You also, I think a lot of people forget about this part, which is that you also need to make sure that you have a system in place that doesn't allow those samples to get contaminated at any point. Um, in our discord, which if you're not in it, you should definitely join it. Um, we had a pretty interesting discussion, uh, the other day about contamination and planetary protection and other stuff to the point that I think I now want to make a video for tomorrow about planetary protection. So everybody can learn, uh, that what they thought would work is actually wildly incorrect. Um, and there's a big problem though, which is that this is starting. First of all, it costs money. That's a problem, right? Um, secondly, usually the money that you want for your mission. Actually isn't the amount of money you need. Usually you need just a little bit more than that. Uh, for some missions, you end up needing a lot more. Like, I don't know, three or four times the amount that you originally thought you were going to need at the start. Uh, question. What was James Webb? What was James Webb? Was it three or four times? James Webb was originally supposed to be just about $500 million. So, and it only, it only went 20 times over budget. So it's fine. Um, so don't worry. Hey, you know what? James Webb, you know, Jelloscope started in the late eighties and by the time it was done and was ready to go at $10 billion, that I think that accounted for inflation very nicely, um, with that there. I'm sure all of the economics people watching the show would agree with me. Uh, 100% there. Um, but yeah, more sample return was supposed to be just a couple of billion dollars. This is a flagship mission, so it's going to be a couple of billion dollars right out of the gate, no matter what you think it should cost. It's a flagship mission. So it's going to be given a lot of budget priority. It's been going to be given a lot of money. The problem is that it's now starting to do something like what James Webb did, which is that those costs are starting to really spiral out of control. Uh, the estimated cost now, more sample return is somewhere in the upper portion of $5 billion, so getting closer to $6 billion. And there's some reports that are saying that if this continues, the overall mission cost could end up being about $10 billion, which there, the problem with that is not necessarily that the people working more sample return are like, Oh man, that's bad. The problem with that is that unlike Gelescope, uh, there's not as much support overall for more sample return. It's not like, uh, you know, Gelescope where the entire spaceflight and astronomy and cosmology community wanted that very, very badly. Uh, more sample return, I don't want to necessarily say it isn't popular, but it is definitely not universally across the board wanted by everybody. So that's a big problem when you start ballooning your budget and potentially eating into other missions, which is that you're not, if you don't really have a lot of support, especially universal support like J.Dubb did, uh, yeah, you're going to have a, actually a really big uphill battle. And if you don't have universal support in Congress here in the United States, which is where you get your funding from, whether you like it or not, um, as we always say, whether you like it or not here in the United States, politics is a critical portion of spaceflight. Um, yeah, and you have to appeal to both the Senate and the House of Representatives, and those are two entities that will bounce budgets back and forth between each other to compromise in your mission may end up getting, you know, it's budget set a certain way in that compromise, which may then end up either enabling your mission like Europa Clipper. Europa Clipper is one of the missions where it was saved in the budget, where the compromise ended up allowing Europa Clipper to actually occur, or your mission may end up like Europa Lander, which was going to be the one off Lander mission that we were going to do, which got destroyed and basically closed out in the budget because nobody could agree to compromise on it. So there it went. So, yeah, so more sample return right now is at a really critical point where it's either got to get itself together in terms of the budget, or, or it seems like it seems like the, uh, it seems like Congress here in the United States is going to smash it and, and, and, and any chance of more sample return happening, but unlike JDAP, the spaceflight community as a whole doesn't seem to be willing to step up to the plate and attempt to save it. It almost seems like everybody has said we're tired of mission budgets going out of control and that if you, if you go over and it cost you your mission, sorry, that's, uh, that's a tough lesson for you to learn, isn't it? So we're almost, I don't want to say the attitude is getting into if he dies, he dies, but it's, it's kind of reaching a point where, yeah, it's, I think people are, I think people within industry are finally getting to a point where they're beginning to understand that budget control is a pretty important thing. And I think that's an interesting thing too, which is that it seems like over the past couple of generations of PIs and, and head engineering divisions and other things like that, there really has been this sort of loss of the ability to control a budget of a mission as well. So I guess there's a lot of hard lessons. On the time scales in which we work on in aerospace. By the way, when Jared was live, we've been working on fixing these scenes behind the scenes. Did you guys hear me when Jared was full screen? Having said that, in the time scales in which aerospace works, it's like, yeah, okay, we're sick of going over budget. But we're already so far into these projects is are a bunch of these really big projects now going to inadvertently get canceled because we don't want to have them go over budget. And like, they, there wasn't enough time for them to realize that, Hey, we need to cut back, right? Because there's, there's a discrepancy between the speed in which society works and the speed in which aerospace works. You know, there are times where I mean, no, no, technically, how do I say this? Trying to figure out a really nice way of saying it, which is that at no point is your mission safe. Right? So there's, there's been a couple of missions recently that NASA did cancel, right out of it, or not right out of the gate, but basically like, well, you couldn't get your budget together. So you're done. One of my I can think of is gems, which is which stands for gravity and extreme magnetism small Explorer, which there's a mission called IXPE, an x-ray telescope that got launched two years ago that basically doing what gems was going to do. But gems was beginning to rapidly balloon and its budget, it was literally becoming four or five times what the budget originally was supposed to be. So that they said, Hey, guess what, you haven't even started building your spacecraft yet.  So you don't get to responsibly have a mission. And that's the point that Mars sample return is at right now. They're getting into the finalization of the, of the designs of the things that they want from our sample return, but they don't have any of the hardware yet. Hardware is really what separates it. Hardware is what makes or breaks it, I guess, is the way to say that in terms of budget. Usually when you built stuff, that makes a pretty good argument as to why you should continue to do that mission. That was one of the big arguments with J. Dub, which is back in 2011, when they were trying when when the really actual threat of cancellation of J. Dub was happening, most of the telescope had actually already been built by that point. We've already got the hardware. So if you're going to cancel this mission, why are you doing that? Because we already have this hardware ready to go. As Tarshish is pointing out in our chat room, Janice, this is a mission that was supposed to fly with Psyche. And because of Psyche's launch window, that didn't because it got changed, it couldn't couldn't do its mission anymore. So NASA just announced this week that they're going to be putting the two Janice spacecraft in the long term storage. That mission is up in the air now, because of that. Discover the deep space climate observatory. It had a very interesting sort of and it first end to its mission where it was going to be doing work towards climate change. And then a executive branch of the government got voted in that did not did not have a very positive idea as to the science behind climate change. So they basically stopped that mission and put the satellite in long term storage for that. So there's a lot of a lot of different reasons that your mission at any phase could actually be cut. And it's it's really important to make sure that you walk that tightrope as best you can. And it seems like with Mars sample return, they're not really doing that. They think that there's almost this idea that because it's Mars, it's invincible. And it's looking like that's not what's going to actually end up happening. Or is it that we're just going to send humans there to Mars, and then it doesn't matter, right? So like, what the time is to get a Mars return going like SpaceX will have humans on Mars. So this is where that really interesting planetary protection discussion that we had the other day in our discord comes from, which is that you cannot the whole point of doing Mars sample return is to get pristine samples back to the surface of the earth. There are multiple categories of planetary protection. Mars is in the highest tier of those categories. That means that this spacecraft that we send to Mars, especially the ones that we send to the surface of Mars, are some of the cleanest things on this planet. They are baked at high temperatures. Every part is disinfected multiple times throughout the process is not exposed to air. That is anything less than a class 10,000 clean room, which means that for every cubic meter, there are less than 10,000 particles in it. So everybody as everybody has been doing for almost the past decade in spaceflight saying, what about SpaceX? No, it's not going to it's not going to help the SpaceX system with Starship. That's not good for getting pristine samples because I don't know if people are aware of this with Starship is built mostly outside outside. Wait, what? Not the cleanest air. Can you imagine that? Like this? Does anyone hang on? Does anyone know where we can get like a live feed of them building Starship outside? Is that a thing that they can? I don't know. I don't feel like that's a I don't know. Ryan who's just glancing. You can't see him because he's not on screen. He's just glancing side to side. Then I don't know man. I mean, if only there was somebody who has had like a feed that I could see everything like vents and bolts being turned and people dropping hammers. And then we could have articles about it. But yeah, the Starship being built outside. Guess what? Yeah. Yeah, that's that's you are you are that is an unbelievable amount of contamination. And that would be one spacecraft doing that. And essentially, sending people to Mars will also contempt will also be direct contamination of Mars. You just cannot make the interior of a human spacecraft clean. It's it's near impossible. I would just say it's outright impossible to do that. This the instant you open an airlock that people have been inside of on the surface of Mars, that's it. The planet at that point is contaminated. Any any samples that you would get would be considered. It would be very difficult for us to look at that those samples. And if we found back to some sort of life or bacteria, something whatever you want to call it, we'd be very, very difficult to look at that and say, Well, we can't rule out this having not been brought from Earth, because we have people from Earth on Earth. And we know that the stuff on their suits the stuff on them, it's gotten all over the interior of their spacecraft all over the interior of their airlock. Therefore, they are likely contaminated the planet. So no, no, we cannot have people go and grab those samples and do that. We need pristine samples. It was even someone even brought up the idea of perseverance is current samples. So perseverance, the rover has a sample caching system.   The problem is that you then contaminate the outside of your sample tubes there and you risk in the process of bringing the samples back into the laboratory, you you escalate the risk so much that it ends up becoming just as bad as like if I were to go out and breathe on a rock and then bring it back in. It's it's one of those things where you need it. The cleanliness is the critical key to making sure that the samples are right and correct and have what we need. And any anything that can disrupt the process that cleanliness at any level that will ruin it. I know you've okay, I hear your point. And I knew we've driven this point home. But like, arguably, you don't need infinite like there's going look humans are going to Mars. Yes, we're going to contaminate Mars. Like that's why we have to do more sample return as fast as we can. The problem is, no, no, no, what you need is what you're saying is you need a pristine sample of Mars. That doesn't mean it needs to come home. It just needs means you need a pristine sample of Mars, correct? Before humans get there. Right? So there's there's a world in which we get the sample and just leave it on Mars, then humans go and pick it up. Yes, but like I said, the problem is that once humans are in the equation, once you put people in the equation, that the moment the sample comes to hang on the moment the sample comes to Earth, humans are in the equation. But no, here's the thing. We can isolate it from the humans on Mars. It becomes very difficult in order to know you're missing my point. Before we send humans to Mars before a before Starship ever goes, no human has ever stepped foot on Mars. We can send a spacecraft to Mars, grab a sample and not return it and encapsulate it so that it is so it's protected, right? And then a human goes and picks that up and does what they need to do with it and same protections just on Mars. Because if you're saying if you're saying the moment a human touches it and it's contaminated, well, that applies here on Earth to write the moment it hits our atmosphere, it's contaminated. So arguably, it would be a better mission, would it not to leave it on Mars and limit the contamination of whatever spores could hit it on the way back, whatever is hitting it in the atmosphere, whatever is happening to it here on Earth, don't even go through all that. Alls we have to do is make sure that when we approach it on Mars, whatever this container, this capsule is, we don't contaminate just that part of it. So the big, the big problem with just examining it on Mars is that you have to move your laboratory to Mars, which let's do that. That's an awesome thing to do. But also, damn, that's expensive to do something like that. So look, man, we're already sending humans to Mars, right? Why don't we bring it back to Earth as well? Why don't we do both? Because getting it back to Earth is substantially harder, right? That's so who cares? I mean, yeah, when given the option between A and B, let's choose a work when choosing given the option between A or B choose A and B, I don't disagree using my own using my own logic against me. But yeah, all right, fine. Yeah, I do want to say that I couldn't see it. And I couldn't see who it was in the chat room, but somebody in the chat room said that that because robots are an extension of humanity, that we've already contaminated Mars. Well, the thing is, we have protocols, we have unbelievable protocols in place that are designed to handle things like that, right? So these things, all of our spacecraft that go to Mars, including ones that don't land on Mars are built in class 10,000 clean rooms, they're baked at hundreds of degrees Celsius for hours at a time. They are wiped down multiple times with disinfectants during the assembly process. Also, the transit time to Mars helps out a little bit is not the end all be all, which is something we also discussed in our discord chat the other day. But we have everything as clean as it can be. As it can be. You have you see, you had to add a qualifier because you're also an engineer and you're not going to give me a hundred percent. Are you? Thank you for great timing. So so it's not going to be a hundred percent something probably made it through. Yeah, and I know in Josh is saying it doesn't matter how much you clean or how much you clean your robotics, we're going to litter and yeah, so it's contaminated. So here's the thing. You we can make robots a lot cleaner than humans.  I'm sorry. I'm sorry, Jamie. That's the way it is. But you're arguing against yourself. You're saying it has to be the pristine thing before humans arrive. And I think the argument is, but but humans have already arrived. The robots have been there. We have brought humanity with us. The human physically the humans, us in person. But we can still. All right, we're going in circles. We're going to be clean. And just trust me, you ain't convinced me on this one today. I'm not saying that humans aren't dirty. I'm not saying humans aren't dirty. I'm just saying that maybe that plan is not the best utilization of resources with the understanding that humanity is going to Mars. That's my point. That's all. That's it. I don't agree with that. So what do you guys think added into the comments below like you guys are adding into the chat. I'm pointing as to chat rooms as if you can see where our chat room is. But like, yeah. All right, Ryan, you've been eerily quiet. Oh, and I do have the shot of star. I brought up the shot of starship being built out in Starbase. If we wanted to like, it's not a clean room environment, right? It's, it's pretty messy. Yeah, that would that would pretty much ruin just about any chance at any clean sample from Mars. Not a clean room. Not asking how many zeros are we talking about in terms of cleanliness infinite? That's how many we are. So you're welcome. Cool. Ryan, why got you? How's that for a awkward horrible transition? What got you excited about space flight this week? A few things. First of all, Bennett Elder said a while ago in the in the chat room. Evie Muck said it was eight seconds ago, but I don't think it was eight seconds ago. I'm asking, psyche's not on the chopping block, is it? No, it's in a key at the Cape. I've I've a picture on my screen. Dutter of a man pointing to psyche, proving that it is indeed there. It exists. It is going to be launching. I don't know if that's gonna there we go. So there you go. It is indeed there. Someone is pointing to it. There you go. It's just like random dude pointing like point. Yeah. So there you go.  It was a software bug. And so there you go. Let's move on. Okay, SpaceX, they do cool things, don't they? Okay, so first of all, six dash five. Let's look at this, because they like to reuse their rockets, which makes them cheap. So by reusing their rockets, many, many times brings the cost down. And for the first and the second time, in the space of seven days, they've launched and it landed a booster 16th time each for those boosters. This was the first one starting at six dash five. And this clip is longer than I thought it was going to be. So I'm just going to stall for time a little bit. There we go, landing legs out and Bosch on the drone ship. There you go. That was the worm booster, the one that carried Bob and Doug to the International Space Station and has done 15 other missions now alongside that one. And then starting five 15 later in the week just last night, did the exact same thing again, became the second booster to do to perform 16 flights flawlessly sending the second stage on its way coming back to the drone ship landing doing something that just a decade ago, people would have been laughing at what they were laughing at. And yet we're now 16 flights into this booster, these boosters lives with just one period of refurbishment, which is kind of crazy to think about if you know, you think back to shuttle after every single flight, they those things were meticulously gone through and refurbished. And now they've done a 16th flight after one period of refurbishment on the booster. So there you go. We use ability works and yeah, make space cheaper. I don't know where Jamie's gone, but Nigel says that if the engines being reused to the same extent, we don't really because they don't they don't keep a track of them. And we can't really see the Merlin's apart from when they're in flight. And it's essentially impossible to keep track of the engines. It is known that they have done engine swaps previously on boosters, but we don't know which when and what. So there. Ah, Bennett worm boosters the No, right. So when we do SpaceX stories, I turn off my camera and microphone. You don't I can't talk SpaceX. Oh, yeah, I forgot about that. The entire internet noticed I randomly like you're like, I like blah, blah, blah SpaceX. And you just see me go, why am I gone? Where could she have gone? Why? I wonder why I left. I don't understand. Yeah. Yeah, I can't imagine why anyone any of us would disappear at specific reasons and specific points for specific times. But then so and then I'm trying to get back into the show. And so I'm drinking this. All right, fun fact. Toys have nothing to do with space. I'm drinking my cold brew to try to keep myself awake, right? Because after the show, we're going to back up a little bit here. So I moved the shows to Sunday. So first off, thank you, Dada, Jared, Ryan, all of you for being flexible and being like, Yep, I can move the show to Sunday. Dada and Jared, blah, blah. But Ryan, I don't know what time it is there. But like, we keep messing with your schedule. I appreciate your willingness to allow us to mess with your schedule. I go. Yeah. It's seven. Exactly. Okay, that's much better. That's a much better time than before. Yeah. Yeah.  He's pissed I cropped his frame, but it's been bothering me for like a year. So I just knocked into it. So thank you, everyone. And then thank you viewers for letting me move the show. Everyone's saying this better now. The the reason I moved the show is because at Company X, it was it's insanely difficult now for me to work on Monday or Friday evenings. Whereas before, like Friday evenings was one of my easier days to work. My everything at Company X shifted for me. And now Fridays are very, very bad. So we move the show to Sunday basically to help me. So thank you. So then today's the first Sunday show. And it turns out my whole team is in town. They are currently working without me so I can do this show. I should technically be at work right now helping them out. And I was like, I can't, I cannot cancel on the first time I moved the show. I just can't do it. So I owe my I owe my team dinner, drinks and dinner.   But yeah, yep. It's just really hard at Company X to carve out the time even on weekends. It's just really hard. Oh, so point is, that's why I have the cold brew to keep me awake. I should cover the logo. I have an unnamed company's cold brew to keep me awake. I was gonna say I've got an unnamed company's green drink green drink in order to try to wake me up. So so anyhow, I think unless anyone else has any more stories, I think a lot of my focus on this particular show was like, you know, we're losing the studio at the end of the year. So I'm trying to find an online system that allows us to do this from anywhere, right? Like, why do I have to have a studio other than I just Zach, you're not wrong. You're not wrong. They so one of two things either they I got them a Bluetooth speaker. So in the IDF, they're either listening to music right now in the Bluetooth speaker, which I think is like an 80% chance that they're listening to music. But there's a 20% chance that they're listening to me right now. And I don't have my phone nearby. And I'm just waiting for them to ping me and make fun of me. Anyhow, um, yeah, so on this particular show is a lot of work behind the scenes to make Evie mux kind of do what we want, so that we can get out of the studio like little subtle detail changes to the interface that we can like make the shows look nicer. I'm trying to get the intro sequence so that like it's easier to get into the show, things like that. And like, we're still struggling. I'll be blunt, we're still struggling. Edie mux is not the same as having a full control room with $100,000 worth of gear producing a show, right? Like, that's like real time changes. You can do anything you want. It's a little bit easier. But I think I do think we'll get there with this particular one. So I know it's a struggle in figuring out audio and like all the other fun jazz and like pissing off Ryan because I'm making him frame up nicely. Just he just stares blankly at the camera. He's shooting lasers at me right now through the camera lens. They're missing me, but he's shooting them at me. All right. I do think that's our show this week. I have no idea what we're going to talk about in post show. Does anyone have the members only streamed? Does anyone have any ideas what we want to chat about? I was gonna say man, it's got a good man. He's got a good one to start out right there, which is that start your extreme to new worlds doing really nice so far off. Alright, so we're going to talk about strange new worlds. By the way, in order to be in order to be able to watch the member stream, you do need to be a member of tomorrow and there may be many different memberships levels in which you can do that and duttle throw those up on the screen so you can take a peek what those different are and then you also get your name in the show. There we go. Hi, Jamie. Hey, Jamie. Hi. There's no audio for you there because Evie Mux is amazing. Well, so did we miss it in the we had a moment of silence for our members. Yeah. So when the when the pictures when the when the fancy pictures went up, we could we could hear you. They couldn't hear you and you couldn't hear us. Yeah, that's an interesting one. I see. Okay. Changed visibility which makes them not audible as well. Yeah, I was hoping that changing. Okay, you know, we'll talk about this in the member show. All the people who are up on the screen are members and they're awesome and thank you and we will get this work. I will we will get this working. I swear to you, we will get this working. We are close. We're hacking away at it. We're getting close. Also, I think the fact that we keep failing at the exact same thing over and over and over again is kind of funny. It was like, it was like, oh, that sucks at first and it was like, it happened again. It was like, oh, that's kind of sad. You shouldn't have let it happen again. And now at this point, it's almost like a comedy sketch. I'm like, I feel like when you go to the when we go to the slates, this is going to fail. So we learned that layer visibility impacts audio.  We'll talk about this in the member stream. Thank you everyone so much for watching. Members will see you in a couple minutes. Watch the YouTube for that.


We are ever grateful that you are able to join us to celebrate our 2021 Distinguished Alumni. I'm Brenna Keelan Kelly, a senior from West Falls, New York, majoring in material science and engineering in the Honors College. Not only am I a Boilermaker, but I am a community builder. I serve as president of the Purdue University Material Advantage, providing student membership into preeminent material science professional organizations, such as AIST, ASM International, TMS, ACERS, allowing for student network opportunities with other materials professionals. I'm also a materials engineering ambassador, helping the college's recruitment and retention activities by sharing the student experience. Outside of Purdue, I am a musician in the St. Thomas Aquinas Music Ministry, playing the fiddle during masses and other performances. Building community adds rhythm and rhyme to my life as a student and a future engineer. It is my honor to introduce the 2021 Distinguished Engineering Alumni Award recipient from the School of Materials Engineering, Stephen E. Ferdon. He has taken Cummins Fuel Systems from a startup in Columbus, Indiana to a worldwide operation. As global director of engineering technology, he leads 100 engineers and technicians at centers in the US, Mexico, China, India, and Sweden, collaborating on fuel technology engineering and bringing in $1 billion in revenue. In his persistent pursuit of the next giant leap, Ferdon's innovated green technologies in fuel system supply chain and quality, demonstrating environmentally sustainable manufacturing. He holds three patents with three pending. Due to COVID-19, operations in Wuhan were rerouted and Chinese team members transitioned to work from home. By adapting the work environment, Ferdon preserved 500 jobs and livelihoods, lessening the loss to CFS. Closer to home, he volunteered as disaster response coordinator for United Methodist Committee on Relief, organizing volunteers to design, test, and build ventilators and respirators for the Columbus, Indiana Hospital. Ferdon is a charter member of the Purdue Center for Surface Engineering and Enhancement, serving consortium members' needs and educating the future leaders of the industry. For his commitment to environmentally responsible engineering through pioneering innovations in fuel system supply chain that push for the highest purity standards in the global market and demonstrating technical leadership in pursuing material selection and process design for sustainable global manufacturing, the College of Engineering is proud to present the Distinguished Engineering Alumnus Award to Stephen E. Ferdon. To learn more about how Purdue influenced Mr. Ferdon, please click on his video link below. Boiler up and hail Purdue.


So what do you do when a new client pays you money? Well, I'm going to show you the exact onboarding sequence that we use at our drop servicing agency growth response for all new clients that come into our agency. Hey, what's going on? It's Sean Anthony.  I post videos just like this every Tuesday and every Thursday. So in this video, I'm going to be going over step by step, our exact onboarding sequence for new clients in our agency growth response. We do done for you, LinkedIn services for B2B companies with high ticket solutions, mainly in the technology space. So I'm going to show you exactly how our onboarding sequence works and what happens once a client hands over money and wants us to start delivering services for them. OK, so I'm going to keep this real simple for you guys. I have it all drafted out of my computer. I'm going to show you all the pages and all the sequences that we use. So let's just jump right into it right now. Alrighty, so on my screen here, I have the exact step by step process that we use when we're onboarding a new client. So I'm going to walk through each of these steps and then show you examples from our own agency on what that looks like. OK, so step number one is the client pays for our service. They usually sign an agreement and they pay for our LinkedIn services or our cold email services, right? So that's step number one, right? Once they pay for our service, they automatically get sent to a they get sent an automated email like an onboarding email once they complete their payment. And in that email is a link for them to fill out an onboarding questionnaire form. Now, this questionnaire form gathers all the information that we need to deliver the service successfully for them, right?  What is your actual service and how does it help to solve the problems of your market? Right? What is your account access, right? For LinkedIn, right? So everything that we need to be successful and to create strong messaging campaigns, we gather that in the questionnaire form. OK, so I have a team. I have an in-house team now of like contractors that actually do like the copywriting and messaging and run the service. But we also like if you are using a white label provider and you're running a drop servicing agency, you can also go to the freelancer or the white label provider and ask them what you need from the client to be successful, right? So they might tell you, oh, we need their their Facebook ads account access or we need these types of images, right, from the client. So what you're going to need from the client is going to depend on what your service is and you're only going to know that whether you're a service provider yourself or if you're leveraging like a different fulfillment provider, you need to figure out what that is for your business. But you're going to gather that in the questionnaire form, the onboarding questionnaire. OK, now once once someone fills out this questionnaire, the client fills it out, it gets automatically sent to my team. That's what this T stands for. OK, the client also gets sent to my calendar link to schedule a kickoff call. And on that kickoff call, this is like the only part we try to automate as much of this as possible. The kickoff call is usually me or someone on my team is on this kickoff call, right? And this kickoff call helps to set expectations of the client and also get everything approved from what my team did in terms of the messaging and in terms of like creating the campaign. My team creates that and on the kickoff call for the client approves that. OK, so once the client approves that, then we turn the campaign live, right? So it's a very simple onboarding process and we try to automate as much of it as possible with a tool called Zapier. If you have never heard of it, Zapier just helps multiple different apps talk to each other, right? So we have like active campaign, we have Slack, we use Stripe. Zapier connects all those apps like together so that when one thing happens on one platform, it sends it to the other platform and so on and so forth. So on and so forth. OK, so once the client pays, they get sent to the questionnaire form. That this is what this looks like. I just made a copy of our example onboarding questionnaire and I'm just going to show you some of the things that we ask on it, right? So things like the person's name, their company and website, their email. Who's your ideal customer? What industries are you targeting? What are their job titles?  What are the pain points people are facing in their business or their personal lives that motivate them to buy your product or service?  I'm not going to read through each of these, but we ask all the questions that we need to be successful in creating them a campaign, right? So at the end here, we also ask them to they need to make sure they upgrade the sales navigator and they need to agree to letting us run the LinkedIn campaign through their profiles, right? Again, this is going to be all different depending on what your actual services. So you either need to come up with these questions yourself based on what you need if you're delivering the service yourself, or if you're a drop servicing agency, you're going to ask your white label provider or your freelancer or whoever it is that's doing the service. Hey, what do I need to be successful with the service for my client? OK, and they're going to tell you what they need. All right. So that's the questionnaire. Once they get, let me cross this off here. Once the client fills us out, right, it gets sent to my team. So I have a Slack channel here and we have different channels for different things you can see like prospecting positive replies, negative replies, different channels, LinkedIn, cold email, so on and so forth. But we have one here for client onboarding, right? So whenever someone fills out in a questionnaire, a client fills out a questionnaire, it gets automatically sent to here. And I'm not going to go into it because it has the actual client information in here, but the actual questions or the answers from these questions are going to be sent in a PDF form to this channel here. OK, once my team receives that, they then send it off to like there's there's a project manager in here that helps me out. They send it out to our copywriter.  OK, so what does the client see? Well, let me cross this off. You just saw the team part, right? The client sees my calendar to schedule a kickoff call. So this is Calendly.com. It's just a simple it's a simple calendar app that connects to your calendar, right, and it allows them to schedule time. So all the client does is they'll click on a date, they'll schedule a time here, right? And on this call, they click Confirm, they put their name, email, company. And on this call, we show them the actual messaging that we created for them, that my team created for them for their LinkedIn campaign. OK, so what do we do here? We the client paid and they signed an agreement. They automatically got sent to the questionnaire form, right? That's this here. The client fills out the questionnaire form that gets sent to my team and they create the messaging, they create the campaign for the client. The client then jumps on a kickoff call with me or someone on my team and they approve the messaging that was created from my team, right? And once they approve that, the client approves that we turn their campaign live. So all we're doing is we're we're connecting with people on their behalf. We're starting conversations on their behalf on LinkedIn and we're generating them leads and appointments and ultimately new clients for their business using LinkedIn and cold email. OK, this is how our new client onboarding process works. It's very simple. A lot of people just like to over complicated. They like to make all these different steps. But all we really need, all we're trying to do is really set the expectation with the client of how this whole process is going to work and also establish a good relationship with them and get everything that we need in order to be successful in delivering the service for the client. Right. And that's what this does here. They sign, they pay, they fill out a questionnaire, get sent to my team so we can work on the campaign and then we have a kickoff call to turn the campaign live. Right. So guys, this is a question that came up many different times in the past couple of weeks. How do you onboard clients? Like how do you actually what happens once a client pays? How do you fulfill the service? Well, this is how we do it, right? You're either going to have a team that does this for you or you're going to have a white label provider where you're going to have to send them the questionnaire or the information that they need to actually deliver the service. Okay. So that's it for this video. That's our new client onboarding process for our agency growth response. I just showed you each step in the process. It doesn't need to be more complex than that. The main thing is that you set expectations with the client and you make sure you get everything you need to deliver them an amazing result. Okay. So let me know if you guys like this video. Let me know if you have any questions below, comment with any questions that you have. Make sure you like this video. And yeah, I'll see you in the next one.


This is by Sheena. She says you had highlighted the importance of thinking out of box. What kind of research should be done for making out of box ideas successful in a case where there are no previous presidents? Well, thinking out of the box is what? Thinking innovatively. One must think deep, one must think hard. You will get newer ideas. That's why I gave you the example of Shri Parasaran, 50 different constitutions. Once he completes it, no, he leaves it. He takes the next one, looks at the article. Every time you look at the article, article 19, let me give you an illustration. Article 19, sorry, Article 14 is discrimination. If you look at the judgments, Article 14 merely says that one person will not be discriminated against the other person or the state will not discriminate between two persons who are equally stationary. Supreme Court dilated on that. If you remember, it said arbitrariness is a part of Article 14. Unreasonableness is a part of Article 14. This is again thinking out of the box. Why? This was done to ensure that sucker is given to a litigant. Many a times the judges also think out of box. After all, if you look at the judgments, there are innovations. There are leapfrogging of the thinking process, which is evident when a brilliant judge is there as against a state judge. So this is what you must do. This thinking out of box is something which you will have to adopt and evolve. It is only by practice that you will start imbuing that process or that character. I am sure if one thinks deeply, one would be able to think out of the box. After all, when clients come, they will have different things. They'll have different problems. Now, when you want to reach Delhi, you can reach Delhi through Nagpur. You can reach Delhi through Bombay. You can reach Delhi through Calcutta. If you think that there are certain hurdles by going straight to Delhi, you can go via Calcutta. Thinking out of box is that trying to be more innovative. After all, innovation is a part of every lawyer's life. When you have a formidable opponent against you, you always think and think as to how to beat him out. After all, I've always said this also, it's like a chess game. When you have litigation, it's like a chess game. How do you play chess? You always think and you think at least five or six moves ahead. How do you do that? Again, thinking out of box is needed. These are things in which you, once you evolve, adopt this methodology. You become a past master in it.


Hi, this is your host and welcome to here for let's talk. And today we have with us Prashanth Chansekar, CEO of Stack Overflow. Prashanth is great to have your show. Thank you, Slapnel. Wonderful to be here. Yes, I'm looking forward to this discussion. Of course, primarily we are going to talk about overflow AI. But since you are here, and if you look at Stack Overflow, first of all, you folks predate a lot of these modern technologies that we talk about all the cool boys, you know, Kubernetes, cloud natives, everything else. And also, if you look at the whole developer movement, you folks played a very big role there as well to kind of build a community there. We started talking about a lot of culture movement we talked about. DevOps movement, DevSecOps, and SRS platform engineering. But now we, I mean, I record a lot of shows and we are talking about bringing that developer experience back again. So what I want to hear from you is how have you seen the whole evolution of this developer journey from the day when Stack Overflow was created and when we are today? Great question. We've obviously got a tremendous amount of historical knowledge and data on a platform for about 15 years of operating since we were founded in 2008. So we've seen a lot of evolution in software programming when we think about concepts like abstraction where it's gone easier and easier to write code over time. And I look back to the time when I was writing code where, you know, we were like most people that pre Stack Overflow, you know, we didn't really have a lot of resources to leverage other than, you know, really figuring it out on your own or, you know, working with other people in person to do it. But over time, and Stack Overflow has been part of this journey where we've actually accelerated in many ways and enabled people to build more and more elegant software, you know, really sort of improving on the prior versions of certain capabilities that have been invented. And it's been fascinating to see that notion of getting it sort of making it easier and easier to grow, so to sort of build software. And along with that, what has happened is that the number of software developers have actually increased fairly dramatically. So it's that's what we've really sort of observed. Because as it's gotten easier, more people have actually gotten into the field of writing code, which makes a lot of sense because as it's gotten easier, more companies want to leverage technology to be more, to be closer to their customers to deliver great experiences from a digital standpoint. And now we're entering this, this new phase around the AI era, which is also going to be a tremendous platform shift, which is going to affect all things in software development, because again, companies are going to leverage this sort of compounding effect of collecting data, leveraging the fact that, you know, they've now got access to very, very sort of affordable compute storage and networking through cloud computing. They've got transformer technology. Now that is, you know, obviously with neural networks have been around for a long time, but all this is compounded to a place where now all companies can leverage all these pieces and these building blocks to make really, really powerful, intuitive customer experiences happen. And then of course, don't forget the startup ecosystem, you know, of course, in India and the rest of the world, this is an absolute explosion of startups building great things in this new and enabled by this new space. And so it's really, really exciting time. And one of the last point I mentioned Swapnil is that, you know, we believe the number of developers are just going to go up very, very meaningfully. We're probably talking about a multi, you know, three to five times type of, you know, number because so many more people are going to feel comfortable writing code going into this next phase. This is kind of a loaded question, but a lot of folks say that he's going to take away jobs. I don't believe so invention of build did not take away jobs actually led to the creation of company like Tesla and drivers and a lot of things. So generally AI is also going to create more job than take away. But but how do you see the emergence of Genetic AI because you folks have been leveraging AI for a long time. But Genetic AI, sometimes a lot of technology, they come like a blip and FT is a good example, but then there are a lot of technologies like Kubernetes or Linux kernel, which is actually concrete. How do you see it because you have to, of course, embrace latest technologies. But in reality, how do you see Genetic AI? We believe Genetic AI is a tremendous platform shift that's going to define this next era of computing. So I think we are we don't believe it's it's a fad and we don't believe it's, you know, sort of a blip on the radar. It is going to be transformative in many, many ways. Now, that doesn't mean that there isn't a lot of hype associated with this. That's just the world we live in with, you know, information flowing very freely. But it is transformative. There is something, as we like to say, there's a there there in the context of the technology. And so the way we have thought about it, Swapnil, is that Genetic AI specifically has some tremendous benefits.  And many other elements that make it really, really powerful to leverage very, very large, you know, data sets in a way that can be really sort of insightful and really provide produce new insights and new capabilities for companies and developers to use. And of course, generate code and all these other use cases that we've seen. At the same time, we believe that it has a set of deficiencies, which we believe we should be filling with community. So, so community brings things like, you know, creation of new knowledge, it creates talks about things like, you know, how do we connect the dots between various things and come up with with conclusions and make decisions of things. So the intersection between Genetic AI and community is really where Stack-O-Flow plays. And why is that? It goes down to, you know, every year we we conduct a developer survey, and this year 90,000 people from our community responded. And they said that 70% of them were interested in using AI tools or were already using AI tools. And, but only 40% of them trusted these AI tools, because they're very much sort of black boxes. They have no idea, you know, the amount of risk and let's say the code being generated or information being provided. Is it hallucinating? Is it not? Is it right? Is it wrong? There's a lot of that, you know, in the responses. And it makes sense, because, you know, we as technologists and developers are on the hook to build production level applications, things that are, you know, are very, very mission critical for companies. And so you want to feel confident that what you're actually putting into your code is actually going to be what is going to work. Number one, and number two, you can always reference back and be able to figure out if something does go wrong. How do you sort of really sort of debug it and also engage with your colleagues to that do that successfully. So, so this intersection of community and AI with Stack-O-Flow in the middle is really rooted around building highly trusted solutions as part of that, but has attribution and citations. It is highly accurate and high quality. It has a great feedback mechanism, just like we've been doing on Stack-O-Flow for 15 years. It has personalization and ultimately has recognition, recognition for the contributions of people putting content, creating new content, you know, innovating new languages. And all that existing on Stack-O-Flow is the foundation of how we've built what we built with O-Flow AI. So O-Flow AI is this, you know, we have announced five different capabilities under O-Flow AI, all with these principles that I just described to you. And I'm happy to talk about exactly the five different announcements around O-Flow AI, but specifically that's how we have built this with this intersection of community and AI with humans in the loop, as we like to say, to provide that reinforcement learning and feedback and attribution along the way. Yeah, I would love to talk about O-Flow AI and how it will be used. But before we go, one more question about the whole developer news articles we keep reading about, hey, is Genetic AI going to augment or is it going to replace the jobs? There's always a fear and something new comes.  How do you see that is Genetic going to take away a lot of developers' job or is it actually going to empower just like Photoshop? It gives us, actually, it enables more people to be photographers now because they can easily do those things that you could not do earlier. I think that it is absolutely going to, especially in software development. I can speak to what I'm close to. We believe it's going to increase the number of software developer jobs dramatically, right? And this is because it's going to make it more accessible, more inclusive, more open to people with various skill levels to be able to just get on the journey of being a software developer because the bar is going to be a lot lower. But at the same time, it's lower and also higher in that everybody's going to be able to do, you know, a minimum amount of coding in a way that's quite powerful as a result of some of these tools. So it's actually quite a very interesting time to be in in technology. And overall, you know, we believe that same, that virtual cycle I mentioned earlier because more people get in. What they're actually doing in coding could be different, by the way, Swapna, it may not be what we were all doing, let's say five, six years ago, because with the rise of prompt engineering, which is also an area we've now created on Stackflow flow called the Genai Stack Exchange, and the national language processing collective or sub community where people can have discussions and learn about the subjects. So with prompt engineering, the types of things that people will do will be different over time as they sort of really leverage to harness the power of these LLMs to produce tremendous outcomes. And then companies using this, the startups using this will create this kind of virtual cycle where companies will be able to unlock a lot of value as they build great high value experiences for their customers. And so we are very bullish on what this means for job growth for in specifically in technology. You know, as it relates to other industries, I think it's, you know, your point in that people will have to adapt to leveraging these tools. I think people who don't use these tools will probably get left behind. And those when you think about job loss, I think it's basically people who are reticent to leveraging these tools to be more effective and productive. And people who do use these tools will be orders of magnitude, you know, more effective in their organizations. So I think it's like anything in technology, I think you have to adapt and leverage these tools for your benefit to go faster and do more with what you have. So I think it's going to generate a tremendous productivity boom for people. When I was listening to you, it just reminded me the whole, you know, old times of, you know, digital transformation journey or cloud native adoption journey where a lot of companies who were not, you know, and suddenly they're especially during COVID times, only they almost ran out of, you know, business because they did not have any digital online presence. So I think soon we'll start talking about, hey, you should be on the gen AI transformation journey, you should have those strategies in place. I would love to, as I said, overflow AI. But when we talk about these teams, you know, or as you said, organizations, they should or not necessarily should, but organizations, you know, they do want to embrace a lot of these technologies. What kind of challenges you see are there, which kind of becomes kind of hurdle in the adoption of these generative AI technologies among developers. We've got a Swapno, not only the two parts of our company, it's important to explain this because we, you know, we have the context in that we have a public platform that everybody knows about, which is, you know, tens of millions of developers come to that. And we've got 58 million questions and answers on the public platforms, a lot of like the historical context there over the past 15 years. And then we also have a very large software as a service product that's called stack overflow for teams. And that's leveraged by 15,000 organizations to effectively share knowledge and collaborate with our platform internally within organizations. So effectively it's a private stack overflow for companies to use. And with these both these vantage points what we have discovered through our research and our work as we launched overflow AI, is that especially in companies, there is absolutely an interest to leverage generative tools like that 70% statistic I mentioned as part of our survey very consistent. But there is a lot of reticence to fully trusting, you know, what's coming out of these tools and can they actually run mission critical critical applications is so those are so trust is a broad theme. And then you look underneath that, there is this notion of privacy, security of your data. There is this, you know, real explosion of the amount of code that's going to be generated using code gen tools, without really any control to be able to figure out how do you debug this when you need to are you going to get pulled into a room and something breaks in production. And where's all the context that's missing, you know, which is why what we've discovered that the need for something like stack overflow for teams as the knowledge base for all things technology information is so high. And we've seen a tremendous interest since we announced and we've been working on that overflow AI and even a few weeks before that as we were working with customers to preview some of this. People are super excited that they now can leverage a capability that is the source of truth within the organizations that they can leverage that data and leverage our AI capabilities are generally capabilities on top of that trusted data, which which really gives them a lot of comfort as they leverage these leverage and harness these tools. So generally speaking, privacy, security, trust and attribution, and really feeling that they can have control over the explosion of amount of code that's going to get created here with high context knowledge base. And since you're talking about teams, I also want to quickly talk about how, how does it integrate with teams with the organization because we talk about a lot of things go wrong. We talk about things like chaos engineering where they big break things on purpose, they collect a lot of data, we talk about the whole observatory where they do see what's going on wrong in the company. But when they do that, they also look at answers what went wrong, how to fix it. So how does stack overflow teams, does it still remains like, okay, it's private, but does it somehow integrate with their internal processes or it remains a totally different entity. It completely integrates with their developer workflow. And with what we have announced with overflow AI even more so and we can talk about that next. But with the currents that just you know, pre overflow AI stack overflow teams integrates with your code repository with GitHub, it integrates with you know, JIRA for your ticket thing systems it integrates with octa integrates with Slack integrates with Microsoft teams. So the idea is to really sort of make sure that you are in the flow of your work and you're not context switching. And you just have access to accurate information the right place right time irrespective of where you are in the developer workflow. Sometimes what happens is that when organization like stack overflow you embrace our technology, it also sends a message to the to the to the rest of the world. Hey, the people who are using these tools, it breeds confidence between those tools, those technologies as well. So let's now talk about overflow AI. Yeah, so you know, we were super thrilled to announce overflow AI. Last week at the we are developers conference in front of thousands of our developers in the community. And this has been by the way months in the making. We had carved out 10% of our company to focus on building these amazing solutions. And now the response has been absolutely tremendous over the past, you know, a few days since we've actually made the announcement publicly. So overflow AI is us leveraging genitive AI capabilities in both our public stack overflow as well as stack overflow for teams. And it's really bringing together those two things I mentioned earlier, which is community and AI the power of both those things, the intersection of both those things to our users and customers. So the five things we announced. Number one is really providing fantastic search capabilities on the public platform. And what does this mean overflow AI search leverages semantic search where they're able to have a natural language conversation with stack overflow. You know how do you do this thing in Python, and you're going to get a generative AI answer that is going to summarize content from our 58 million questions and answers from our public platform, provide citations and attribution to where the answer is coming from or how did it actually come up with the answer that it did. And here's all the links to those. It's embedded in the answer, the generative answer, including the experts, you know, the world's best JavaScript expert actually contributed to that generative answer as an example, in an implied way. And it gives you the ability to provide feedback based on that answer, whether that helped you or not. You can if it didn't completely solve your problem, you can have a natural language conversation with overflow AI straight on stack overflow, where you can extend that conversation for deeper provide more context even add in your code. And it will provide even better search results and more refined generative AI and kind of summarize search results and answers. And all of that is sort of a single player type of experience where until you can just engage with the generative AI overflow AI capability. And if none of that work, then you can still post it in our community and and get the opportunity to somebody an expert to respond. So this is number one, which is search capabilities on public stack overflow. And what this does is it opens up the opportunity for people of all levels of capability to engage on stack overflow. Historically, the level had to be pretty high for you to engage on stack overflow you'd be an expert and so on. But now this is like anybody can have this experience and still get the best of what the platform offers again based on the 58 million questions and answers. So that's number one. The, the number two piece on the public platform is that we've also launched an entire area of AI community discussions where people can really sort of engage on as I mentioned earlier, generative AI topics like prompt engineering, natural language processing. We now have the ability for people to have real discussions on the public platform with their subject matter experts. This is this is related to the AI announcement. But we wanted to really make sure we promote learning for people because the space is moving so rapidly that we want to provide that capability. So that's that sort of focused on the public platform. Now as we move to stack overflow for teams, we have the first piece is something called overflow AI enterprise knowledge ingestion. So what we're able to do with this is really use generative AI to point to existing knowledge bases in the company could be confluence or SharePoint or GitHub or, or Google Drive and really ingest all that information into stack overflow for teams, instantaneously create Q&A pairs, automatically create tag suggestions, subject matter experts, and then give the option for the for the customer to choose whether to ingest these are not based on the quality and also dial up and down, which are, you know, what are qualified to actually be ingested. And this does this happens in minutes. And so what this allows you to do is to bootstrap a stack overflow community within your company in very, very rapidly, right? So there's no cold start problem that many software products have. And this is really tremendous way to leverage this to get your community flywheel going within your company. So that's the second large announcement. The third one is around enhanced search capabilities, like on the public platform that I explained. Now what we're also able to do in stack overflow for teams is provide ask a natural language question. How do I do this on, you know, could be Google Cloud X, Y, Z service. And the answer is going to come back from the public stack over 58 million questions answers but also from your stack overflow for teams, you know, repository within your own company, and it's going to summarize it in a generative AI answer with again links and attribution to all the source, you know, the source content, but also, so importantly, also bring back a links to other repositories within your company, even outside of stack overflow. So you could provide a confluence link, a GitHub link, it could provide all these other elements and search in our opinion and companies has been broken for a long time. So this we really wanted to address that by building this amazing enhanced search capability, which really sort of, you know, is in this kind of this phase in the in the sphere of enterprise search, etc, which is really what's been in that category has been around for a long time. So we're very excited about this capability. And then the next two announcements, our capabilities are all about keeping developers in their flow of work. So it's about what we did what we did announces this overflow AI visual studio code extension, where now for the first time you have the ability to surface stack overflow content, both public stack overflow from 58 million questions and answers as well as your private stack overflow content in your IDE, through a genitive AI capability and conversational interface where you're able to ask again a natural language question, it's going to provide you again with all the answers in the flow as as your writing code or generating code on the left side of the screen in the IDE and visual studio code, it's going to provide links to all the relevant content from stack overflow public as well as stack overflow private, and you're able to really then have a lot of context as you encounter issues and you want to start things and so on. And then the final one is providing is providing the same capabilities genitive AI capabilities in your slack in your slack interface. And this is really again you're able to have natural language conversations in your slack interface, people spend a lot of time on in their chat ops, and again surface public stack overflow as well as private stack overflow content, and have a conversational interface to be able to do that so those are the five that be that we announced so really sort of a robust, you know, set of announcements. How much of these, you know, kind of capabilities that you build were also kind of based on you did touch upon some of those pain point that are actually facing today so if this is coming through from your users and less from you. We are here to serve our developers ecosystem of community, our ecosystem of developers in our community as well as customers who we've been working with on stack overflow for teams.  And so in that context, we have been observing what challenges that they've been facing. We have a developer survey like I mentioned to you that was responded to by 90,000 people this year. So we look at all of that. And we have been engaged with both developers in our public community, as well as our customers and stack overflow teams to build these overflow AI capabilities over the past several months. So they've been very much part of giving us the right input to make sure that we we ultimately build something that's highly valuable to them. Of course, there are certain things that you cannot talk about this point there, but the things are in the pipeline, the roadmap. But in general, if I ask you what are the next thing we can expect from you, okay, you're like, these are the things that we are working on to further improve, you know, developer experience or to help organizations in that journey. And what we've discovered is that the value of the, we've got a long list of ideas, firstly, that we've got and that we are always looking at and exploring the goal for us to make sure that we firstly launch these things here. And then in August to make sure that we open this up to as many developers and customers as we can. And then go from that process all the way to general availability over the next several months, and really sort of iterate based on even more customer feedback to your earlier point, which is we want to make sure that customers and users drive in many ways, you know, how we how we continuously build this. But overall, you know, we just believe that the opportunity set is significant here, because the value of Stack O flows historical data that we have from 15 years, we've been running several experiments on that topic behind the scenes as in the power of layering in certain data sets on top of let's say open source models. And what does that actually produce and how efficiently can it produce because one of the issues with with general AI is that it's extremely expensive proposition at the moment right specifically for companies trying to build some of these capabilities. And we've realized that our data is fantastically powerful. You can build very lightweight models which produce tremendous outputs and high quality outputs that you know right you know that are commensurate with what you see in the news with some of the very expensive models that people have built. And that gives us a lot of flexibility to do things for our users and customers, especially from a from a unit economic standpoint. So that's just to give you a sense what notes around how to be provide more and more insightful, right place right time context for our for our users and customers and do it sort of at very, very large scale with with cost in mind. And as you said, no, we will be leveraging a lot of genetic AI, but you also kind of stressed on the importance of actual people, actual developers, subject matter experts. And, of course, adoption of detail. What role do you see is tag or flow or these technologies that you folks are building will build in within organizations as they will be leveraging those technologies because they will need a lot of help. And with cloud cloud what they had done is it has enabled a lot of organizations who would otherwise not been able to get on journey to get started very quickly. So talk about the role that you folks will be playing in future. We believe that we've got this large data set firstly on the public platform, which is the place where people are able to really build new technologies answer each other's questions as we develop new innovation happens very rapidly on our platform, much like it does within companies as people try to, you know, go through technology transformations and they want to learn from new things and their colleagues, etc. What we notice is that what's shifting is this notion this nature of you know self service right where people are at lowest the barrier to entry as we talked about with people sort of being able to access information in a very reasonable way with Genitive AI. So yes it's going to open things up it's going to open things up where people the friction of actually learning and engaging is going to be so much lower because you're engaging with something like overflow AI, and you're getting sort of this collective wisdom of, you know, tens of millions of developers who have who have contributed to that, and that knowledge over the past 15 years. So developers will be able to learn very rapidly as a result of this be more productive, efficient. I think all those things are powerful both within companies and just generally in the ecosystem. And that is going to result in, as we talked about earlier, a just a huge productivity boom, where people are just going to be able to do a lot more with, you know, very, a lot faster than historic than history. And that's all very exciting for us as we as we keep moving into this phase. Prashant, thank you so much for taking time out today. And of course, I really appreciate the whole discussion on not just the developer journey, but also how they can leverage Genitive AI and how you folks actually could help them. So thanks for all those insights. And I would love to chat with you folks again, because I can see there are a lot of things in the pipeline. Thank you. Indeed. Thank you Swapnil. I appreciate the questions.


Hi, I'm Chelsea Hopkins. I'm the Outreach and Volunteer Coordinator with Yolo Basin Foundation. We're excited to be here today at Sudwork for a big day at the dock. Yolo Basin Foundation does environmental education and outreach for the wildlife and wetlands in the Yolo Basin area. We have school programs that reach about 4,000 kids every year. We have our Bat Talk and Walk programs throughout the summer so you can come see the bats fly out from under the causeway.


Hello students, myself Ganesh Biajlawe working as an assistant professor in Department of Mechanical Engineering, Walchain Institute of Technology, Singapore. In this fifth session of extended surfaces or fins, we will see few numericals. Learning outcome. At the end of this session, students will be able to evaluate fin performance. Now, we will see first numerical. The statement is, it is required to heat oil to about 300 degree Celsius for frying purpose. A ladle is used in the frying. The section of the handle is 5 mm by 18 mm. The surrounding are at 30 degree Celsius. The conductivity of the material is 205 watt per meter Kelvin. If the temperature at a distance of 380 mm from the oil should not reach 40 degree Celsius. Determine the convective heat transfer coefficient. Now, as per the statement, we should see the given data. A ladle is given, so it is required to heat oil to about 300 degree Celsius for frying purpose. A ladle is used in the frying. The section of the handle is 5 mm by 18 mm. The surrounding temperature T infinity temperature is 30 degree Celsius. The conductivity of the material is 205 watt per meter Kelvin. If the temperature at a distance, so suppose this is the origin and consider this as 380 mm distance and the given temperature is 40 degree Celsius, 40 degree Celsius. Then they are asked to find the convective heat transfer coefficient, convective heat transfer coefficient. Now, we can use the condition of, we can use the equation theta by theta naught is equal to e raise to minus mx. Now, this theta is nothing but T minus T infinity by T naught minus T infinity, which is equal to e raise to m and x is 0.380 meter. Now, here we can substitute T T infinity, T naught T infinity. Then we will get m as we know m is nothing but square root of HP by KA and this value we will get as 8.673. Now, we can calculate perimeter area, KA is also given. So, after substituting the values, we will get the edge as 30.17 watt per meter Kelvin. So, this is the convective heat transfer coefficient, this is the answer. Now, we will move to the next number, the statement is a pinfin 2.5 mm diameter is made of copper, conductivity is given 396 watt per meter Kelvin. It protrudes from a wall maintained at 95 degree Celsius and placed in 25 degree Celsius air. The convective heat transfer coefficient over the fin is 10 watt per meter square Kelvin. Calculate the heat loss for fin for infinite length. Now, we will write the given data, a pinfin of diameter 2.5 mm protrudes from the wall, which is maintained means base temperature becomes 95 degree Celsius and it is placed in the surrounding where temperature is 25 degree Celsius air. The convective heat transfer coefficient between the fin and the surrounding is 10 watt per meter square Kelvin. Now, they asked to find the heat loss, infinite length of the fin, this second case we required to consider. Now, first we will find out the m value, which is equal to square root of H p k a, H is given perimeter pi by 4 d square into L, a pydial perimeter is pydial and air is pi by 4 d square k conductivity is 396, we will obtain m as 6.36, then as we know the rate of heat conduction through the infinite length fin. In last sessions, we have derived the equation, so q is equal to square root of H p k a theta naught, which is equal to square root of H p k a theta naught is a t naught minus t infinity, which is equal to H given is 10, this is pi d L into k is 396 into air is pi by 4 d square. So, this is H p k a, t naught is 95 minus 25, sorry here only pi d, pi d. So, if you substitute here, then you do the now calculation, you will get the answer as 0.861 watt, depending upon the given cases, the rate of heat transfer formulae changes, then the temperature distribution relations also changes. For given numerical, the material given is copper, so we use the conductivity of the copper, given conductivity, we can analyze the problem, same problem we can analyze for different materials. For example, if the material is copper, we got the answer as 0.61, you can alter it, you change the material instead of copper, instead of copper you take the aluminum, find out the rate of heat transfer, for gold, for silver etcetera, you can find out the cube, then this is the homework, you find out, you can plot the rate of heat transfer for different materials. So, you find out the curve, or you can plot the histogram, and from that you can select that particular material, depending upon the budget available for that particular application. For further study, you can refer fundamentals of heat and mass transfer by Incropera David. Thank you.