1 00:00:04,160 --> 00:00:07,160 Speaker 1: Get in touch with technology with tech Stuff from how 2 00:00:07,200 --> 00:00:13,920 Speaker 1: stuff works dot com. Hey there, and welcome to tech Stuff. 3 00:00:13,960 --> 00:00:17,680 Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer over 4 00:00:17,680 --> 00:00:20,280 Speaker 1: at how Stuff Works and I love all things tech, 5 00:00:20,880 --> 00:00:25,160 Speaker 1: and today I'm doing an episode based off a listener request. 6 00:00:25,760 --> 00:00:29,840 Speaker 1: Nelly asked if I might do an episode about Instagram, 7 00:00:29,880 --> 00:00:32,879 Speaker 1: And as it turns out, Instagram is a pretty interesting 8 00:00:32,920 --> 00:00:37,040 Speaker 1: story and big enough so that it necessitates two episodes. 9 00:00:37,159 --> 00:00:39,680 Speaker 1: So this is our first one talking about the birth 10 00:00:39,760 --> 00:00:42,520 Speaker 1: of Instagram, and in our next episode will continue that story. 11 00:00:42,560 --> 00:00:45,479 Speaker 1: But today we're gonna talk about an app that started 12 00:00:45,520 --> 00:00:47,760 Speaker 1: off as a project that was meant to help a 13 00:00:47,800 --> 00:00:50,760 Speaker 1: young fellow learn how to code, and it turned into 14 00:00:50,840 --> 00:00:54,520 Speaker 1: a billion dollar acquisition deal. It's one of those Silicon 15 00:00:54,720 --> 00:00:58,360 Speaker 1: Valley fairy tales that thousands of people chase after, but 16 00:00:58,440 --> 00:01:01,320 Speaker 1: only a select few ever atchieve. So we're going to 17 00:01:01,320 --> 00:01:04,920 Speaker 1: look at the Instagram story. And Instagram was designed by 18 00:01:05,000 --> 00:01:09,600 Speaker 1: co founders Kevin Systrom and Mike Krieger, and they launched 19 00:01:09,640 --> 00:01:12,640 Speaker 1: it in twenty ten. But our story will begin a 20 00:01:12,640 --> 00:01:15,559 Speaker 1: little earlier than that, because you guys know, I love 21 00:01:15,640 --> 00:01:17,960 Speaker 1: my history. So let's begin with a quick look at 22 00:01:18,000 --> 00:01:21,800 Speaker 1: the backgrounds of the two founders. Kevin Systram was born 23 00:01:21,840 --> 00:01:26,080 Speaker 1: in nineteen three in Holliston, Massachusetts, and his parents are 24 00:01:26,160 --> 00:01:29,399 Speaker 1: Douglas Systrom, a vice president of human resources at the 25 00:01:29,440 --> 00:01:34,320 Speaker 1: department store corporation t j X Companies, and his mother, Diane, 26 00:01:34,360 --> 00:01:36,560 Speaker 1: is an executive in the marketing department at zip Car 27 00:01:36,640 --> 00:01:39,319 Speaker 1: and has worked at other startups. He attended school and 28 00:01:39,400 --> 00:01:44,040 Speaker 1: Conquered Massachusetts at a private school called Middlesex School, a 29 00:01:44,040 --> 00:01:47,440 Speaker 1: boarding school or private school rather, which has fewer than 30 00:01:47,520 --> 00:01:50,840 Speaker 1: four hundred students total, and, according to The New York Times, 31 00:01:51,080 --> 00:01:53,600 Speaker 1: has nearly as many acres in land as it has 32 00:01:53,760 --> 00:01:58,280 Speaker 1: students enrolled. So this is not a Rags to riches Dale. 33 00:01:58,680 --> 00:02:01,800 Speaker 1: This is more of a rich's to Holy Cow, you 34 00:02:01,840 --> 00:02:06,560 Speaker 1: are so incredibly rich tale for Mr Systram. In addition 35 00:02:06,600 --> 00:02:09,480 Speaker 1: to his studies, he became a fan of the computer 36 00:02:09,639 --> 00:02:13,400 Speaker 1: first person shooter game Doom too, And I talked about 37 00:02:13,440 --> 00:02:15,840 Speaker 1: that in a couple of episodes way back when when 38 00:02:15,840 --> 00:02:19,120 Speaker 1: I was covering things like it. The Doom franchise was 39 00:02:19,160 --> 00:02:22,200 Speaker 1: one of a handful of games that launched level developer 40 00:02:22,280 --> 00:02:25,440 Speaker 1: tools to the community. That meant that if you liked 41 00:02:25,480 --> 00:02:28,359 Speaker 1: you could download those tools for yourself and you could 42 00:02:28,360 --> 00:02:31,720 Speaker 1: actually build your own maps for the game system. Began 43 00:02:31,760 --> 00:02:35,000 Speaker 1: to do that and also started studying computer programming, though 44 00:02:35,040 --> 00:02:38,680 Speaker 1: really only more as an enthusiast. He would not pursue 45 00:02:38,720 --> 00:02:43,360 Speaker 1: a degree in computer science after school. Systrom enrolled in 46 00:02:43,440 --> 00:02:47,560 Speaker 1: Stanford University back in two thousand two, studying management science 47 00:02:47,639 --> 00:02:51,680 Speaker 1: and engineering, so essentially the business classes over at Stanford, 48 00:02:51,919 --> 00:02:55,560 Speaker 1: and Stanford was or still is actually located near Silicon 49 00:02:55,720 --> 00:02:58,640 Speaker 1: Valley in California, and it's one of those places where 50 00:02:58,639 --> 00:03:03,600 Speaker 1: ambitious students and grew investors often collide. They meet up 51 00:03:03,680 --> 00:03:06,880 Speaker 1: with each other, they share ideas, and frequently students are 52 00:03:06,960 --> 00:03:09,320 Speaker 1: looking to get recruited right off school into one of 53 00:03:09,320 --> 00:03:13,000 Speaker 1: the big tech companies and uh they that ends up 54 00:03:13,040 --> 00:03:18,560 Speaker 1: just being a rich pool of talent for companies like Apple, Google, Microsoft, 55 00:03:19,280 --> 00:03:22,640 Speaker 1: and all the startups as well. Systrom spent a winter 56 00:03:22,720 --> 00:03:27,120 Speaker 1: semester at Stanford in Florence. He actually went to Florence 57 00:03:27,120 --> 00:03:30,720 Speaker 1: to study abroad, studying photography in particular, so he had 58 00:03:30,720 --> 00:03:34,639 Speaker 1: an interest in photography long before Instagram was ever a thing, 59 00:03:35,200 --> 00:03:37,960 Speaker 1: and at this time the iPhone had yet to appear 60 00:03:38,000 --> 00:03:40,280 Speaker 1: and cell phone cameras were fairly primitive, so he was 61 00:03:40,360 --> 00:03:44,640 Speaker 1: using actual film cameras and higher in digital cameras. In 62 00:03:44,680 --> 00:03:47,800 Speaker 1: two thousand five, System became part of a special work 63 00:03:47,880 --> 00:03:52,720 Speaker 1: study program called the Mayfield Fellows Program. Only twelve students 64 00:03:52,760 --> 00:03:56,480 Speaker 1: are selected to do this each year at Stanford. Coincidentally, 65 00:03:56,800 --> 00:03:59,520 Speaker 1: Mike Kreeger, the other co founder, would be selected for 66 00:03:59,600 --> 00:04:02,600 Speaker 1: that same program in two thousand seven, though at that 67 00:04:02,680 --> 00:04:05,200 Speaker 1: time sisterm and Krieger didn't really know each other that well. 68 00:04:05,560 --> 00:04:08,520 Speaker 1: Systems work in the program led to an internship at 69 00:04:08,520 --> 00:04:12,720 Speaker 1: a company called Odeo. Now I've covered Odio in the past, 70 00:04:12,800 --> 00:04:17,039 Speaker 1: but here's a very quick refresher. Odio started out as 71 00:04:17,040 --> 00:04:21,719 Speaker 1: a podcast focused company, not necessarily to produce podcasts, not 72 00:04:21,800 --> 00:04:25,840 Speaker 1: a content creator, but rather as a way to publish podcasts, 73 00:04:25,880 --> 00:04:29,799 Speaker 1: to subscribe to podcasts, and to follow podcasts. But Odio 74 00:04:29,880 --> 00:04:35,640 Speaker 1: faced serious stiff competition, namely in iTunes, and ultimately the 75 00:04:35,680 --> 00:04:38,919 Speaker 1: company would pivot to a different project that one of 76 00:04:38,960 --> 00:04:41,480 Speaker 1: its employees had been working on for a while. It 77 00:04:41,560 --> 00:04:43,680 Speaker 1: was a little messaging app that would let users send 78 00:04:43,680 --> 00:04:47,640 Speaker 1: out a quick hundred forty character message to followers, and 79 00:04:47,720 --> 00:04:51,280 Speaker 1: it would end up being called Twitter Systrom joined the 80 00:04:51,400 --> 00:04:55,120 Speaker 1: Sigma New fraternity while he was at Stanford, and he 81 00:04:55,200 --> 00:04:58,920 Speaker 1: gained a reputation for being creative and particularly talented and 82 00:04:59,080 --> 00:05:03,719 Speaker 1: making visually appealing presentations and videos. During his senior year, 83 00:05:04,000 --> 00:05:07,039 Speaker 1: he was encouraged to drop out of school and joined 84 00:05:07,080 --> 00:05:10,520 Speaker 1: the Facebook team, which was just really getting started at 85 00:05:10,560 --> 00:05:13,960 Speaker 1: the time. System actually turned down that offer after chatting 86 00:05:13,960 --> 00:05:17,320 Speaker 1: with friends and concluding that Facebook was likely just a fad. 87 00:05:17,600 --> 00:05:20,120 Speaker 1: I think things turned out all right for Sistrom in 88 00:05:20,200 --> 00:05:23,800 Speaker 1: the end, however, even though he missed that opportunity. After 89 00:05:23,880 --> 00:05:27,600 Speaker 1: graduating Stanford in two thousand and six, Systrom joined the 90 00:05:27,680 --> 00:05:29,760 Speaker 1: ranks of Google in a move that many of his 91 00:05:29,839 --> 00:05:34,120 Speaker 1: peers felt was a safe but somewhat uninspired decision. Google 92 00:05:34,120 --> 00:05:36,839 Speaker 1: had already kind of established itself by two thousand six, 93 00:05:36,880 --> 00:05:39,640 Speaker 1: it was no longer in that crazy start up phase, 94 00:05:40,080 --> 00:05:43,160 Speaker 1: and System would stay with Google for about three years, 95 00:05:43,279 --> 00:05:46,920 Speaker 1: leaving to join a company called next Stop. Next Up 96 00:05:46,960 --> 00:05:49,960 Speaker 1: was founded by a former Google employee, or actually a 97 00:05:49,960 --> 00:05:52,919 Speaker 1: couple of former Google employees, and it was a social 98 00:05:52,960 --> 00:05:56,760 Speaker 1: travel recommendation site. The idea was the site would help 99 00:05:56,800 --> 00:05:59,560 Speaker 1: people find fun things to do in new locations, so 100 00:05:59,640 --> 00:06:03,520 Speaker 1: you could post about things that were interesting at different 101 00:06:03,560 --> 00:06:06,520 Speaker 1: places in the world, and that's where we're gonna leave 102 00:06:06,600 --> 00:06:08,800 Speaker 1: Mr Systram for the time being. We're gonna switch to 103 00:06:08,839 --> 00:06:12,440 Speaker 1: the other co founder, Mike Krieger. Krieger was born in 104 00:06:12,560 --> 00:06:15,680 Speaker 1: nineteen eighty six and sal Paulo, Brazil. His father is 105 00:06:15,720 --> 00:06:18,880 Speaker 1: an executive who traveled extensively, and so Kreeger spent time 106 00:06:18,880 --> 00:06:22,240 Speaker 1: in places like Portugal, Argentina, and the United States as 107 00:06:22,279 --> 00:06:24,840 Speaker 1: he was growing up. He got his first computer when 108 00:06:24,880 --> 00:06:28,240 Speaker 1: he was four years old, So yeah, this is also 109 00:06:28,440 --> 00:06:31,520 Speaker 1: not a rag Store Riches story for Mr Kreeger. By 110 00:06:31,520 --> 00:06:35,040 Speaker 1: the age of six, Kreeger was already starting to experiment 111 00:06:35,120 --> 00:06:38,320 Speaker 1: with coding, mostly in an effort to enhance his gaming 112 00:06:38,360 --> 00:06:41,240 Speaker 1: experience on his Windows based computer. So you're starting to 113 00:06:41,279 --> 00:06:46,440 Speaker 1: sense a theme here, kids getting into coding through computer games. 114 00:06:46,440 --> 00:06:48,920 Speaker 1: By the time he was a teenager, he was acting 115 00:06:48,960 --> 00:06:52,120 Speaker 1: as a mentor to maintenance personnel in an after school 116 00:06:52,200 --> 00:06:54,960 Speaker 1: education program at his high school. So he would go 117 00:06:55,400 --> 00:06:58,200 Speaker 1: attend high school and afterwards he would help teach people 118 00:06:58,240 --> 00:07:01,080 Speaker 1: how to develop computers skills so that they could get 119 00:07:01,120 --> 00:07:03,960 Speaker 1: better jobs. It was kind of cool. When he turned eighteen, 120 00:07:04,040 --> 00:07:06,960 Speaker 1: he was accepted to Stanford University, and that was in 121 00:07:07,080 --> 00:07:11,720 Speaker 1: two thousand four. Kriegers major was in symbolic Systems, with 122 00:07:11,800 --> 00:07:16,840 Speaker 1: a focus on human computer interaction. That discipline combines elements 123 00:07:16,880 --> 00:07:21,120 Speaker 1: not just of technology, but also psychology and several other 124 00:07:21,160 --> 00:07:23,920 Speaker 1: important movers and shakers in the tech world graduated with 125 00:07:24,000 --> 00:07:27,520 Speaker 1: similar degrees, and as I mentioned earlier, Krieger, like Systrom, 126 00:07:27,600 --> 00:07:29,880 Speaker 1: was part of the Mayfield Fellows program, so he was 127 00:07:29,920 --> 00:07:33,120 Speaker 1: also one of those twelve students. While in college, Krieger 128 00:07:33,280 --> 00:07:36,960 Speaker 1: interned with Microsoft. He would work on power Point as 129 00:07:37,000 --> 00:07:40,360 Speaker 1: a project manager. He also interned at a company called 130 00:07:40,360 --> 00:07:44,120 Speaker 1: fox Marks, which creates a browser add on that allows 131 00:07:44,200 --> 00:07:48,160 Speaker 1: users to synchronize passwords and bookmarks across multiple computers and 132 00:07:48,240 --> 00:07:51,239 Speaker 1: over there he served as a software developer, and after 133 00:07:51,240 --> 00:07:54,360 Speaker 1: he graduated Stanford, Krieger went on to work for a 134 00:07:54,400 --> 00:07:57,520 Speaker 1: company called me Bo. Me Bo was a web based 135 00:07:57,560 --> 00:08:01,040 Speaker 1: instant messaging provider as well as something of a social network. 136 00:08:01,520 --> 00:08:06,000 Speaker 1: So in early System is that next stop, which would 137 00:08:06,080 --> 00:08:09,400 Speaker 1: later be acquired by Facebook, and Krieger was at me Bow, 138 00:08:09,560 --> 00:08:11,880 Speaker 1: which in two thousand twelve would be acquired by Google, 139 00:08:12,360 --> 00:08:15,080 Speaker 1: and System was working on a little side project since 140 00:08:15,120 --> 00:08:17,560 Speaker 1: two thousand nine that Krieger got a chance to try 141 00:08:17,560 --> 00:08:19,720 Speaker 1: out because the two knew of each other, but at 142 00:08:19,760 --> 00:08:22,720 Speaker 1: that point they hadn't really worked together. And that sets 143 00:08:22,760 --> 00:08:27,320 Speaker 1: the ground for the predecessor for Instagram, which I'll talk 144 00:08:27,360 --> 00:08:29,480 Speaker 1: about in just a second, But first let's take a 145 00:08:29,560 --> 00:08:39,480 Speaker 1: quick break to thank our sponsor. So before we went 146 00:08:39,520 --> 00:08:42,120 Speaker 1: to the break, I mentioned that System had been working 147 00:08:42,200 --> 00:08:45,160 Speaker 1: on a project since two thousand nine. That project was 148 00:08:45,200 --> 00:08:48,679 Speaker 1: called Bourbon, but it was spelled b U r b 149 00:08:49,000 --> 00:08:53,319 Speaker 1: N because it's an app and apps hate vowels, I guess, 150 00:08:54,240 --> 00:08:58,160 Speaker 1: and Bourbon is apparently System's favorite drink, and he was 151 00:08:58,200 --> 00:09:00,600 Speaker 1: working on it over the weekends when he wasn't doing 152 00:09:00,600 --> 00:09:02,840 Speaker 1: his normal work either at Google or then later at 153 00:09:02,920 --> 00:09:06,120 Speaker 1: Next Stop, and it was a bit of an odd beast. 154 00:09:06,240 --> 00:09:09,840 Speaker 1: Systrom had aspirations of launching his own app and potentially 155 00:09:09,880 --> 00:09:13,080 Speaker 1: his own company, and Bourbon was really the where he 156 00:09:13,120 --> 00:09:16,160 Speaker 1: was cutting his teeth on app development because that really 157 00:09:16,200 --> 00:09:19,600 Speaker 1: wasn't what he had studied. He knew about the power 158 00:09:19,640 --> 00:09:22,760 Speaker 1: of apps, and he was convinced that mobile was going 159 00:09:22,800 --> 00:09:25,600 Speaker 1: to be the biggest thing moving forward. This was in 160 00:09:26,280 --> 00:09:30,000 Speaker 1: when Mobile was already doing quite well and Bourbon was 161 00:09:30,040 --> 00:09:33,040 Speaker 1: in many ways a project that System was using to 162 00:09:33,240 --> 00:09:36,240 Speaker 1: learn how to develop apps, how to use HTML five, 163 00:09:36,280 --> 00:09:39,600 Speaker 1: and what sort of features users would actually want. Now, 164 00:09:39,720 --> 00:09:42,360 Speaker 1: remember that while System was interested in all this, he 165 00:09:42,400 --> 00:09:44,720 Speaker 1: still didn't have that degree in computer science or anything 166 00:09:44,760 --> 00:09:47,280 Speaker 1: like that, and so Bourbon ended up being kind of 167 00:09:47,320 --> 00:09:50,520 Speaker 1: a hydra, a mini headed creature that was trying to 168 00:09:50,520 --> 00:09:53,280 Speaker 1: do a lot of things all at once. For one thing, 169 00:09:53,600 --> 00:09:55,760 Speaker 1: it was a check in service, similar to what four 170 00:09:55,800 --> 00:09:58,199 Speaker 1: Square used to be. You could visit a place and 171 00:09:58,320 --> 00:10:00,720 Speaker 1: use the app to check in. He let your friends 172 00:10:00,760 --> 00:10:03,280 Speaker 1: know you had visited. You could make recommendations to friends, 173 00:10:03,320 --> 00:10:06,160 Speaker 1: and you could plan for future get togethers at specific spots, 174 00:10:06,559 --> 00:10:09,319 Speaker 1: which would earn you points in a sort of gamified 175 00:10:09,440 --> 00:10:13,000 Speaker 1: element in the app. System had cited the social network 176 00:10:13,040 --> 00:10:15,520 Speaker 1: game Mafia Wars as an influence on some of the 177 00:10:15,520 --> 00:10:18,600 Speaker 1: app design, and you could upload photos to the app 178 00:10:18,720 --> 00:10:22,319 Speaker 1: and share those with your friends as well. Krieger was 179 00:10:22,360 --> 00:10:25,560 Speaker 1: an early user of Bourbon, and Systram had conversations with 180 00:10:25,600 --> 00:10:28,560 Speaker 1: the Krieger focusing on ways to enhance the app's features 181 00:10:28,559 --> 00:10:32,960 Speaker 1: and make things better. Meanwhile, System continued life in Silicon Valley, 182 00:10:33,080 --> 00:10:35,880 Speaker 1: which included going to networking events and to try to 183 00:10:35,880 --> 00:10:39,840 Speaker 1: make connections with other entrepreneurs and developers. At one such 184 00:10:39,880 --> 00:10:43,120 Speaker 1: event hosted by a startup called Hunch, Systram met a 185 00:10:43,120 --> 00:10:47,280 Speaker 1: guy named Steve Anderson who was the founder of Baseline Ventures, 186 00:10:47,320 --> 00:10:51,280 Speaker 1: which is an investment firm. Anderson looked at a prototype 187 00:10:51,280 --> 00:10:54,480 Speaker 1: build of Bourbon and agreed to invest in the development 188 00:10:54,480 --> 00:10:57,440 Speaker 1: of the app to the tune of two fifty dollars 189 00:10:57,520 --> 00:11:00,559 Speaker 1: is a pretty big of agreement. He also recommended System 190 00:11:00,679 --> 00:11:03,280 Speaker 1: that he find a collaborator to work with more closely 191 00:11:03,720 --> 00:11:07,880 Speaker 1: and not just become a personal echo chamber. In March, 192 00:11:08,640 --> 00:11:12,640 Speaker 1: System decided to pursue Bourbon as an actual entrepreneurial opportunity, 193 00:11:12,960 --> 00:11:15,439 Speaker 1: and he quit his job at next Stop, which was 194 00:11:15,480 --> 00:11:18,920 Speaker 1: a pretty easy decision to make, especially after Mark Andresen 195 00:11:19,040 --> 00:11:22,640 Speaker 1: added to that initial investment with two fifty thousand dollars 196 00:11:22,679 --> 00:11:25,360 Speaker 1: of his own, which brought that launch investment up to 197 00:11:25,440 --> 00:11:28,560 Speaker 1: half a million dollars. And Systrom was able to convince 198 00:11:28,640 --> 00:11:32,160 Speaker 1: Kreeger a couple of months later in May to quit 199 00:11:32,200 --> 00:11:34,120 Speaker 1: his job at me Bo and come work with him 200 00:11:34,120 --> 00:11:37,520 Speaker 1: on the project, and so the two co founders joined forces. 201 00:11:38,040 --> 00:11:41,640 Speaker 1: They set up shop at a place called dog Patch Labs, 202 00:11:41,800 --> 00:11:44,880 Speaker 1: which was a company that offered up shared office space 203 00:11:44,960 --> 00:11:48,400 Speaker 1: for the startup tech companies in the Bay Area. Companies 204 00:11:48,400 --> 00:11:50,720 Speaker 1: that did not yet have an office of their own 205 00:11:50,800 --> 00:11:53,840 Speaker 1: could rent out space at dog Patch Labs, and before 206 00:11:53,920 --> 00:11:57,760 Speaker 1: long the two decided that they weren't really on the 207 00:11:57,840 --> 00:12:01,400 Speaker 1: right track. They had come to the conclusion that Bourbon 208 00:12:01,480 --> 00:12:04,320 Speaker 1: was just too similar to four Square, which was already 209 00:12:04,400 --> 00:12:07,319 Speaker 1: an established app at that time, and they also felt 210 00:12:07,360 --> 00:12:10,200 Speaker 1: the service was just too busy and cluttered. It had 211 00:12:10,320 --> 00:12:13,280 Speaker 1: so many features that was a little confusing as to 212 00:12:13,320 --> 00:12:17,000 Speaker 1: what it was intended to do. And thus, in June 213 00:12:17,640 --> 00:12:21,559 Speaker 1: they decided to engage in the great tradition of app development, 214 00:12:22,120 --> 00:12:24,720 Speaker 1: the pivot. And I mentioned a pivot a little bit earlier, 215 00:12:24,720 --> 00:12:27,920 Speaker 1: but what exactly is that. Well, a pivot in Silicon 216 00:12:28,080 --> 00:12:31,840 Speaker 1: Valley speak is when you realize you've done messed up 217 00:12:32,120 --> 00:12:34,560 Speaker 1: and you need to try something else. So if you 218 00:12:34,600 --> 00:12:38,360 Speaker 1: ever hear about a company pivoting, what that's really saying 219 00:12:38,840 --> 00:12:40,880 Speaker 1: is that the people in charge realized that what they 220 00:12:40,880 --> 00:12:43,720 Speaker 1: had been doing is just not working and they'd better 221 00:12:43,760 --> 00:12:47,240 Speaker 1: do something else or they're going to face ugly consequences. 222 00:12:48,000 --> 00:12:50,679 Speaker 1: For Kreeger and Systrom, that meant taking a look at 223 00:12:50,720 --> 00:12:52,960 Speaker 1: their app and then trying to figure out what they 224 00:12:53,040 --> 00:12:55,679 Speaker 1: might be able to salvage from it. And while the 225 00:12:55,760 --> 00:12:58,720 Speaker 1: check in services were sewn up, one thing that stood 226 00:12:58,720 --> 00:13:02,439 Speaker 1: out was the idea of a photo sharing app. Their 227 00:13:02,480 --> 00:13:05,560 Speaker 1: first attempt at building a solo photo sharing app was 228 00:13:05,600 --> 00:13:08,400 Speaker 1: a failure. It didn't even get a new name, and 229 00:13:08,440 --> 00:13:11,000 Speaker 1: this was before they had entirely abandoned the hope for 230 00:13:11,040 --> 00:13:14,040 Speaker 1: a full featured bourbon app. But they got back to 231 00:13:14,120 --> 00:13:16,880 Speaker 1: it and they began to refine their approach, and one 232 00:13:16,920 --> 00:13:19,840 Speaker 1: thing that really helped them out was the inclusion of 233 00:13:19,880 --> 00:13:25,320 Speaker 1: a popular feature in Instagram, the photo filter. Systram tells 234 00:13:25,400 --> 00:13:29,040 Speaker 1: a story about being on vacation with his then girlfriend 235 00:13:29,240 --> 00:13:33,760 Speaker 1: now his wife, Nicole. Nicole was another Stanford graduate, and 236 00:13:34,280 --> 00:13:37,840 Speaker 1: she explained to Systrom that she never really liked sharing 237 00:13:37,880 --> 00:13:41,120 Speaker 1: the photos she was taking with her iPhone four because 238 00:13:41,120 --> 00:13:43,520 Speaker 1: she felt they never looked as good as she wanted 239 00:13:43,559 --> 00:13:46,960 Speaker 1: them to. And that inspired System to develop a filter 240 00:13:47,520 --> 00:13:51,600 Speaker 1: for photos taken by the iPhone four camera, and one 241 00:13:51,640 --> 00:13:55,440 Speaker 1: that would automatically adjust settings in a post processing approach, 242 00:13:55,760 --> 00:13:58,600 Speaker 1: so you didn't have to do all that messing around 243 00:13:58,640 --> 00:14:01,800 Speaker 1: with settings yourself. It would just automatically apply them and 244 00:14:01,840 --> 00:14:05,080 Speaker 1: make the image better. So it would change the color balance, 245 00:14:05,240 --> 00:14:07,920 Speaker 1: it would change the contrast, it would soften the edges, 246 00:14:08,320 --> 00:14:11,360 Speaker 1: adding a little bit of golden light to sweeten the image. 247 00:14:11,559 --> 00:14:13,720 Speaker 1: And he taught himself how to create the tools and 248 00:14:13,760 --> 00:14:17,600 Speaker 1: then developed his first filter, the x pro to filter, 249 00:14:17,760 --> 00:14:21,320 Speaker 1: And according to both System and Krieger, they would use 250 00:14:21,440 --> 00:14:25,120 Speaker 1: Photoshop to actually create the effects they wanted to create 251 00:14:26,080 --> 00:14:29,560 Speaker 1: within Photoshop, and then reverse engineer how to do that 252 00:14:29,600 --> 00:14:33,120 Speaker 1: within the app how to create those same effects uh 253 00:14:33,160 --> 00:14:36,880 Speaker 1: as an as a post processing trick with images taken 254 00:14:36,880 --> 00:14:41,280 Speaker 1: from a iPhone camera. Ultimately, Krieger and System decided that 255 00:14:41,320 --> 00:14:44,440 Speaker 1: their new app would allow users to share photos, to 256 00:14:44,560 --> 00:14:48,400 Speaker 1: leave comments, and to like images, as in you could 257 00:14:48,760 --> 00:14:51,360 Speaker 1: hit the little like button or the little heart button 258 00:14:51,400 --> 00:14:53,280 Speaker 1: and say, hey, that was a pretty cool picture. I 259 00:14:53,320 --> 00:14:56,720 Speaker 1: really enjoy it, and also to use filters. They needed 260 00:14:56,720 --> 00:14:59,840 Speaker 1: a new name, and they chose Instagram, which is a 261 00:15:00,000 --> 00:15:04,400 Speaker 1: portmanteau of instant and Telegram and also kind of hearkens 262 00:15:04,440 --> 00:15:07,640 Speaker 1: back to the instant cameras that Sistram had played with 263 00:15:07,680 --> 00:15:11,720 Speaker 1: when he was younger, like a classic Polaroid camera. It 264 00:15:11,760 --> 00:15:14,240 Speaker 1: took the two about eight weeks to go from the 265 00:15:14,320 --> 00:15:18,280 Speaker 1: idea to a full fledged app, and before they submitted 266 00:15:18,320 --> 00:15:21,200 Speaker 1: the app to the Apple App Store, they tested it 267 00:15:21,240 --> 00:15:25,000 Speaker 1: with their friends. And these were influential friends. It wasn't 268 00:15:25,120 --> 00:15:28,480 Speaker 1: just buddies who were in the neighborhood. These are people 269 00:15:28,520 --> 00:15:31,840 Speaker 1: like Jack Dorsey, who was the founder of Twitter. Not 270 00:15:32,040 --> 00:15:34,240 Speaker 1: bad idea. If you want to get some evangelists for 271 00:15:34,280 --> 00:15:37,360 Speaker 1: your product, you go after people who already have a 272 00:15:37,440 --> 00:15:41,800 Speaker 1: wide following. And a little after midnight on October six, 273 00:15:43,120 --> 00:15:46,880 Speaker 1: the Instagram app launched in the App Store. When it debuted, 274 00:15:47,120 --> 00:15:50,240 Speaker 1: it was an iPhone exclusive, and it would remain so 275 00:15:50,400 --> 00:15:52,520 Speaker 1: for more than a year and a half. The app 276 00:15:52,560 --> 00:15:55,960 Speaker 1: wouldn't be available on other platforms for a while, so 277 00:15:56,000 --> 00:15:59,120 Speaker 1: on the first day of it being available, about twenty 278 00:15:59,520 --> 00:16:03,920 Speaker 1: thousand people downloaded the app. They began taking photos, they 279 00:16:03,960 --> 00:16:08,000 Speaker 1: began sharing them and breaking the system. The system load 280 00:16:08,080 --> 00:16:11,880 Speaker 1: was too much for Instagram's initial servers to handle, and 281 00:16:11,920 --> 00:16:14,160 Speaker 1: it sent Systram and Krieger onto a little bit of 282 00:16:14,160 --> 00:16:16,920 Speaker 1: a panic. They tried to figure out who they could 283 00:16:16,920 --> 00:16:21,240 Speaker 1: contact to get some advice, and they settled on Adam D'Angelo, 284 00:16:21,320 --> 00:16:24,040 Speaker 1: whom System had met at a Sigma New party at 285 00:16:24,080 --> 00:16:28,960 Speaker 1: Stanford years earlier, D'Angelo had served as Facebook's chief technology 286 00:16:28,960 --> 00:16:32,600 Speaker 1: officer and was a pretty knowledgeable guy. D'Angelo helped out 287 00:16:32,640 --> 00:16:35,200 Speaker 1: his buddy and talked him through the process of moving 288 00:16:35,240 --> 00:16:39,720 Speaker 1: the load over to Amazon's hosting services, where Instagram could 289 00:16:39,800 --> 00:16:44,360 Speaker 1: rent server capacity while building out its own systems. According 290 00:16:44,400 --> 00:16:49,640 Speaker 1: to Systrom, the conversation took about half an hour and 291 00:16:49,680 --> 00:16:52,520 Speaker 1: then things were back up and running. Now, at this point, 292 00:16:52,680 --> 00:16:55,080 Speaker 1: it was still a two man show, and both Systrom 293 00:16:55,120 --> 00:16:57,600 Speaker 1: and Krieger made it a habit to always have a 294 00:16:57,600 --> 00:17:00,800 Speaker 1: computer with WiFi capability handy in case there was a 295 00:17:00,840 --> 00:17:03,800 Speaker 1: need to jump into the app and patch it so 296 00:17:03,840 --> 00:17:07,560 Speaker 1: that you could smooth out a bug or fix other problems, 297 00:17:07,600 --> 00:17:10,199 Speaker 1: which was happening on a fairly regular basis due to 298 00:17:10,240 --> 00:17:13,360 Speaker 1: the enormous popularity of the app, because within just three 299 00:17:13,400 --> 00:17:17,640 Speaker 1: weeks that thousand user base had grown to three hundred thousand, 300 00:17:18,240 --> 00:17:20,439 Speaker 1: and this was just the start of a wild ride. 301 00:17:20,880 --> 00:17:23,159 Speaker 1: I have more to say about Instagram, but before I 302 00:17:23,240 --> 00:17:25,840 Speaker 1: jump into the next section, let's take another quick break 303 00:17:26,119 --> 00:17:36,760 Speaker 1: and thank our sponsor. The same month that Instagram launched, 304 00:17:36,920 --> 00:17:41,240 Speaker 1: Systrom and Krieger hired their first coworker, Josh Redal. He 305 00:17:41,280 --> 00:17:44,240 Speaker 1: would become the community manager and led efforts to form 306 00:17:44,320 --> 00:17:47,960 Speaker 1: partnerships at Instagram. He had previously worked at next Stop, 307 00:17:48,040 --> 00:17:50,800 Speaker 1: the same company that Systram had worked for earlier in 308 00:17:52,200 --> 00:17:56,560 Speaker 1: a month later in November, Shane Sweeney joined as a 309 00:17:56,600 --> 00:18:00,480 Speaker 1: mobile engineer. Sweeney had become interested in program main through 310 00:18:00,520 --> 00:18:04,960 Speaker 1: computer games It's sound familiar, and then later through social platforms. 311 00:18:05,200 --> 00:18:07,399 Speaker 1: He had started working in web development while still in 312 00:18:07,480 --> 00:18:09,800 Speaker 1: high school. He had moved on to doing work with 313 00:18:09,840 --> 00:18:12,760 Speaker 1: a company that was called Digital Path that was making 314 00:18:12,800 --> 00:18:16,359 Speaker 1: wireless mesh networks. It's a pretty cool technology. I'll have 315 00:18:16,359 --> 00:18:18,040 Speaker 1: to do a full episode on that at some point. 316 00:18:18,480 --> 00:18:21,640 Speaker 1: But three months into his stint of working for the company, 317 00:18:22,040 --> 00:18:25,520 Speaker 1: the funding fell out and one hundred people were laid off, 318 00:18:25,800 --> 00:18:29,159 Speaker 1: including Sweeney. He would go on to work on personal 319 00:18:29,200 --> 00:18:32,720 Speaker 1: projects at dog Patch Labs, using that as a workspace, 320 00:18:33,040 --> 00:18:36,359 Speaker 1: and there he met Sistrom and Sistrom invited him to 321 00:18:36,400 --> 00:18:40,800 Speaker 1: work on Bourbon earlier in but Sweeney actually said no 322 00:18:41,280 --> 00:18:43,359 Speaker 1: when he was invited to work on Bourbon. It was 323 00:18:43,480 --> 00:18:47,359 Speaker 1: only after Instagram launched that Sweeney reconsidered and joined the team. 324 00:18:47,640 --> 00:18:49,720 Speaker 1: And in fact I saw an interview with Sweeney where 325 00:18:49,720 --> 00:18:54,240 Speaker 1: he said there's an ongoing joke at Instagram that everyone 326 00:18:54,359 --> 00:18:57,880 Speaker 1: says no to Systrom. Initially he asks them to join 327 00:18:57,920 --> 00:19:01,080 Speaker 1: his project, and they'll say no, and then later on 328 00:19:01,160 --> 00:19:03,359 Speaker 1: they'll change their minds and say yes, and that this 329 00:19:03,440 --> 00:19:07,440 Speaker 1: is just a thematic thing that goes on at Instagram. Well, 330 00:19:07,440 --> 00:19:11,080 Speaker 1: there wouldn't be another higher until two thousand eleven, so 331 00:19:11,119 --> 00:19:15,120 Speaker 1: in those initial weeks, Instagram was a four person operation. Meanwhile, 332 00:19:15,160 --> 00:19:18,200 Speaker 1: the app continued to get thousands of downloads and user 333 00:19:18,240 --> 00:19:21,920 Speaker 1: activity was increasing on a daily basis. In fact, by December, 334 00:19:22,960 --> 00:19:27,520 Speaker 1: Instagram had one million registered users. And remember this was 335 00:19:27,640 --> 00:19:30,760 Speaker 1: before there was any support for platforms like Android or 336 00:19:30,800 --> 00:19:35,760 Speaker 1: Windows Mobile. This was purely on iOS. The flagship phone 337 00:19:35,760 --> 00:19:38,439 Speaker 1: for Instagram was the iPhone four, which had launched in 338 00:19:38,560 --> 00:19:42,359 Speaker 1: June two thousand ten. The iPhone four had two cameras. 339 00:19:42,600 --> 00:19:45,719 Speaker 1: The back facing one was a five megapixel camera and 340 00:19:45,760 --> 00:19:49,359 Speaker 1: the front facing camera was just point three megapixels. And 341 00:19:49,480 --> 00:19:52,040 Speaker 1: a quick explanation for folks who have heard the term 342 00:19:52,080 --> 00:19:54,720 Speaker 1: megapixels but they don't really have a grasp on what 343 00:19:54,880 --> 00:19:59,160 Speaker 1: that's all about. Megapixels are a way to measure image resolution. 344 00:19:59,400 --> 00:20:02,320 Speaker 1: A pixel is a point of light within a digital 345 00:20:02,359 --> 00:20:05,639 Speaker 1: image or a screen. So if you are looking at 346 00:20:05,640 --> 00:20:09,080 Speaker 1: a television screen, every single little bit of that television 347 00:20:09,080 --> 00:20:10,800 Speaker 1: screen is made up of tiny little points of light 348 00:20:10,840 --> 00:20:15,080 Speaker 1: called pixels. So every photo is a collection of pixels. 349 00:20:15,320 --> 00:20:17,520 Speaker 1: If you only have a small number of pixels, your 350 00:20:17,520 --> 00:20:20,240 Speaker 1: image is going to be blocky and ill defined. I've 351 00:20:20,320 --> 00:20:23,639 Speaker 1: used this example before, but imagine that you've got a 352 00:20:23,720 --> 00:20:27,080 Speaker 1: bunch of blocks of different colors, and the blocks measure 353 00:20:27,119 --> 00:20:30,480 Speaker 1: maybe two inches per side, and you're told to make 354 00:20:30,560 --> 00:20:33,879 Speaker 1: the image of a flower, and you're given fifty blocks 355 00:20:33,920 --> 00:20:35,840 Speaker 1: to do it. That flower is going to be a 356 00:20:35,840 --> 00:20:39,800 Speaker 1: little blocking. But let's say you're given two hundred blocks 357 00:20:39,960 --> 00:20:43,760 Speaker 1: and they're each a half inch per side. Well, that 358 00:20:43,800 --> 00:20:45,720 Speaker 1: flower is going to be less blocky. It's gonna look 359 00:20:45,720 --> 00:20:49,159 Speaker 1: more like a flower. The smaller the blocks are, and 360 00:20:49,200 --> 00:20:52,800 Speaker 1: the more blocks you have, the more refined the image 361 00:20:52,800 --> 00:20:59,880 Speaker 1: you can create, So you increase the resolution of your image. Uh, However, 362 00:21:00,720 --> 00:21:03,520 Speaker 1: that's only part of the quality of a photo. It 363 00:21:03,600 --> 00:21:06,639 Speaker 1: is true that more pixels generally means higher resolution image, 364 00:21:06,920 --> 00:21:10,479 Speaker 1: and a megapixel is technically one million, forty eight thousand, 365 00:21:10,560 --> 00:21:13,320 Speaker 1: five D seventy six pixels that we usually just round 366 00:21:13,359 --> 00:21:16,440 Speaker 1: down and say it's a million pixels, But megapixels don't 367 00:21:16,480 --> 00:21:19,440 Speaker 1: always mean better photos. Like if you have a ten 368 00:21:19,480 --> 00:21:22,840 Speaker 1: megapixel camera and your friend has a fifteen megapixel camera, 369 00:21:23,119 --> 00:21:26,239 Speaker 1: it does not necessarily mean the fifteen megapixel images are 370 00:21:26,240 --> 00:21:28,439 Speaker 1: going to be better than yours. Uh, I mean it 371 00:21:28,480 --> 00:21:32,000 Speaker 1: matters a lot of other things matter too. System's then girlfriend, 372 00:21:32,080 --> 00:21:35,600 Speaker 1: Nicole now wife. That's what she was complaining about the 373 00:21:35,640 --> 00:21:38,280 Speaker 1: iPhone four camera. Wasn't that the megapixels were bad. It's 374 00:21:38,359 --> 00:21:42,320 Speaker 1: just that there were other elements that would factor into 375 00:21:42,600 --> 00:21:45,960 Speaker 1: the quality of an image, like color representation, or contrast 376 00:21:46,320 --> 00:21:50,200 Speaker 1: and other factors. And that's partly why photo filters became 377 00:21:50,280 --> 00:21:54,199 Speaker 1: so popular. The filters could compensate for shortcomings in the 378 00:21:54,240 --> 00:21:57,680 Speaker 1: digital camera sensors that were found in smartphones at the time. 379 00:21:58,040 --> 00:22:00,720 Speaker 1: Instagram was not the only out to do this, or 380 00:22:00,720 --> 00:22:03,200 Speaker 1: even the first app to do this. The app hip 381 00:22:03,200 --> 00:22:06,080 Speaker 1: Stomatic had already made a name for itself at this time, 382 00:22:06,400 --> 00:22:10,159 Speaker 1: turning smartphone photos into these little, squared off images that 383 00:22:10,200 --> 00:22:14,080 Speaker 1: look like vintage photographs, and it had several filters that 384 00:22:14,119 --> 00:22:16,600 Speaker 1: would automatically apply to each image to give it sort 385 00:22:16,600 --> 00:22:20,280 Speaker 1: of that vintage feel. But Instagram gave users an easier 386 00:22:20,320 --> 00:22:23,400 Speaker 1: way to archive photos and keep a record of those images. 387 00:22:23,640 --> 00:22:26,400 Speaker 1: And unlike hip Stomatic, which cost a dollar ninety nine 388 00:22:26,440 --> 00:22:30,640 Speaker 1: to purchase, Instagram was free. What's more, Systrom had said 389 00:22:30,680 --> 00:22:34,760 Speaker 1: it would always be free and that monetization strategies would 390 00:22:34,800 --> 00:22:37,720 Speaker 1: not involve users coughing up money to pay for the service. 391 00:22:38,440 --> 00:22:40,320 Speaker 1: I have to do a full episode and hip Stomatic 392 00:22:40,400 --> 00:22:42,960 Speaker 1: at some point, because that's another fascinating story of a 393 00:22:43,000 --> 00:22:45,640 Speaker 1: company that made a huge impact when it launched, only 394 00:22:45,680 --> 00:22:48,400 Speaker 1: to find itself in troubled waters. A couple of years later, 395 00:22:48,960 --> 00:22:52,600 Speaker 1: in January twoleven, Instagram rolled out support for one of 396 00:22:52,640 --> 00:22:58,520 Speaker 1: its enduring features, hashtags. The hashtag the pounds symbol had 397 00:22:58,560 --> 00:23:02,800 Speaker 1: already gained popularity over at Twitter, where users had sort 398 00:23:02,840 --> 00:23:05,879 Speaker 1: of invented and adopted the practice in an effort to 399 00:23:05,880 --> 00:23:09,440 Speaker 1: make it easier to follow tweets about specific subjects. You 400 00:23:09,440 --> 00:23:12,880 Speaker 1: would use Twitter Search and you would search hashtag the term, 401 00:23:13,040 --> 00:23:15,200 Speaker 1: and that way you would just get the tweets that 402 00:23:15,240 --> 00:23:19,280 Speaker 1: were specifically including that hashtag, because otherwise, if you just 403 00:23:19,280 --> 00:23:21,600 Speaker 1: search for a regular word, you get a whole bunch 404 00:23:21,600 --> 00:23:23,399 Speaker 1: of tweets that were not relevant to whatever it was 405 00:23:23,400 --> 00:23:24,680 Speaker 1: you were looking for. So it was a way to 406 00:23:24,800 --> 00:23:29,440 Speaker 1: narrow things down. Um, So that was how it worked 407 00:23:29,440 --> 00:23:32,240 Speaker 1: on Twitter, but in Instagram it would do something similar, 408 00:23:32,240 --> 00:23:35,080 Speaker 1: but this time you allow for another possible application, a 409 00:23:35,119 --> 00:23:38,040 Speaker 1: group photo album. The way it works on Instagram is 410 00:23:38,080 --> 00:23:40,240 Speaker 1: that you would caption the photo and you would include 411 00:23:40,240 --> 00:23:44,080 Speaker 1: one or more hashtags to help describe the photos context, 412 00:23:44,560 --> 00:23:47,240 Speaker 1: what the photo is about, what's going on in the photo, 413 00:23:47,720 --> 00:23:51,760 Speaker 1: something that's more specific than just hashtag photo. Perhaps you 414 00:23:51,800 --> 00:23:54,760 Speaker 1: attended an event and you wanted your image included with 415 00:23:54,800 --> 00:23:57,399 Speaker 1: others from that same event, So you might do something 416 00:23:57,440 --> 00:24:01,199 Speaker 1: like hashtag Jonathan's birthday party, and then other people are 417 00:24:01,280 --> 00:24:04,120 Speaker 1: using that same hashtag, and it becomes easy to see 418 00:24:04,160 --> 00:24:06,679 Speaker 1: all the photos taken by all the people at that 419 00:24:06,760 --> 00:24:10,160 Speaker 1: event by doing a search on hashtag Jonathan's birthday party. 420 00:24:10,320 --> 00:24:12,560 Speaker 1: You just use that hashtag and boom, your image is 421 00:24:12,680 --> 00:24:16,040 Speaker 1: going to join all the others tagged with that same label. Now, granted, 422 00:24:16,280 --> 00:24:19,840 Speaker 1: the more general the label, the more likely your image 423 00:24:19,840 --> 00:24:21,280 Speaker 1: is going to be grouped with a bunch of ones 424 00:24:21,359 --> 00:24:25,960 Speaker 1: that don't really have the same, uh, same perspective, or 425 00:24:26,240 --> 00:24:28,560 Speaker 1: the same relevance as yours. So you want to get 426 00:24:28,600 --> 00:24:32,400 Speaker 1: as specific as you can without getting ridiculously long hashtags. 427 00:24:32,400 --> 00:24:35,000 Speaker 1: It's a bit of a balancing act to do this. 428 00:24:35,119 --> 00:24:37,440 Speaker 1: You have to make sure you're using those right hashtags. 429 00:24:37,440 --> 00:24:40,080 Speaker 1: So if you use one variation and everyone else uses 430 00:24:40,119 --> 00:24:43,080 Speaker 1: a different one, you're the one who's left out. So 431 00:24:43,160 --> 00:24:46,760 Speaker 1: let's say again, you said hashtag Jonathan's birthday and everyone 432 00:24:46,800 --> 00:24:50,960 Speaker 1: else is doing hashtag John Strickland's birthday, then yours is 433 00:24:51,000 --> 00:24:53,680 Speaker 1: not going to show up with everybody else's. And Instagram 434 00:24:53,720 --> 00:24:56,800 Speaker 1: elites will tell you that including lots of hashtags to 435 00:24:56,880 --> 00:25:01,880 Speaker 1: cover several different contexts is key to discover ability. I've 436 00:25:01,920 --> 00:25:06,120 Speaker 1: seen guides about best uses, best practices on on Instagram 437 00:25:06,160 --> 00:25:08,560 Speaker 1: suggesting that you should use no fewer than a dozen 438 00:25:08,680 --> 00:25:11,960 Speaker 1: hashtags when you're capturing your photos if you want people 439 00:25:12,000 --> 00:25:15,440 Speaker 1: to see them. I questioned that because I think after 440 00:25:15,520 --> 00:25:18,000 Speaker 1: a while, if you see that many hashtags, you start 441 00:25:18,000 --> 00:25:20,959 Speaker 1: to roll your eyes. But then again, I don't have 442 00:25:21,000 --> 00:25:23,399 Speaker 1: that many followers on Instagram, so who am I to 443 00:25:23,480 --> 00:25:27,760 Speaker 1: say whatever? Like I, I can't give strategic advice. But 444 00:25:27,840 --> 00:25:30,639 Speaker 1: it has led to abuse of the system as people 445 00:25:30,680 --> 00:25:33,920 Speaker 1: began to use hashtags that were completely unrelated to the 446 00:25:34,280 --> 00:25:36,960 Speaker 1: photos that they were posting, just in an effort to 447 00:25:37,000 --> 00:25:39,879 Speaker 1: get those photos seen. It would be disingenuous for me 448 00:25:39,920 --> 00:25:42,280 Speaker 1: to take a photo of, say the building I work 449 00:25:42,280 --> 00:25:45,640 Speaker 1: in and tag it with hashtag Beyonce just to see 450 00:25:45,640 --> 00:25:48,399 Speaker 1: if I could get more impressions with my image. And 451 00:25:48,440 --> 00:25:51,080 Speaker 1: as Instagram has grown in popularity, having a lot of 452 00:25:51,119 --> 00:25:54,800 Speaker 1: followers and engagement in the app has become much more important. 453 00:25:55,400 --> 00:25:58,159 Speaker 1: It can be a way to get hired as a 454 00:25:58,200 --> 00:26:01,879 Speaker 1: social manager, for example. So as a result, Instagram has 455 00:26:01,880 --> 00:26:05,760 Speaker 1: occasionally instituted new policies to help cut down on hashtag abuse, 456 00:26:06,119 --> 00:26:09,520 Speaker 1: including implementing a policy called shadow banning, which really only 457 00:26:09,600 --> 00:26:14,200 Speaker 1: became known years later. And a shadow ban still allows 458 00:26:14,200 --> 00:26:18,320 Speaker 1: you to post to Instagram. You can still contribute, but 459 00:26:18,440 --> 00:26:22,080 Speaker 1: it will not share your images with the Instagram community 460 00:26:22,160 --> 00:26:25,840 Speaker 1: through those hashtags. So let's say that I have been 461 00:26:26,160 --> 00:26:31,320 Speaker 1: abusing hashtags on Instagram for a while. The algorithms have said, 462 00:26:31,760 --> 00:26:34,640 Speaker 1: this guy is just using random hashtags that have nothing 463 00:26:34,640 --> 00:26:36,680 Speaker 1: to do with his photos. We're gonna shadow ban him. 464 00:26:36,720 --> 00:26:39,200 Speaker 1: And then I go to see a big event. Let's 465 00:26:39,240 --> 00:26:44,280 Speaker 1: say I go to, uh, the next Star Wars premiere, 466 00:26:44,600 --> 00:26:46,760 Speaker 1: and I'm taking a lot of photos from the red carpet, 467 00:26:46,840 --> 00:26:50,440 Speaker 1: and I want to have Star Wars Premiere hashtag on 468 00:26:50,520 --> 00:26:53,119 Speaker 1: my Instagram photos so they could be added with everyone else's. 469 00:26:53,960 --> 00:26:56,320 Speaker 1: I could still post all those photos to Instagram, and 470 00:26:56,359 --> 00:26:58,359 Speaker 1: if you went to my account, you would actually see 471 00:26:58,480 --> 00:27:01,360 Speaker 1: those photos, but they would not be shared with all 472 00:27:01,400 --> 00:27:04,920 Speaker 1: the other Star Wars premiere photos because the shadow band 473 00:27:04,960 --> 00:27:09,240 Speaker 1: would keep my hashtag from working. And it was all 474 00:27:09,320 --> 00:27:15,119 Speaker 1: meant to negate this tendency for people to use hashtags 475 00:27:15,119 --> 00:27:17,240 Speaker 1: that had nothing to do with the images they were posting, 476 00:27:17,359 --> 00:27:20,320 Speaker 1: just in an effort to boost the number of views 477 00:27:20,320 --> 00:27:23,720 Speaker 1: they were getting. In early two thousand eleven, Instagram held 478 00:27:23,720 --> 00:27:27,320 Speaker 1: another round of investment funding. The apps popularity was skyrocketing, 479 00:27:27,320 --> 00:27:29,800 Speaker 1: with more than a million and a half users in 480 00:27:29,840 --> 00:27:34,320 Speaker 1: February and more than two fifty thousand photos shared each day, 481 00:27:34,400 --> 00:27:38,200 Speaker 1: and investors flocked to the new company. Adam to Angelo 482 00:27:38,480 --> 00:27:41,760 Speaker 1: was one of those investors, as was Jack Dorsey. Chris Soaka, 483 00:27:41,800 --> 00:27:45,320 Speaker 1: who was an early employee over at Google, also invested 484 00:27:45,320 --> 00:27:48,800 Speaker 1: in the company, and in all, angel investors poured seven 485 00:27:49,000 --> 00:27:53,120 Speaker 1: million dollars into Instagram, which still had fewer than five 486 00:27:53,160 --> 00:27:56,800 Speaker 1: people working there, so more than a million dollars per employee, 487 00:27:57,000 --> 00:28:00,520 Speaker 1: which is pretty darn good. In two thousand eleven, Instagram 488 00:28:00,560 --> 00:28:03,320 Speaker 1: would continue on its trajectory of growth. The company would 489 00:28:03,359 --> 00:28:07,320 Speaker 1: hire three more new employees. Jessica Zolman joined in August 490 00:28:07,720 --> 00:28:11,359 Speaker 1: eleven as a community evangelist. She acted as part customer 491 00:28:11,440 --> 00:28:14,919 Speaker 1: service representative and part communicator from the company to the 492 00:28:15,000 --> 00:28:18,040 Speaker 1: users to explain new features and changes to the app. 493 00:28:18,480 --> 00:28:22,119 Speaker 1: In October two thousand eleven, Amy Cole joined Instagram to 494 00:28:22,160 --> 00:28:25,679 Speaker 1: handle business operations. Cole had previously worked for Sephora in 495 00:28:25,760 --> 00:28:30,520 Speaker 1: business development, and in December two thousand eleven, Gregor Hachmouth 496 00:28:31,000 --> 00:28:34,160 Speaker 1: and I'm sure I'm mispronouncing his name joined the company 497 00:28:34,240 --> 00:28:36,679 Speaker 1: as an engineer. And he had previously co founded a 498 00:28:36,720 --> 00:28:41,880 Speaker 1: company called Mody, which presented users with slide shows of art, products, typography, 499 00:28:41,880 --> 00:28:44,040 Speaker 1: and more, and you would rate the images with various 500 00:28:44,120 --> 00:28:47,160 Speaker 1: finger swipe gestures. By the end of two thousand eleven, 501 00:28:47,400 --> 00:28:52,720 Speaker 1: Instagram boasted ten million active monthly users. Version two point 502 00:28:52,760 --> 00:28:55,240 Speaker 1: oh of the app had gone live on iOS and 503 00:28:55,320 --> 00:29:00,320 Speaker 1: incorporated new features, including new filters, some new post processings 504 00:29:00,320 --> 00:29:03,560 Speaker 1: like borders and tilt control, and more. But the real 505 00:29:03,720 --> 00:29:08,000 Speaker 1: crazy stuff would happen the following year. In two thousand twelve, 506 00:29:08,480 --> 00:29:11,400 Speaker 1: Instagram would grow again and it would hold another round 507 00:29:11,400 --> 00:29:13,640 Speaker 1: of funding. System would talk about how he had no 508 00:29:13,680 --> 00:29:16,000 Speaker 1: intention to sell the company and then he sold the 509 00:29:16,040 --> 00:29:20,520 Speaker 1: company to Facebook just days later. But I'll cover that 510 00:29:20,600 --> 00:29:22,880 Speaker 1: in our next episode. For now, we're gonna wrap up. 511 00:29:23,280 --> 00:29:26,560 Speaker 1: Thank you Nellie for the request, and I hope you 512 00:29:26,680 --> 00:29:30,320 Speaker 1: enjoyed this first episode about the earliest days at Instagram, 513 00:29:30,360 --> 00:29:33,000 Speaker 1: how it was born out of a totally different app. 514 00:29:33,760 --> 00:29:37,400 Speaker 1: And it's interesting because when we cover in the second part, 515 00:29:37,680 --> 00:29:42,520 Speaker 1: we'll talk about how Instagram's more recent trajectory has sort 516 00:29:42,520 --> 00:29:45,440 Speaker 1: of put it back in line with what Bourbon was 517 00:29:45,520 --> 00:29:49,160 Speaker 1: doing earlier in some ways, not exactly the same way, 518 00:29:49,200 --> 00:29:52,400 Speaker 1: but in ways that make me a little worried is 519 00:29:52,440 --> 00:29:56,400 Speaker 1: probably the wrong word, but concerned. Let's say, if you 520 00:29:56,440 --> 00:29:59,320 Speaker 1: guys have suggestions for future episodes of tech Stuff, hit 521 00:29:59,360 --> 00:30:01,920 Speaker 1: me up since me and email. The address for the 522 00:30:01,920 --> 00:30:04,960 Speaker 1: show is tech Stuff at how stuff Works dot com, 523 00:30:05,040 --> 00:30:08,000 Speaker 1: or you can draw me a line on Facebook or Twitter. 524 00:30:08,120 --> 00:30:11,000 Speaker 1: The handle there is tech stuff hs W and hey, 525 00:30:11,040 --> 00:30:14,440 Speaker 1: you know what, we have an Instagram account. You should 526 00:30:14,480 --> 00:30:18,400 Speaker 1: follow that and I'll talk to you again really soon 527 00:30:24,040 --> 00:30:26,480 Speaker 1: for more on this and thousands of other topics. Is 528 00:30:26,480 --> 00:30:37,640 Speaker 1: it how stuff Works dot Com