>> Narrator: Live from Boston, Massachusetts this is the Cube, covering Spark Summit East 2017 brought to you by Databricks. Now, here are your hosts, Dave Vellante and George Gilbert. >> Welcome back to Boston, everybody, where it's a blizzard outside and a blizzard of content coming to you from Spark Summit East, #SparkSummit. This is the Cube, the worldwide leader in live tech coverage. Joel Cumming is here. He's the head of data at Kik. Kicking butt at Kik. Welcome to the Cube. >> Thank you, thanks for having me. >> So tell us about Kik, this cool mobile chat app. Checked it out a little bit. >> Yeah, so Kik has been around since about 2010. We're, as you mentioned, a mobile chat app, start-up based in Waterloo, Ontario. Kik really took off, really 2010 when it got 2 million users in the first 22 days of its existence. So was insanely popular, specifically with U.S. youth, and the reason for that really is Kik started off in a time where chatting through text cost money. Text messages cost money back in 2010, and really not every kid has a phone like they do today. So if you had an iPod or an iPad all you needed to do was sign up, and you had a user name and now you could text with your friends, so kids could do that just like their parents could with Kik, and that's really where we got our entrenchment with U.S. youth. >> And you're the head of data. So talk a little bit about your background. What does that mean to be a head of data? >> Yes, so prior to working at Kik I worked at Blackberry, and I like to say I worked at Blackberry probably around the time just before you bought your first Blackberry and I left just after you bought your first iPhone. So kind of in that range, but was there for nine years. >> Vellante: Can you do that with real estate? >> Yeah, I'd love to be able to do that with real estate. But it was a great time at Blackberry. It was very exciting to be part of that growth. When I was there, we grew from three million to 80 million customers, from three thousand employees to 17 thousand employees, and of course, things went sideways for Blackberry, but conveniently at the end Blackberry was working in BBM, and leading a team of data scientists and data engineers there. And BBM if you're not familiar with it is a chat app as well, and across town is where Kik is headquartered. The appeal to me of moving to Kik was a company that was very small and fast moving, but they actually weren't leveraging data at all. So when I got there, they had a pile of logs sitting in S3, waiting for someone to take advantage of them. They were good at measuring events, and looking at those events and how they tracked over time, but not really combining them to understand or personalize any experience for their end customers. >> So they knew enough to keep the data. >> They knew enough to keep the data. >> They just weren't sure what to do with it. Okay so, you come in, and where did you start? >> So the first day that I started that was the first day I used any AWS product, so I had worked on the big data tools at the old place, with Hadoop and Pig and Hive and Oracle and those kinds of things, but had never used an AWS product until I got there and it was very much sink or swim and on my first day our CEO in the meeting said, "Okay, you're data guy here now. "I want you to tell me in a week why people leave Kik." And I'm like, man we don't even have a database yet. The first thing I did was I fired up a Redshift cluster. First time I had done that, looked at the tools that were available in AWS to transform the data using EMR and Pig and those kinds of things, and was lucky enough, fortunate enough that they could figure that out in a week and I didn't give him the full answer of why people left, but I was able to give him some ideas of places we could go based on some preliminary exploration. So I went from leading this team of about 40 people to being a team of one and writing all the code myself. Super exciting, not the experience that everybody wants, but for me it was a lot of fun. Over the last three years have built up the team. Now we have three data engineers and three data scientists and indeed it's a lot more important to people every day at Kik. >> What sort of impact has your team had on the product itself and the customer experience? >> So the beginning it was really just trying to understand the behaviors of people across Kik, and that took a while to really wrap our heads around, and any good data analysis combines behaviors that you have to ask people their opinion on and also behaviors that we see them do. So I had an old boss that used to work at Rogers, which is a telecomm provider in Canada, and he said if you ask people the things that they watch they tell you documentaries and the news and very important stuff, but if you see what they actually watch it's reality TV and trashy shows, and so the truth is really somewhere in the middle. There's an aspirational element. So for us really understanding the data we already had, instrumenting new events, and then in the last year and a half, building out an A/B testing framework is something that's been instrumental in how we leverage data at Kik. So we were making decisions by gut feel in the very beginning, then we moved into this era where we were doing A/B testing and very focused on statistical significance, and rigor around all of our experiments, but then stepping back and realizing maybe the bets that we have aren't big enough. So we need to maybe bet a little bit more on some bigger features that have the opportunity to move the needle. So we've been doing that recently with a few features that we've released, but data is super important now, both to stimulate creativity of our product managers as well as to measure the success of those features. >> And how do you map to the product managers who are defining the new features? Are you a central group? Are you sort of point guards within the different product groups? How does that, your evidence-based decisions or recommendations but they make ultimately, presumably, the decisions. What's the dynamic? >> So it's a great question. In my experience, it's very difficult to build a structure that's perfect. So in the purely centralized model you've got this problem of people are coming to you to ask for something, and they may get turned away because you're too busy, and then in the decentralized model you tend to have lots of duplication and overlap and maybe not sharing all the things that you need to share. So we tried to build a hybrid of both. And so we had our data engineers centralized and we tried doing what we called tours of duty, so our data scientists would be embedded with various teams within the company so it could be, it could be the core messenger team. It could be our bot platform team. It could be our anti-spam team. And they would sit with them and it's very easy for product managers and developers to ask them questions and for them to give out answers, and then we would rotate those folks through a different tour of duty after a few months and they would sit with another team. So we did that for a while, and it worked pretty well, but one of the major things we found was a problem was there's no good checkpoint to confirm that what they're doing is right. So in software development you're releasing a version of software. There's QA, there's code review and there's structure in place to ensure that yes, this number I'm providing is right. It's difficult when you've got a data scientist who's out with a team for him to come back to the team and get that peer review. So now we're kind of reevaluating that. We use an agile approach, but we have primes for each of these groups but now we all sit together. >> So the accountability is after the data scientist made a recommendation that the product manager agrees with, how do you ensure that it measured up to the expectation? Like sort of after the fact. >> Yeah, so in those cases our A/B tests are it's nice to have that unbiased data resource on the team that's embedded with them that can step back and say yes, this idea worked, or it didn't work. So that's the approach that we're taking. It's not a dedicated resource, but a prime resource for each of these teams that's a subject matter expert and then is evaluating the results in an unbiased kind of way. >> So you've got this relatively small, even though it's quadruple the size when you started, data team and then application development team as sort of colleagues or how do you interact with them? >> Yeah, we're actually part of the engineering organization at Kik, part of R and D, and in different times in my life I've been part of different organizations whether it's marketing or whether it's I.T. or whether it's R and D, and R and D really fits nicely. And the reason why I think it's the best is because if there's data that you need to understand users more there's much more direct control over getting that element instrumented within a product that you have when you're part of R and D. If you're in marketing, you're like hey, I'd love to know how many times people tap on that red button, but no event fires when that red button is tapped. Good luck trying to get the software developers to put that in. But when there's an inherent component of R and D that's dependent on data, and data has that direct path to those developers, getting that kind of thing done is much easier. >> So from a tooling standpoint, thinking about data scientists and data engineers, a lot of the tools that we've seen in this so-called big data world have been quite spoke. Different interfaces, different experience. How are you addressing that? Does Spark help with that? Maybe talk about that a bit more. >> Yeah, so I was fortunate enough to do a session today that sort of talked about data V1 at Kik versus data V2 at Kik, and we drew this kind of a line in the sand. So when I started it was just me. I'm trying to answer these questions very quickly on these three or five day timelines that we get from our CEO. >> Vallente: You've been here a week, come on! >> Yeah exactly, so you sacrifice data engineering and architecture when you're living like that. So you can answer questions very quickly. It worked well for a while, but then all of a sudden we come up and we have 300 data pipelines. They're a mess. They're hard to manage and control. We've got code sometimes in Sequel or sometimes in Python scripts, or sometimes on people's laptops. We have no real plan for Getup integration. And then you know real scalability out of Redshift. We were doing a lot of our workloads in Redshift to do transformations just because, get the data into Redshift, write some Sequel and then have your results. We're running into contention problems with that. So what we decided to do is sort of stop, step back and say, okay so how are we going to house all of this atomic data that we have in a way that's efficient. So we started with Redshift, our database was 10 terabytes. Now it's 100, except for we get five terabytes of data per day that's new coming in, so putting that all in Redshift, it doesn't make sense. It's not all that useful. So if we cull that data under supervision, we don't want to get rid of the atomic data, how do we control that data under supervision. So we decided to go the data lake route, even though we hate the term data lake, but basically a folder structure within S3 that's stored in a query optimized format like Parquet, and now we can access that data very quickly at an atomic level, at a cleansed level and also an at aggregate level. So for us, this data V2 was the evolution of stopping doing a lot of things the way we used to do, which was lots of data pipelines, kind of code that was all over the place, and then aggregations in Redshift, and starting to use Spark, specifically Databricks. Databricks we think of in two ways. One is kind of managed Spark, so that we don't have to do all the configuration that we used to have to do with EMR, and then the second is notebooks that we can align with all the work that we're doing and have revision control and Getup integration as well. >> A question to clarify, when you've put the data lake, which is the file system and then the data in Parquet format, or Parquet files, so this is where you want to have some sort of interactive experience for business intelligence. Do you need some sort of MPP server on top of that to provide interactive performance, or, because I know a lot customers are struggling at that point where they got all the data there, and it's kind of organized, but then if they really want to munge through that huge volume they find it slows to lower than a crawl. >> Yeah, it's a great point. And we're at the stage right now where our data lake at the top layer of our data lake where we aggregate and normalize, we also push that data into Redshift. So Redshift what we're trying to do with that is make it a read-only environment, so that our analysts and developers, so they know they have consistent read performance on Redshift, where before when it's a mix of batch jobs as well as read workload, they didn't have that guarantee. So you're right, and we think what will probably happen over the next year or so is the advancements in Spark will make it much more capable as a data warehousing product, and then you'd have to start a question do I need both Redshift and Spark for that kind of thing? But today I think some of the cost-based optimizations that are coming, at least the promise of them coming I would hope that those would help Spark becoming more of a data warehouse, but we'll have to see. >> So carry that thread a little further through. I mean in terms of things that you'd like to see in the Spark roadmap, things that could be improved. What's your feedback to Databricks? >> We're fortunate, we work with them pretty closely. We've been a customer for about half a year, and they've been outstanding working with us. So structured streaming is a great example of something we worked pretty closely with on. We're really excited about. We don't have, you know we have certain pockets within our company that require very real-time data, so obviously your operational components. Are your servers up or down, as well as our anti-spam team. They require very low latency access to data. We haven't typically, if we batch every hour that's fine in most cases, but structured streaming when our data streams are coming in now through Kinesis Firehose, and we can process those without have to worry about checking to see if it's time we should start this or is all the data there so we can run this batch. Structured streaming solves a lot of those, it simplifies a lot of that workload for us. So that's something we've been working with them on. The other things that we're really interested in. We've got a bit of list, but the other major ones are how do you start to leverage this data to use it for personalization back in the app? So today we think of data in two ways at Kik. It's data as KPIs, so it's like the things you need to run your business, maybe it's A/B testing results, maybe it's how many active users you had yesterday, that kind of thing. And then the second is data as a product, and how do you provide personalization at an individual level based on your data sciences models back out to the app. So we do that, I should point out at Kik we don't see anybody's messages. We don't read your messages. We don't have access to those. But we have the metadata around the transactions that you have, like most companies do. So that helps us improve our products and services under our privacy policy to say okay, who's building good relationships and who's leaving the platform and why are they doing it. But we can also service components that are useful for personalization, so if you've chatted with three different bots on our platform that's important for us to know if we want to recommend another bot to you. Or you know the classic people people you may know recommendations. We don't do that right now, but behind the scenes we have the kind of information that we could help personalize that experience for you. So those two things are very different. In a lot of companies there's an R and D element, like at Blackberry, the app world recommendation engine was something that there was a team that ran in production but our team was helping those guys tweak and tune their models. So it's the same kind of thing at Kik where we can build, our data scientist are building models for personalization, and then we need to service them back up to the rest of the company. And the process right now of taking the results of our models and then putting them into a real time serving system isn't that clean, and so we do batches every day on things that don't need to be near real-time, so things like predicted gender. If we know your first name, we've downloaded the list of baby names from the U.S. Social Security website and we can say the frequency of the name Pat 80 percent of the time it's a male, and 20 percent it's a female, but Joel is 99 percent of the time it's male and one percent of the time it's a female, so based on your tolerance for whatever you want to use this personalization for we can give you our degrees of confidence on that. That's one example of what we surface rate now in our API back to our own first party components of our app. But in the future with more real-time data coming in from Spark streaming with more real-time model scoring, and then the ability to push that over into some sort of capability that can be surfaced up through an API, it gives our data team the capability of being much more flexible and fast at surfacing things that can provide personalization to the end user, as opposed to what we have now which is all this batch processing and then loading once a day and then knowing that we can't react on the fly. >> So if I were to try and turn that into a sort of a roadmap, a Spark roadmap, it sounds like the process of taking the analysis and doing perhaps even online training to update the models, or just rescoring if you're doing a little slightly less fresh, but then serving it up from a high speed serving layer, that's when you can take data that's coming in from the game and send it back to improve the game in real time. >> Exactly. Yep. >> That's what you're looking for. >> Yeah. >> You and a lot of other people. >> Yeah I think so. >> So how's the event been for you? >> It's been great. There's some really smart people here. It's humbling when you go to some of these sessions and you know, we're fortunate where we try and not have to think about a lot of the details that people are explaining here, but it's really good to understand them and know that there are some smart people that are fixing these problems. As like all events, been some really good sessions, but the networking is amazing, so meeting lots of great people here, and hearing their stories too. >> And you're hoping to go to the hockey game tonight. >> Yeah, I'd love to go to the hockey game. See if we can get through the snow. >> Who are the Bruins playing tonight. >> San Jose. >> Oh, good. >> It could be a good game. >> Yeah, the rivalry. You guys into the hockey game? Alright, good. Alright, Joel, listen, thanks very much for coming on the Cube. Great segment. I really appreciate your insights and sharing. >> Okay, thanks for having me. >> You're welcome. Alright, keep it right there, everybody. George and I will be back right after this short break. This is the Cube. We're live from Spark Summit in Boston.

(upbeat dramatic music) >> Hello, everyone, welcome to the Cube Conversation, here in Palo Alto Studios, for The Cube. I'm John Furrier, the cohost of The Cube, co-founder of Silicon Angle Media. We are here for Thought Leader Thursday, with Mitzi Chang. She's a securities attorney and partner at Goodwin. Formerly Goodwin Proctor, Goodwin Proctor's the name. Again, great to have you on. Thanks for coming in and talking about some of the securities around Blockchain ICO's. You guys doing a lot of work, thanks for coming in. >> Thanks for having me. >> So, obviously, Blockchain is the hottest thing we're seeing. AI, obviously, is hot as well, IOT, all of this about a new, decentralized internet. And it's the wild west. And we know because we're looking at doing our Blockchain and tokens for The Cube and all that good stuff. So we're totally love the new environment. Everyone, all the light tier one entrepreneurs are licking their chops and going, ah, man, good action. And a lot of the thought leaders are saying this is a fundamental shift. So it's cool, we get that. But now, okay, is the technology ahead of the law? And, just today, the news is breaking that the SEC is now putting a clampdown on a new thing, celebrity endorsements, into ICO's initial coin offering. So, yeah, you're a securities attorney. You have to sit back there and, like, wire these deals together. >> Right. >> What's going on, I mean, is the law behind the tech? How are you guys managing it, what's the flow look like for you? >> Yeah, I mean, I think that the law is almost always behind the technology, right. That's just how it works. I mean, from our perspective, you know, we represent tons of companies on normal securities law, or securities issuances. And this can be similar, depending on how the token is structured. So, you know, the SEC said in its July guidance that tokens can be securities, depending on the facts. A part of what we do, as lawyers, is review the facts of the token, right. What does the token do, how do you treat the token, how are you issuing the token, how are you marketing the token? Are there securities-like features of the token? So, for example. Does it have profit sharing features? Does it have voting features? Those are pretty obviously more security-like features. But, also, you know, in the token ecosystem, are you treating it like you would equity? So, for example, you know, are you putting vesting conditions on there? Are you marketing it to VC's who may never use your network? Those are some factors that make it look like more security. Versus a utility. >> You guys also, I mean, I've been in Silicon Valley now 18 years, and been an entrepreneur for longer, and entrepreneurs are always three feet in a cloud of dust, breaking things in the bowl in the China shop, as they say, and have to get the lawyers to kind of clean things up or set things straight. Securities is a known practice, but now there's some kind of bumps in the road but still people are moving forward. So I got to ask you, what's the test? I mean, we hear things like the Howey Test. >> Mm hmm. >> What are some of the things that entrepreneurs should know around where to pay attention? Kind of where to put their head down and drive because there are known practices, on the security site you mentioned, a few of them, but where's the test? What's the one thing, is it the Howey Test? What is this Howey Test concept? And what other things should entrepreneurs know about? >> Right, so I think, you know, the Howey Test is a test that was in CaseLab that basically explains what is an investment contract. And an investment contract is what is considered a security. So, basically, the payment of money, you know, based on the efforts of others, where you kind of have the reasonable expectation of obtaining profits, right, from those efforts of others, versus yourself. So that's the general gist of it. So I think, from a securities law perspective, that's really important. Because there has been so much focus from the SEC. But there's also other regulatory agencies who are focused on this. Some of those are, you know, money transmitter laws. You know, there's potential commodities law issues. So there's definitely other regulatory regimes that could implicate the token. Or the token could be implicated in that regime. But I think the securities law one is one that I focus on. >> Yeah. >> And it's important to look at. >> Alright, so the first test is, okay, obviously, new internet infrastructure, different conversation, but the real law test is, is this token going to be an investment making money. >> Right. >> Or is it going to be a utility. One that provides values to the participants. Did I get that right? >> Yes, I would say, generally speaking, right. Is the token, you know, is it a use case? Or is it an investment? Am I expecting profits from that token? Or am I using it like an access fee or a membership? Or to obtain services. >> An arcade game, as Grant Fonda would say. >> Exactly. An arcade game is probably your best example. >> Yeah. Okay, so then the next test is I've heard of some things I'd like to get you to explain. What anti-money laundering or AML is. And KYC, Know Your Customer. And, obviously, Bitcoin has been kind of, you know, we've heard Silk Road stories, underbelly, a lot of bad things are happening, but anonymous is good. But here, financially, Know Your Customer is a specific thing that means something and then AML, anti-money laundering, how does that factor into this whole thing? >> Yeah, so I think for, you know, when you open a bank account, for example, right, your bank wants to know who you are. They'll obtain certain information from you. Whether it's your drivers license or passport. Where you obtained your funds. I mean, that's part of the Know Your Customer, anti-money laundering activity, right. >> And identity behind the, before you sign the thing. >> Right. So part of it is because cryptocurrency can be very anonymous, right. There are anonymous wallets that you're sending cryptocurrency to and from, you don't know who these people are. So part of it is making sure that you understand who your purchasers are. You don't want to run afoul of, you know, an anti-terrorist type, you know, regulations. The US government has several lists that they have online that you can search for names of folks that you don't need to be doing business with. So there's a lot of structures already in place. And part of that is just understanding who your purchasers are. >> And these are requirements on certain things, and the anti-money laundering exposes just audit trailing and certain things that you got to have as compliance things. >> Correct, correct. And so I think, in America, we don't normally, I would say if you were kind of outside of the US, this is probably a little bit more normal, right. People are used to doing it. I think, in America, maybe we're not as used to it. But these are not kind of new guidelines. This has always existed. >> Alright, so sometimes entrepreneurs are fast and loose with their, ah, screw the anti-money laundering thing. Or they get, I don't understand, that's too much work, I don't understand it. >> Yeah. >> So they blow it off. When do they have to not blow it off? When do you have to worry about, like, all these anti-money laundering things? Cause you have to, obviously, do more work. >> Right. >> Got to make sure you're checking the boxes, complying. That probably has overhead, costs money, or maybe write some new software. So we've been recommending that all of our clients who are in the token space and kind of obtaining, you know, digital currency, go through KYC and AML. Some of the digital currency exchanges, right. So in order, when you're receiving your digital currency and you need an account, >> Mm hmm. >> in order to exchange the digital currency into US dollars, for example, it's essentially like opening a bank account. So they're going to ask for all of the information with respect to how did you receive your digital currency. So part of that is you need to have that in place prior to actually launching your token sale so that you can kind of follow the flow of funds. >> So I was trying to find this image I would put up but I can't find it cause I'm on this computer, but I saw a thing on a conference, might have been Block Con, that you guys were at. I think you guys sponsored that event. Where the cost of doing an ICO can range from, they said, on the cheap end, they use the word cheap, not inexpensive, cheap, probably implying not get a good lawyer, a hundred K up to 750 thousand dollars. So, range of cost between hundred thousand and 750 thousand. From cheap to done right. >> Right. Right. >> Or expensive. Is that right or is that, what's the cost ranges? >> Yeah, I mean, I think there's a lot of players in the ecosystem, right. So there's the lawyers. And typically lawyers bill by the hour, so that's kind of how much time, you know, we're kind of looking at documents and things and helping you structure. There's the tax accountants. So part of that is also, you know, how much time they're spending. But some of it can be very complicated from a tax structuring perspective. Then there's the technical people, right. Unless you have that in house. To actually build your Blockchain network. Kind of help you with all of that, you know, the technical aspects of it. So software engineers, for example. Then there's the ICO consultants. Someone to kind of help you manage, quarterback the process, maybe help you with marketing the tokens to certain different websites, or help you with that. So, all of those together, I mean, yes, it can be very expensive, it kind of depends on how much of that you want to outsource. And how much of that you can do yourself. Obviously, you can't really do all that stuff yourself. >> So it's in the ranges. It could be in the ranges. >> Yeah. I mean, tax alone could kill you if you're looking at all kinds of complicated schemes or licensing agreements. >> Right. >> I mean. >> So all that, you want to make sure you're structuring the entity appropriately before you start it. >> Okay, so where do you get involved? So let's just say that, let's just walk through the day and day operations of, say, Goodwin. Okay, I've got to client. >> Yep. >> And, okay, you come in for the securities component. What does that mean? You just make sure they're incorporated properly? All the laws on the stock and then the tokens treatment? What specific things do you do? >> Sure, so, you know, once we kind of have brought the client in, after our conflicts procedures, and we've agreed to the engagement, part of depends on where they are. If they don't have a company, we'll help you form the company, right. And make sure that all of those startup documents have been appropriately done. Sometimes people have already, they're, you know, an actual company, right. We don't need to form them, they're already in existence. So then we look at pass the formation items and we look at the token issuance. So we'll look at your white paper. The white paper typically describes how the token works in the ecosystem and kind of what the company. >> You get involved in that, just to kind of check if it sounds. >> From a structuring perspective, right. Do we think this is a security? Or do we think it is leaning towards utility? And the SEC obviously has not said, what is a utility and what is a security. >> So that's the gray area? >> Yes. >> So the gray area is watch the language, be careful what you say. >> But also what you do, right. It's not just what you say, it's also what you do. So part of it is talking to the clients about what are you thinking, how are you envisioning this? Where can we help you kind of restructure or decrease your risks? >> And you guys become a safety net and help defend that too, obviously, as attorneys. But the clients still own, >> Correct. I mean, part of it is we give you advice. And the clients can take or not take our advice. But that's what we're here for. >> Do you guys offer a legal opinions behind these? I'm sure you don't. (laughs) >> We don't offer legal opinions. You know, we do do research memos on kind of where we think your token lies. But we don't do legal opinions. >> So have you guys talked to the SEC at Goodwin? I mean, do you guys have conversations? I don't know what goes on behind the curtain of the big law firms but I'm assuming that you guys are up to speed on all the notes and everything, but do you guys actually talk to people at the SEC? Is that how it works? Cause this is a cutting edge area, I'm sure you guys have to be on the cutting edge. >> Yeah, I mean we haven't had any clients, knock on wood, that have had to go through any of the SEC investigations on this. So, you know, we have not had, on behalf of our clients, had to talk to them about it. >> So that's good news, you guys doing good. >> Yeah. >> I know you guys doing over close to 30 plus ICO's, so congratulations. Is there a pattern that you've seen, from a legal standpoint, that you've seen emerging? Obviously, it's pretty clear, out in the market place, certainly the celebrity endorsement, Paris Hilton to the boxer dude and all kinds of stuff was going on where people were endorsing >> Right. >> things, so. Kind of, I don't want to say pump and dump, but that's a word that's been used in the dot com bubble, but people are saying a lot of these things are scams. And the majority of them aren't going to work out. So we've said, editorially here on The Cube and Silicon Angle, that failure doesn't mean scams. We had some failures, but certainly there are some scams. So has that caused people to pull back a little bit? And say, whoa, we're not going to go forward fast enough? Or is nothing stopping this, what's the pattern? >> Yeah, I would say, compared to a year ago, where there was no SEC guidance, right, there was no guidance from other regulator agencies, people were definitely going very quickly. I think now what we're seeing are more sophisticated clients. Clients who really want to make sure that they're following all of the legal requirements to the best that they can, given the grayness in the securities laws and other regimes. And a lot more of a thoughtfulness about, well, let's make sure that this works, right, we're not going to get into trouble. >> Have you seen any co-mingling between some of the traditional VC, venture capital investors or hedge funds, they're emerging, who want to come in and participate on the pure equity side, or the preferred stock or, more common, mostly prefer we see them. But, also, play in the tokens. Is there co-existence between participation? Or is it mostly they line up on the preferred and then let the tokens go here? Is there a pattern there that you see around how those securities are playing out? >> Yeah, I think a lot of people see value in the token ecosystem and they want to participate in that. And a lot of our venture capital clients, or our token clients who have VC investors, they want to participate. So we are definitely seeing people are very excited about it and want to kind of be a part of it. >> What about the presale concept? We're seeing a lot of people jump on the presale bandwagon because it allows them to, you know. It's not an inexpensive process. You guys, obviously, don't work for free. You guys have deals where, obviously, startups can come in. And you guys have a great startup program, I could testify that. You guys do have a good community participation there. But, at the end of the day, this is a legitimate process now. >> Mm Hmm. >> It costs money. You guys have to get paid. And service provides, like the tax attorneys got to get paid. So there's a lot, we see a lot of entrepreneurs doing that's presale. Where they try to offer this kind of discount. How is that working out and has that been going well? >> Yeah, I mean I think, you know, while the SEC has not commented on this, the practitioners and kind of the ecosystem, most people, I think, are considering that presale agreement prior to a network actually being live as a security. And, so, people are going out to accredited investors, sometimes that's VC, sometimes that's high net worth individuals. That's usually done through a SAFT, which is, it stands for Simple Agreement for Future Tokens, or a presale contribution agreement. So part of that is it's like a, you can liken it to a preferred stock financing. >> It's a known process. >> But it's not preferred stock. >> But it's a known vehicle for financing. >> Correct. >> It's not like it's tied to the ICO in a new vehicle. It's just like, okay, we're going to do something down the road, there's risks associated, all that stuff. >> Right, it's an investment contract. I'm giving you a million dollars to invest, to build up the platform. At the end of, when the platform launches, and, hopefully, when the network has utility and your token has utility, then you'll receive tokens. >> And this is good for innovation, because it gets everyone rolling a little bit. Is that, that kind of seems to be the pattern that I'm seeing. It's like, you know. >> It's basically like a seed round, alright. That's probably a really good example, is it's a seed round to get something started. That thing is not your company, it is your network. >> And it also sets the community. I've noticed on the Blockchain, these ICO communities are a very bit part of it. Goodwin's got a great reputation, certainly here in Silicon Valley, and around the world, as a law firm. This is a big part of it. So the presale's also kind of a gesture of credibility for the opportunity and I think, I mean, you know, people I talk to are like, hey, I look at what's going on in the presale, kind of as an indicator of who's involved, judged by the company that you keep kind of thing. So that's interesting. Have you seen that presale dominating more than just going right to the ICO, given the market conditions of all the ICO's? >> Yeah, I mean I think it depends, right. Some of our clients have existing businesses, right. Where this is very complimentary. The Blockchain network is complimentary to their existing business and, so, they may not need to have this big presale, right. Part of the presale could be two weeks before your general crowd sale. You have folks who kind of get in early. To me, that is not necessarily, I mean, it really depends, obviously, fact-specific, but that's a little big different that doing a, quote, presale agreement. Like a year before or six months before your token launch. That's a little bit different. >> Yeah, so also you brought up a good point. Existing businesses versus kind of like people who just need the cash to get going. >> Right. >> We're seeing a lot of companies that either have a successful business, like Kik and then Kik Kin Token was once example, we talk about all the time. The other one is pivots. We're seeing a lot of entrepreneurs take companies that were pivots, AKA, going out of business, where the token timing of a token in decentralized Blockchain actually is great for their business model. And they have to, essentially, go recap or do some securities, you know, resetting. That's your world, right? You got to get involved in those areas. >> Yeah, I mean, I think anything that has to do with kind of changing your capital structure, right, you should have your securities lawyer or your corporate lawyer involved. Because that'll obviously impact your securities law. You know, exemptions that you're taking, you know, typically from a private placement exemption, for most of our private company clients. >> Is there any new trends that are popping out of that kind of pivot or, wow, this is really, you know, I was out there, I got some funding from Y Combinator, or some sort of venture, and we're kind of just barely staying alive. This Blockchain could really accelerate, there's now momentum. Is there any trends that you see, from your work standpoint, where you have, that are happen, that are obvious new things that are coming out of this? Or is it a standard recap to cap table, normal corporate work? >> I think there is a tension, right, between doing a normal stock finance, preferred stock, or common stock financing that, you know, whatever you would typically do. Whether that's a convertible security or a convertible note. And then raising funds through a token sale. And so, from my perspective, it's obviously cleaner to do it the traditional way. Because you're not dealing with unclear SEC rules, right. It's very clear how you do a preferred stock financing. We do that every day. So to the extent that companies are in that position where they can choose, it's certainly cleaner to do it the traditional way. >> If you pull off an ICO, god bless you. It's certainly equity-free, tokens. There's no equity to token, if you're a utility token. >> Right. >> Okay, so I was reading about the Delaware, Delaware was allowing companies to use Blockchain. >> Mm hmm. >> This is right up your alley. So, they're not doing ICO's. So can you clarity the Delaware situation relative to Blockchain, cause they're using a Blockchain from a ledger standpoint, but it's not an ICO haven yet. So talk about the Delaware situation. >> Correct, so the Delaware amendments, which I believe are now approved, as of a couple of months ago, over the summer, essentially allow the cap table ledger to be on the Blockchain. So they're kind of ahead of everything, right. Because, you know. So, for like, for example, a few years ago, no one had uncertificated stock certificates. Everybody wanted the physical stock certificates. And now most companies, that we represent, >> They want digital. >> Exactly, digital, uncertificated stock certificates. But there is a ledger and there is a record of it. You just don't have the fancy paper with the pretty legend on it. So I think technology is moving and the law needs to as well. So part of that is Delaware kind of getting onboard. >> Delaware's got a great opportunity, they can nail the ICO's. Well, Mitzi, thanks for coming, I really appreciate it. Any other observations that you'd like, that you see in the market that you'd like to share? Take a minute to talk about what you're doing at Goodwin, as well. What's going on, what's happening? >> Yeah, I mean I think it's a really exciting time, we're really excited to be a part of it. It's cutting edge work. I think that there's a lot of, I guess, what I would call kind of your more traditional clients that we have, that we take calls from every day. Whether that's investment banks, or VC funds, private equity funds, or just our venture backed companies that are curious as to what is this all about. >> Yeah. >> So I think it's really exciting and I'm glad to be a part of it. I don't think that it is going to stop. I think that certainly there's likely to be more regulation about how you do one of these ICO's, one of these token generation events, you know, within the confines of the law. But I don't see it stopping. >> You don't see it stopping at all? >> No, I mean I think once there's more regulation, there'll be more clarity about how to do it. And how to do it within the confines of the law, which we try to do, obviously, you know, given that there's not a ton of clear guidance. But I think that, I think the ship has sailed. >> Yeah, well this is a great conversation here with Goodwin, formerly Goodwin Proctor, Mitzi Chang, partner, she's a securities attorney. We should call this show Billable Hours. Because we're getting some free legal opinions and conversations, thanks for coming on, appreciate it. >> Thanks for having me. >> Blockchain is hot, entrepreneurs are using it. All the top tier one entrepreneurs are looking at this. Great opportunity, similar with the Web One dato, the TC IP era of the internet, Blockchain. It's fundamental infrastructure for the future of decentralization, so. Great opportunities, causing lots of innovation. Check with your attorneys, obviously Goodwin, and a few others all doing great ICO's. Great potential fundraising, but also great business opportunities. Thanks again, appreciate it. >> Thank you. >> So Cube Conversations here, in Palo Alto, I'm John Furrier, thanks for watching. (electronic music)