WestRock positioned for 'significant earnings growth' as market recovery continues

Net sales were $4.73 billion compared to $5.28 billion in 2023.

WestRock Reports 2Q Fiscal 2024 Results | Ink World

WestRock beat quarterly profit expectations on Thursday, banking on higher prices, easing input costs and a rebound in demand for its paper packaging products, sending its shares up 6.3% in early trading.

WestRock beats quarterly profit estimates on rising prices | Reuters

An update from WestRock LLC (WRK) is now available. WestRock has announced that it will not conduct a conference call on its second-quarter fiscal 2024 financial re...

WestRock Merges with Smurfit, Skips Q2 Earnings Call - TipRanks.com

WestRock Company reported a decrease in net sales but a significant improvement in net income for the fiscal Q2.

WestRock Company (WRK) Reports Mixed Fiscal Q2 with $0.39 EPS - Tokenist

Comparative Analysis of Quarterly Financial Outcomes Against Analyst Projections

WestRock Co (WRK) Q2 Fiscal 2024 Earnings: Misses Revenue Estimates, Reports Modest Profit

Shares of WestRock Co. inched 0.54% higher to $40.97 Thursday, on what proved to be an all-around great trading session for the stock market, with the S&P...

WestRock Co. stock rises Thursday, still underperforms market - MarketWatch

WestRock Co (WRK) is up 1.23% today. WRK has an Overall Score of 56. Find out what this means to you and get the rest of the rankings on WRK! See Full WRK Report WRK stock closed at $40.75 and is up $0.50 during pre-market trading. Pre-market tends to be more volatile due to significantly lower ...

WestRock Co (WRK) Up 1.23% in Premarket Trading

WeStock

westock

THE VOLUCELLA

l remember when crypto was still a foreign concept? Bitcoin was this new and crazy idea that people didn't really understand, and it was hard to get people interested in learning more about it. Luckily we're all on board and investing now. Or... are we? Many Bitcoiners make the assumption that since they are interested in crypto, everyone else must be too. But you'd be surprised at how many people are still uninterested in learning about crypto; in fact, a lot of people don't even know what it is. Bitcoin has been around for over 10 years now, and all things considered, 300 million crypto users worldwide aren't that many. So how do we get more people interested? How do we educate the uneducated about crypto and persuade them to invest? This is what I spoke about with one of my podcast guests from last year, Aubrey Strobel ( ). She's the head of comms for the crypto startup Lolli. see the episode here Her mission? To make crypto mainstream, and to bridge the knowledge gap for the 'moms and pops' of the world. I thought it'd be interesting to explore this in more detail; the idea of reaching the unreached with your business concept. Let's talk about it. Aubrey Strobel, Lolli, and Educating the Masses Aubrey Strobel is the Head of Communications at Lolli, a platform where you earn free Bitcoin while shopping online. She discovered crypto in 2016 and worked for a few different blockchain projects shortly after wrapping up her journalism degree. She is a regular contributor for Coindesk, has had her works featured by NBC, speaks globally on crypto and blockchain, and today, both Lolli and Aubrey are household names within the crypto scene. So how did this all start? Aubrey herself wasn't an avid Bitcoiner from the get-go; she was a journalism student interested in social justice. It was only after a recommendation from her friends that she went down to the local Bitcoin ATM and made a small investment. That was the beginning. “I got into crypto through talking to my friends. But then I saw an opportunity to work at a PR firm to share the story and educate people about Bitcoin. It was a very large problem, and a problem that I could help solve or be a voice for.” Years later, she's the head of marketing for Lolli and an avid proponent of crypto use. When I asked her why Aubrey told me: “Freedom is a value that I hold very near and dear as an American, and I feel like that has been democratized in terms of the internet, but hasn't really been done in finance. There's too much power in certain institutions.” With a passion to educate and a mission to make crypto mainstream, Aubrey is the perfect example of someone who's gone out of her way to reach the unreached. She's not only an excellent marketer but also believes in what she's selling; a rare combination. The False Consensus Effect As I said, it's easy to wrap yourself in a bubble of your own reality. Maybe you are super educated in all things artificial intelligence, and so you assume that every company must be adopting it, too; or perhaps you are an active member of the vegan community, and now believe that everyone is going plant-based. It's an incredibly human phenomenon. Psychologists have even given this a name: the . We tend to overestimate how widely our own beliefs are shared by others. false consensus effect In some cases, this is totally fine. It's not a problem if you assume that all companies use the same CRM software as you (because it's clearly the best and most popular). But when it comes to your entire business concept, assuming the knowledge of your target consumer is a dangerous game. “When you're in the industry, you want to shake people and say, ‘This is the future. I hope you can see that too'," Aubrey lamented in our interview. "But blockchain, crypto, all these terms we're talking about now are still kind of confusing to a lot of people.” When you ignore the true education level of your audience, you miss out on a whole lot of potential business. Imagine if Facebook had only marketed to people who were already using MySpace. Your grandma wouldn't be posting pictures of her cats for the world to see, that's pretty certain. Aubrey recognized the education gap in the crypto industry immediately, and her work since then has been pivotal in moving the space forward. The State of Crypto Education “The reason that Bitcoin is great is that it has that scarcity component to it; there is no way to create more Bitcoin." Aubrey explained when I asked why she's a fan of the currency. This is the message she's trying to reach the broader masses with – but there's a long way to go yet. “Right now, the mainstream group of people is just trying to take care of their kids and pay their bills; they're not looking much beyond that. So to say it's the ‘future of finance’, and to throw around terms like DeFi and blockchain... the normal person just doesn't have time to really sit there and figure that out.” It's true. For those of us who have personally invested in crypto and perhaps seen some impressive returns, it's hard to remember sometimes that the industry is still in its earliest stages. We've been reading about Bitcoin since 2009; for many people, it only hit their radar in late 2017. This is where Aubrey and her team come in. “We want to lower those barriers to entry for people. We want to be a resource for people; we're trying to help them in every way possible.” The Lolli Approach Aubrey was brought onto the Lolli team as a marketer, and she very quickly put her own spin on the company mission. “I would say Lolli is leading the charge because we're not after just Bitcoiners. It's not just a Bitcoin club anymore. It's about getting every single person possible.” So, what are they actually doing? Great question. At its simplest, Lolli is like Honey for Bitcoin. You install the Lolli extension and shop at one of their partner stores like Sephora or Nike. When you make a purchase, you earn a certain percentage of Bitcoin back – just like cashback rewards. “However we can get people owning Bitcoin is a good thing for me. I don't care how that takes place. Lolli was a project that I thought I could really get people – the moms and dads, aunts and uncles – into the door with.” It's a genius move. If you look at companies like Honey – the brands that attach themselves to the daily habits of millions of people – you start to see the power of what Lolli is doing. People are far more inclined to try something out if it's easy and doesn't require a lot of commitment. “I think we need to get people comfortable holding and owning Bitcoin, and being their own bank first. And Lolli allows people to do that in a very easy way. Not everyone sees themselves as an investor; they see themselves as a shopper, though. I think most people are accustomed to shopping online. And so that bridge is easier to get people over.” Lolli isn't asking you to put down $10,000 to buy Bitcoin; they're saying “Hey, try this out. You might like it.” And the only money you spend is on buying from your favorite stores, which you were doing anyway. “You can earn fractions of Bitcoin on Lolli every single day, which makes it an even more active wallet than Coinbase or perhaps any of these larger exchanges because people are just finding ways to make it a part of their daily behavior accruing money.” I'm so impressed by the Lolli strategy, and by Aubrey's dedication to educating people through it. It's one thing to talk about the importance of Bitcoin; it's another to actually get people to use it in their everyday lives. This is how you make real progress. The Benefit of Humanizing Your Brand For me, the question that arose from my conversation with Aubrey was this: how can I apply her same logic to my own business? How can we all? Bare bones, this is the situation I see: All of us have a wider audience we aren't reaching with the benefits of our products and services, whether that's because they don't know we exist or because they think we're not for them. Most of us want to get in front of that audience, but we don't know how – because we assume they already know about us, and have decided against us anyway. If we could find a way to reach the unreached and get them to give us a chance, we could see a serious uptick in business. The solution? Humanize your brand. Make it accessible. Tailor it to the mainstream as opposed to the people who already stan you. “Any way that you can humanize a brand is impactful, no matter what that may be," Aubrey explained. "People don't want to talk to brands; they want to feel comfortable, they want to engage. You should have your users want to spend money with you, and make them feel that way when they're shopping.” This makes me think of companies like LUSH in Australia and the UK. Not only is Lush one of the most inviting stores to walk into (smells, colors, textures), but they've also managed to remove all knowledge barriers and educate customers on their many natural skincare ingredients. How have they done this? Well, for starters: They've ditched packaging in favor of naked products (no pun intended). This means that customers can touch and feel the product before they buy it, making the experience more interactive. They have open cupboards and displays so that customers can see and smell all the products before they buy them. They have a team of knowledgeable staff members who are passionate about the products and can answer any questions customers might have. What's more, Lush has become a master of content marketing. They've built an entire website dedicated to educating their customers on the benefits of natural skincare, and they've done it in a way that's engaging and easy to understand. Bit of a left-field example, I know – but seriously, who else from the soaps and skincare industry has managed the same feat on such a scale? We can learn a lot from Lush, Honey, Lolli, and other education-first brands. Humanizing Your Brand: Outreach 101 To round out the newsletter, let's hear some of Aubrey's insights into what humanizing your brand requires. What are the steps, and what should you avoid? First, what not to do Aubrey's big no-no is compromising on your unique messaging. Don't sacrifice what makes you special just to get in front of a bigger audience. “A lot of these crypto companies are really trying to dress themselves up like banks. And that's exactly what we were trying to get away from. We're not trying to be banks anymore. We're trying to have this idea of freedom. And so I think really lean into what makes you unique, no matter what that may be.” Lolli doesn't shy away from its identity as a crypto company. It does, however, make an effort to meet people where they are, and to make investing feel more a part of everyday life. “We're trying to be the fun bank. We want to add different incentives like interest accounts and things like that.” Aubrey's advice A big part of the Lolli strategy is about making waves through social media. Lolli accounts aren't posting the latest stock prices or industry news; they're sharing relatable content and building a personality. “We've made our Instagram sort of a meme account. Our Twitter account puts out memes, but it sort of just trends with topics that are happening. We also have other channels where we offer the best Bitcoin back deals that you can get on Lolli." You might be thinking – a meme account? Seriously? No one's going to trust a meme connoisseur with their time and money. Well... you'd be surprised. “People make jokes about memes, but meme advertising is a new strategy that’s going on. People even argue there will be Chief Meme Officers in the future, because that kind of content is important for companies to relate, and it's easy engagement.” And of course, there's the education aspect; the whole goal of Lolli is to make Bitcoin more accessible. Aubrey makes sure that their marketing strategy supports this mission. "We can't just bring people in and then not educate them. Once you own Bitcoin, we want to explain to you why it's a better currency than people have already, and how to take care of that money. Because Bitcoin, while it is very simple in some ways, it can be very complicated.” Aubrey warns that we shouldn't be shying away from social media; it's where the crowds are, and where you'll make the most noise. “For people who may not know how to guide their company or personal brand, I would say just start today. Some people feel kind of intimidated by these platforms – that maybe they couldn't have a voice there. I think just start today and be consistent with your content.” Are You Reaching the Masses? I love today's newsletter topic because it's such a thought-provoking one. Are you accidentally cutting out a huge potential audience by failing to educate? Are you humanizing your brand in a way that makes sense, or are you selling yourself short? Aubrey really showed me that passion is one of the key ingredients to a successful outreach strategy. You need to believe in your mission. You need to want people to find your product and want their lives to change as a result. Trying and failing to reach a broader audience? Meet people where they're at – don't make them come to you. Attach yourself to something they interact with on a daily basis. If you can't do that, double down on your social media strategy and make sure you're being personal, relatable, and consistent. Thanks for reading, everyone. What's your strategy for reaching the unreached? I'd love to hear it below! Also published . here

How to Reach the Masses: Marketing to an Unreached Audience

The Economic Consequences of the Peace: Chapter VI - Europe after the Treaty

A few months ago, our team was contacted by the owners of a financial application for iOS, which has the main user market: North America, Europe, and some Asian countries. In this app, you can receive individual recommendations, up-to-date information about the stock market, simulate trading on the stock and cryptocurrency market, and view the trading results from other users in the app. In the application itself, during registration, the user left the following information about himself: First and Last Name, Email, Phone Number, interests in certain public companies. Attempts to Use Irrelevant Approaches There have been attempts to use email notifications to retain users. But, as statistics have shown, Email campaigns have proved very inefficient. Because many users ignored emails, some of them automatically went to spam, and only less than 20% of users opened emails. Many users also had low interest in the suggested click-through, and as a direct result, the click-through rate was extremely low. In addition, the problem was that not all users approved of receiving push notifications from the app, and some even ignored them altogether, accidentally cleared them, or forgot to check what was new in the application. Then, after a certain time, some users completely removed the app because they lost interest or motivation to check new updates. Together with the removal of the application, the subscription to the service will also be canceled. App owners decide to look for other ways to communicate to improve app retention rates. There was then an idea to use regular text messages, but this option has many disadvantages and showed good results only in limited cases. In SMS services, texting to different countries was very expensive, and for certain countries and cellular providers, the delivery speed left much to be desired. Sometimes messages did not reach the recipients at all, which also raised doubts about the reliability of this distribution method. Therefore, the idea of using instant messengers looked more promising. Instant Messengers for Contact with the Audience As a result, when the app owners contacted us with the question "How we can help their product," we explained that instant messengers are installed on most smartphones, and iMessage is used on almost all devices of the Apple ecosystem, being an independent internal communication system. And since the application was distributed only for iPhone and iPad, it was obvious that most of the users already have iMessage configured on their device. This eliminated the problem when, depending on the country, users had a different collection of instant messengers. The efficiency of using instant messengers is much higher than the traditional communication channels used to promote sales, but businesses are using them rather poorly so far. The main advantage was that, unlike regular texts, sending messages to any country via iMessage is absolutely free! According to our internal statistics, messages in instant messengers are opened 5 times more often than by e-mail, which provides new stable channels of communication with clients. Through them, it is more convenient to interact with users, help to understand the choice of products or services, with orders, and provide technical support. As a result, the owners of the application decided to try using our product for personalized messaging. Personalized Bulk Messaging According to our recommendations, the user base was unloaded, with the following data: Phone number, Email, First name, Last name, last interesting company. Contacts were imported into the LoopMessage macOS app via the import function. After that, the recipients were separated into three different groups: CSV paid users; active users without a subscription; users who were previously active but then did not launch the app for several weeks. Distribution for a group of active users was carried out 1-2 times a week. For a group of users who have not logged into the application for a couple of weeks, we distributed messages once every 2 weeks. Different message templates were made for each of these groups. For example, for users who haven't logged in for a long time, we formulated the following: 👋 Hello [FistName] [LastName]! This is the XXX app team. In the upcoming week, there will be significant changes in the stock market to the previous company you expressed interest in: [Custom1]. We are also ready to provide you with a promotional code for our personal consultations: [Custom2] Let us know if you have any questions. To attract the attention of previously active users and return them to the application, a different template was used, for example: Sup [First Name] 👋! That's Roger from the XXX app. New recommendations for [Custom1] are already in the app. Check them out when you’re free! At the end of each message, sometimes, a link to the app was inserted. For the [Custom1] tag, the ticker of the last company the user was interested in was inserted, for example, APPL or MSFT. The result was great. The message reading statistics were about 80-90%. About 30% of active users who received a message in the first minute immediately responded to it by answering, clicking on a link, or launching an application. The rest of the users have already read and somehow reacted to the messages during the day. Naturally, a certain proportion of recipients did not react in any way to our messages, and this is quite normal. The main difficulty was to try to communicate only with those users who really understand who they are receiving the message from. If you only try to reach those who’ve only spent a couple of minutes in the application a month ago and then deleted it, or even try to cold message everyone, then many users can mark messages as spam, and your messages will never reach them again. If you try to personalize messages for users as much as possible, it will create the effect of a message written solely for them. These messages will most likely show the best possible results. For all subsequent weekly messaging, we recommend changing the message templates to constantly look like personal messages for each recipient. Thus, customers may not even know that this is an automated process for hundreds of users using personalized tags. The rest of the users who could not be contacted via iMessage sent messages through the other most popular messenger: WhatsApp. Thus, it turned out to cover the distribution of messages for almost 99% of the entire user base. Final Results Unlike regular SMS, sending to instant messengers is free, regardless of the country where messages are sent to. Delivery of messages is seamless, unlike SMS, where we cannot even find out whether the user received the message or not, let alone whether he read it at all. Average message open rate: 80-90%. The number of users who return to the app after sending them a message: 25-50%, depending on the group of recipients. Messages are delivered to recipients almost instantly. There is no need to wait for any additional filtering, such as email or regular text distribution by SMS. Many active users read and respond to the message in the first minutes after sending it. You can send pictures, links, various media files, and other data that iMessage can process and display beautifully in messages. When sending via iMessage, you can identify the recipient with the user's phone number and Email. You can also specify Email as the sender of messages instead of a phone number. If the recipient has added the sender, he then will see the name indicated in their contacts. Even if the recipient uses an Android smartphone but has an iPad or macOS device, he can have iMessage activated and receive a message there. It is very important to add your business email and phone number to the user’s contacts. This helps solve the problem when Mail, iMessage, WhatsApp, and other messengers can flag a message as suspicious or move it to spam. To do this, you can invite users in the mobile app to download a file, which contains: vCard Application name (Company field), Corporate Email from which mails come, iMessage Phone / Email, Support team phone number, Application icon (Contact photo). The easiest way to solve this is to offer some minor reward because the user clicks the confirmation to add a new contact to his Address book. To generate a vCard file, you can create a contact on your iPhone/iPad, fill in all fields, and then export by clicking “Share contact.” As a result, it turned out that the owners of the application used LoopMessage not only for corporate correspondence (to return the user back to the application) but also to wish their active users happy holidays (such as on birthdays, Christmas, Thanksgiving, etc.), as well as congratulate them on and track their achievements (like successful trades or break-even days/weeks). This helped to always keep in touch with users and, sometimes, receive feedback to further improve the app. Benefits of the LoopMessage App The main idea of the product: it is easy to send personalized messages to your audience or customers in instant messengers. Our clients get several important features that give them great benefits: It is enough to indicate in the message to the client "Hello [First Name]," and it will automatically replace the teg with the username specified in the contact. A personal appeal to the client in the message gives a higher percentage of reading and involvement in the context of the message. In the application itself, many different tags can be used for personalization. Among other things, you can use “Custom Fields,” which makes it possible to fill in special information for each contact. In this example, stock tickers and promotional codes were added there. The ability to use personalized tags. The app will not ask you to enter credentials for your instant messenger. This is because the app will interact with accounts that you use in their native apps, where you are already authorized through your own account and subsequently protected by their encryption systems. Thus, all conversations with contacts will be stored only in your own accounts. Unneeded credentials. At the moment, the product supports the bulk sending of personalized messages in almost all popular instant messengers: WhatsApp, Facebook Messenger, Telegram, Skype, Viber, Threema. And also via iMessage, which is installed by default on all iOS/macOS devices worldwide! Supports popular instant messengers. The use of personalization tags in the application allows each message to be unique, as mass messaging of the same text is often marked as spam. Thus, if you follow the recommendations described above, you can avoid being blocked by instant messengers for sending spam. It should be kept in mind that if you plan to conduct “cold messaging” to contacts who do not know you or your company, this can look very suspicious to instant messengers, and recipients will mark your text as spam. Minimum risks of being blocked by instant messenger. The app can use contacts from your phone book for messaging but does not have the ability to edit or delete contacts. Your phone book is only under your control! No changes in your phone book. In addition to the regular Apple Contacts, you can use the internal contact storage in the app. All internal contacts are stored only locally on your device and are not uploaded to external servers. With CSV, you can easily import your contacts into the app. The support team is ready to help you if you have any difficulties with the import. Internal local contact storage. Please note that the iOS and macOS build differ in the number of instant messenger platforms they support. In the macOS build, the messaging is fully automated, while in iOS, the messaging is semi-automated. This is due to the fact iOS has a lot of automation limitations. You can download the LoopMessage app from the or iOS/Mac . Website App Store Also, if you initially purchased a license on the website for a macOS app, then it will work for the iOS version as well.

How We Increased User Retention in the LoopMessage App Using Free Messaging

Growth Hacking for Remote and International Developers – Part 1

In the fall of 2016, I quit my job at a recruiting startup. I found it soul-draining trying to convince bright young minds to make life decisions almost purely for financial reasons. I took some time to ponder what my next move would be. My window into the “conventional” startup market had given me concerns about the viability of many internet startups so I was a bit apprehensive about working at another one. The space seemed chock full of competition, with dozens of products for each “viable” idea. My favorite book is “zero to one” by Pieter Thiel and this made me far more interested in entering and creating new markets, rather than improving on existing products and ideas. It was during this period of existential malaise that I first stumbled upon Cryptokitties through a TechCrunch article about the sale of the Genesis Kitty(#1) 247 ETH. The product seemed quite interesting to me — I had done a research paper on Beanie Babies in college based on the thesis that one of the unappreciated reasons for the collapse of the BB market was actually the difficulty in authenticating and distinguishing them from fakes. Thus, Axiom Zen’s idea of storing genetic data for their collectibles(ERC 721 tokens) on the Ethereum blockchain resonated with me in a big way. I also grew up collecting insects and fossils with my father, so I’ve always been a collector of rare things. Breeding and selling rare kitties on the blockchain sounded like a dream come true! Cryptokitties inspired me to take a leap of faith into the world of decentralized gaming. I bought .8 ETH and loaded it into my MetaMask wallet and started scanning the market for cats to start breeding. Over the next few months, I spent around 20 hours a day surveying the market for good deals and breeding my kitties. I amassed a collection of around 2,000 Kitties and earned a fair amount of eth along the way. I learned the ins and outs of the kitty market and became known as one of the most skilled fancy chasers. I also joined the KittyHats team as their community lead. We were the first team to ever attach an ERC20 token to an ERC721. Shoutout to Dan and Jomessin for finding me in CryptoKitty Discord! After the initial hype started to die down and turning a profit became difficult the community started to ask: what now? Cryptokitties in its launch state was just what they said it was: breedable beanie babies on the blockchain. However, in my opinion, this created a problem similar to beanie babies where the craze would die down once the prices of the collectibles started to drop. Indeed, CK now has ~400 DAU(source dappradar) whereas according to dappsvolume.com they have had 77,000 accounts interact with their smart contracts. The last founder cat sold for 8 ETH compared to 254 ETH at the peak of the craze in December. I believe the community expected CK to be a game but in reality, it is just a data platform. The CryptoKitties are more akin to breedable “skins” for games that have not yet been created. Some of these projects such as Kittybattles and Kittyraces are starting to be developed, but time will tell whether it was a wise decision to leave the “game development” side of things up to community developers. In mid March after CK’s failed mobile app/china launch, one of the developers, for a project I’d never heard of, Axie Infinity reached out to me. He had been watching me since the early days of CK and was impressed by my journey from a small fish buying my first ETH to a top CK breeder, streamer, and Kittyhat’s Community Manager. The developer, that reached out to me was Trung Nyugen, one of the players that had actually unlocked the secrets of the CryptoKitty genome. We discussed how the blockchain gaming universe was in dire need of a game that would add actual utility to ERC 721 token. A game where players could use their time and effort to upgrade and improve their tokens and wouldn’t be charged through the nose to “play”. CK had shown that blockchain was useful for giving a true sense of ownership and creating a functioning market for the exchange of game assets but was severely hampered when it came to being an actual immersive gaming experience. I believe people left the “game” after it ceased to be profitable because to most, CK was more “work” than play. The Axie Infinity team had what I like to call the “second mover” advantage. We observed 4 crucial flaws in CK’s core product and designed our game to avoid them: Due to the high breeding costs, without a steady stream of new CryptoKitties players, much of the eth will flow into the hands of the auto-birthers in the long run. Autobirthers are “miners” that compete to verify each Kitty’s genetic data and get paid a fee for this service. It is impossible for your Cryptokitty to be improved by sinking in your time and effort. In fact, if you breed your Cryptokitty, its value of it goes down. So rather than being able to improve your token by “playing” with it, you degrade it. Not ideal. Because the kitties have so little utility now, the only real way to value them is through scarcity + aesthetics. New players have a hard time learning the breeding and gene systems so there is a big barrier to entry and it’s quite hard to answer the question “what should I buy as my first Kitty”. Axiom set an arbitrary limit of 50,000 gen 0’s. That might be way too many, or way too little depending on the size of their future user base — they have boxed themselves into a corner. Many community members are worried about what will happen to the game after November. When designing our product we kept these 4 flaws in mind and believe we have put forth novel solutions to each. For example, rather than using a fully decentralized auto-birthing system, we use Oraclize, a 3rd party, to birth our Axies. This has allowed us to maintain a breeding fee of .002, compared to .008 in CryptoKitties. We knew we couldn’t just optimize CK’s breeding, selling, and siring system. In order to create a new market like Thiel advises in Zero to One, we knew we’d have to add an entirely new layer. This came in the form of our Battle and Terrarium systems. In the Axie Universe, players will be able to form teams of 3 Axies. Like a Cryptokitty, each Axie has a unique genome and these genes correspond to 6 different body parts. These body parts have associated battle moves which can be used in Axie Battles. Axies gain experience from battles which can then be used to upgrade/evolve their existing body parts which in turn, unlock new battle moves. We believe that adding this sense of progression will be key in allowing our game to be the first decentralized game with a truly immersive gaming experience. https://medium.com/loom-network/loom-sdk-projects-axie-infinity-collect-breed-and-battle-fantasy-pets-on-the-blockchain-22e6fd11b410?embedable=true We are also developing a feature called the terrarium system. Just like real pets are often housed in custom terrariums, we realized that the ERC 721 token could allow us to build homes for our Axies as unique as the Axie’s themselves! In the future, Axie trainers(that’s what we’re calling them) will be able to house their Axies in unique terrariums and stock them with unique and interesting tokenized decorations and trophies. Imagine a world where a team of Axies can hang out together when they’re not in battle, surrounded by beautiful plants, decorations, and their trophies from past battles/tournaments they have won! Axie Infinity has currently raised around 1000 ETH with a small team consisting of only 2 developers and 4 artists and 2 growth hackers. We believe that our lean structure combined with the new funding mechanisms made possible by token sales of in-game assets have shown the potential of decentralized gaming. I’m now currently in Vietnam and will be speaking at conferences across Asia this summer. Six months ago, this would have been unimaginable to me. There’s so much promise in this space but decentralized game developers must understand that the ecosystem is fragile. We must make sure we treat our players as our partners and backers. I love communicating directly with our players through discord, Twitter, and live streams. Without direct communication channels between developers and the community, trust dries up and the developers lose touch with the expectations and pain points of their players. It’s still too early to say what will happen in this space — perhaps companies like Blizzard will make the shift to blockchain and snuff us all out — but my suspicion is that the people working on quality decentralized games now will be working as game developers for a long long time. In fact, conventional game companies with millions of users have already reached out to us for advice indicating that the experiences and knowledge we’ve gained in these 6 months are quite valuable to centralized game developers. I believe they will have a difficult time crossing over into developing decentralized games and our competitive moat will be strong for a long time. Much Love, Lead Image source P.S. If you’d like to get in contact with me and discuss the ideas I’ve presented here please feel free to send me an email at or find me on the Axie Infinity Jeff@axieinfinity.com Discord.

My Journey in CryptoCollectibles (so far)

Lessons from Amazon’s shareholder letters

Disclosure: , which provide real-time APIs for developers, has previously sponsored Hacker Noon. Pusher Stock market data becomes more valuable as it essentially delivers an opportunity for traders who seek analysis and statistics. In this tutorial we will be building a trade platform that portrays the experience for stock markets, where trades in prices can be visualized in . This will be built using , Chart.js and realtime capabilities powered by . realtime JavaScript Pusher Pusher is a platform that specializes in building realtime infrastructures for developers in order to build realtime applications as efficiently as possible. We will be leveraging the powerful features of Pusher to show updated prices on our chart directly from the server and also add an extra feature to display a table depicting the prices as shown below: Getting Started As stated earlier, Pusher will be used to easily deliver the realtime functionality necessary for our chart to function as specified. If you don’t have an account with Pusher, you can . Once you are done, go ahead and create a new app from your dashboard. Don’t forget to take note of your , , and as you will be required to use them later in this tutorial. sign up for free app_id key secret cluster Set Up Application Now that we have set up an account and obtained the necessary credentials, we will need to set up a server and the view for our application. This is to ensure communication between our application and . If you do not have Node and npm installed on your machine yet, kindly download them from in order to follow along. Otherwise, proceed creating a new directory with any name and run the command below : Pusher here npm init -y You will be asked a bunch of questions, and then a package.json file will be created for you. Update the file with the following: Now edit the file above by adding the script to start our local server, we will set this up in a bit. We need to install the Pusher SDK and also to help us launch the client app: serve ## Pushernpm install --save pusher ## Servenpm install --save-dev serve We also need some existing dummy data in order to create a proper simulation of stock trades and price variations. For this reason, I downloaded a data sample of previous stock history we can play with. Below is the truncated version of the . You can find the complete file . stock.json here Next, we need to create our project files. In the project folder add the following files and leave them blank. We will fill up the content as we go: Create a Simple Server Within , import the file and initialise Pusher with the required credentials obtained from the application dashboard. server.js stock``.json For our clients to receive realtime payloads, we need to emit those payloads from our sever using Pusher: Every 2 second, we query the JSON file for stock prices and and emit this price alongside some other payload (like the stock name) as JSON using the Pusher’s method. This method takes channel, event, and payload as arguments. GOOG trigger Run the following command to start the server: npm run serve Build the Client App First things first, update your with the following: index.html You have a where you will launch the chart as well as a simple table to show the current prices as they are updated in realtime. We also included the Pusher and Chart SDK which we will use soon. canvas To receive the payload sent in from the server, we need to subscribe to the Pusher event emitted by the server. And to visualize it, you need to create a chart and keep updating it’s data points using the payload received from the server. We will need a couple of functions: App Class We just created the methods bodies. Next is to start implementing their functionalities one after the other. First, let’s initialize Pusher For debug purposes only, we are setting to so as to see the realtime activities logged to the console. Remember to remove that in production so you don’t leave your user’s console bloated with debug logs. Pusher.logToConsole true Next, we create an instance of . The constructor function is available in the file we included earlier. Pusher pusher-js Remember the server is still emitting data. We need to subscribe to it and start consuming the data coming in: The method on Pusher takes a channel we need to subscribe and returns a subscription. We can then bind to this subscription using and passing it the event’s name and a callback function. subscribe bind In the event, we called and passed it the data to keep updating the chart. We create an instance variable in the constructor called . We also called the method to setup the chart in the constructor as well. Before we see the update chart logic, let’s see how this chart is initialized: updateChartData chart initializeChart It might look overwhelming, but a closer look shows that we are just defining a chart and describing what kind of data it should expect, how it should label the data, and how it should look. Now, the update chart method uses the chart instance to update the chart every single time data comes in from the Pusher server. You can launch the client app with the following command: This will start the web application on port 5200. Open up up your browser Realtime Ticker At the moment, thanks to Pusher’s functionality, we are able to update the chart in realtime with the payload sent in by the server. Let’s proceed by adding another feature to display the prices on a table. We will choose a random price to be set as a threshold in order to determine when the price increases or decreases as it is being received from the server. These changes in prices will be indicated with different colors as it is obtainable in any stock market chart. Remember we had the following table in our : index.html To make this work we will edit the method and also create a new one called . The new method will be used to change the colors based on the changes in prices. updateChartData() flashColor``() Don’t forget to include the threshold price within the constructor like this : For visual cues, here is a function that changes the color of the price text every single time the threshold is beat : And that is it : From the chart, the green color for prices means that the price has gone above the threshold while red indicates reduction in price and blue means it is exactly the same as the threshold price. Conclusion From this tutorial, we have seen how to build a stock market like platform where changes in prices are being updated in realtime. This can be built upon and used with any chart library. In case you miss anything, the complete code can be found on GitHub. You can find it and please feel free to submit a pull request. here This post first appeared on the . Pusher blog

How to Build a Realtime Trade Platform with JavaScript and Pusher

This is the text of a talk I gave in March 2017. The world has woken up to AI. Here’s an illustration of this exponential trend: the number of press releases published by companies mentioning “Artificial Intelligence” skyrocketed over the last few years. I conducted a research myself and asked : when AI is being used so frequently in so many different ways, does it have any valid utility in differentiating one thing to another? my Twitter network They were split. About 58% said it doesn’t really have that much use as a description anymore. It brought to mind this kind of idea that comes back to John McCarthy who said: “As soon as it works, no one calls it AI any more.”. It’s been a six-decade journey to get here. Sixty-one years ago the first conference in AI got together at Dartmouth University, bringing together the likes of McCarthy and Herb Simon, Norbert Wiener & Martin Minsky. At the time they thought they’d solve what was the problem of AI then, which we would now call artificial general intelligence: building a machine that could replicate human intelligence within a few years — within a decade is generally what they would say. More, McCarthy, Minsky, Selfridge and Solomonoff How could they be that optimistic? There are a few reasons for this, and it’s important to put them in their historical context: The American scientists who came together were part of what was known as . They had , they had . They’d become the major exporter of the world, and they had marshaled their resources to the to build the Atom Bomb. the Greatest generation lived through the Depression seen America win the WWII Manhattan Project In 1956 they to the Soviet Union. hadn’t yet lost the Space Race But, there were a few problems: They didn’t really know how the human brain worked. It’s pretty hard to build something when you only have a vague understanding of the mechanics of the thing that you’re trying to emulate. The way in which their math or their logic worked was very much grounded in symbolic logic or decision trees which, as we’ve seen a with recent breakthrough in statistical or probabilistic models, has not necessarily been the ideal way of delivering stuff that looks vaguely intelligent. They didn’t have integrated circuits at the time. This group of great minds faced some steep challenges. They didn’t really know what they were building, they didn’t really have the kind of maths to build it and they really didn’t have the processing power on which to run the math. The Cycle of Innovation — Where Are We? So much for sixty years ago. But today AI seems to not just be present but on the cusp of exploding into something significant. The question: is how do we go from that moment to a moment where we seem to be building small things and then suddenly have a moment where there seems to be rush, a ubqiuity, of development? developed a powerful framework: she thinks about technology waves in cycles. Carlota Perez In what she describes over the course of five revolutions, technical revolution is a process where society reconfigures itself over a forty to fifty year period through installation, readjustment, and deployment. This is where there is some kind of breakthrough technology, and combining breakthrough technology with really rare skills creates a set of opportunities. The technology isn’t that useful, so it needs to be deployed into markets using technology push. That’s what many of us would have remembered having gadgets that didn’t really work. During this phase financial speculators, financial capital recognize that there is a new market about to be created and because they can reconfigure themselves very quickly financial speculative capital starts to pour into this market early. It pours in ahead of the technology being widely deployed. Re-adjustment or the “turning point” is the interim period of instability, and, ultimately, economic collapse. The final phase is a reconfiguring stage. This is a time of creative construction; it’s a time where the skills that are needed to make use of this breakthrough technology are much more widely disbursed. It’s a time when consumers actively seek out solutions that depend on that technology. It’s also a time when production capital rather than purely speculative capital is applied for the build out of this new infrastructure. This model can help us think about where we are in the cycle, and what the world is going to look like. Find a Ford: The Model T was introduced in 1908; it was incredibly popular within five or six years. This photos from 1926 in New York City, 18 years after the introduction of Model T. This is New York in 1926. Eighteen years after the introduction of Model T Ford. At that point, technological revolution was still in its . deployment phase In 1908 Henry Ford had introduced the idea of Fordism and the production line. It was a brand new concept. Sales of the Ford car accelerated pretty quickly, pretty exponentially for the time. There’s the readjustment phase: Wall Street crashed in 1929, followed by the depression and then World War II. After that deployment phase came an incredibly optimistic time in American history: they built out highways, got into air travel, holidays became a new normal, suburbs flourished, as well as the suburban shopping malls. Lots of economic, technology and business innovations were deployed across an installation platform. With Carlota’s theory in mind, we need to ask: where are we with ICT? (AI is really part of that wave?) We’ve seen the installation phase beginning in 1971 with Intel 4004 processor. We saw demand for rare skills. It was a small number of people involved in the tech industry, and there were companies that got a tremendous amount of market power: . We alongside this saw the growth of the venture capital industry starting in the late ’60s. Intel, Microsoft, Oracle We’ve had our moments of readjustment. We had the dot-com bubble. Look at WebVan.com and Kozmo.com. They had classic problem of e-commerce in 2000. Not enough users on the Internet, technology infrastructure was immature, and sotware was shonky. In short, far from the prime-time we see today. I can speak from personal experience, too. I invested in an online real estate portal in France. Seems like a great idea today. Most people today use online search for their homes. . No real estate agents had computers in France and none of their customers buying houses had computers. We had this enormous customer acquisition cost where we literally had to buy them the technology: PCs, modems, second phone lines. Not in 1999 Moore’s Law, the Sea of Data and Business Reengineered Does Perez’s model fit where we are today? If it does, what does it mean for us in the field of AI? We do seem to have got to a stage where there are a lot of key infrastructural things in place for this. I’ll look into three. Limits of Moore’s Law and Beyond When I was 13 years old I had lusted after Cray-2. It weighs two and a half tons and it costs $35 million and can do 1.9 gig of FLOPS of calculation power. The PC I had at home was doing about 10,000. Interestingly the 4004 processor back from 1971, the year before I was born could add two eight bit numbers 11,000 times a second. Try running your neural networks on that. With the continued application of Moore’s Law we get to the point where the iPhone 4 is as powerful as a Cray-2, costs $400 and it sits in the drawers in our kitchen. Apple Watch is 100 grams, $300 and is twice the raw processing force power as a Cray-2. What I find interesting is that the industry hasn’t stood still even as we hit the physics limits of Moore’s Law. The blue curve shows us that we started to find architectural enhancements and more specialized architectures and video range of GPUs and you see their growth curve in terms of processing. Availability of data Data is the rocket fuel that powers the math that we do. In 2013, the world had a stock of about four zettabytes of data where 90% of it had been produced in the last two years. Essentially in 2025, which is not so long away, the amount of data we will produce in a week will be the same as the entirety that humanity produced up until 2013 as a species. That’s quite a sea change. Source: IDC Prior to us all having smartphones we didn’t really create that much data; and now with smartphones, without really thinking about it, we are creating : we’re creating Tweets and photos and videos and interactions and messages. Also, it’s not just the human data, it’s the machine data, too. a lot of data The kind of data they would generate is going to be really, really intriguing. If we look at the growth of the CMOS sensors we see flat growth until just about the point in 2011 where iPhone sales are taking off. Since then that’s two billion shipments of CMOS sensors. We’re forecasting six billion or a 3x improvement in an eight-year period. Source: IC Insights We’ve also seen data sources come from other places. These are happening on top and separate to what’s happening in a consumer home with the IoT. Just looking at Earth observation data there’s a tremendous growth in the demand for sale of Earth observation data to the military and to private. There’s also growth in the number of satellites that are being sent up to observe the Earth. Companies such as Orbital Insights and SpaceKnow are taking photos from Earth observation satellites, running them through machine and machine vision to make predictions about how well human companies are doing. learning If the JC Penney shopping mall has fewer cars in it on a given Tuesday in February than previous Tuesdays in February . Of course you can apply that to oil tankers pulling up to the docks in Mumbai or cargo being unloaded at Singapore. that might tell you something about how well their sales are doing The world has become software driven Three things are happening. 1. Architecturally, software doesn’t look like a monolith of spaghetti code that’s really poorly documented. It looks like this perfect architectural diagram with really neat functions and APIs and well-defined contracts in between them. 2. Businesses have reengineered themselves. BPR, business process reengineering was a thing that all consultancies were selling to medium and large firms from the late ’80s through to the dot-com bubble. Business process engineering was essentially APIfying and contractualising internal operations of the company by making them separable, allowing us to find core competencies, enabling outsourcing. 3. The effect is present. Here’s how it works: AI Lock In Loop Once you put a piece of AI into a product some kind of prediction or some kind of optimization, safety or routing algorithm for your logistics company, your service and your product gets better. As your product gets better, you generate more data, and at the same time if you’ve got a decent business model a better product should mean more profits. More profits means reinvesting into improving AI. There’s no way back. What we have seen is that once you implement AI successfully into an industry and into a sector it’s impossible to compete without it. Think about web search — web search has had to have the machine learning, artificial intelligence in it, and it would be almost impossible to imagine someone launching a web search engine that didn’t use some kind of machine learning or data science. You wouldn’t launch a web search engine that just did as its ranking. Tf-idf The other thing that we’ve seen is that AI Almost every week there’s read another example of a narrow domain piece of AI which is outperforming humans. beating humans is very, very normal. Nowadays speech recognition is performing with 5.9% error rates, far better than humans and has gone even further than that. Back in 2013 or 2012 none of these things would have been done better using machine learning — and that’s only a few years ago. not a single one, There’s one issue we seem to have in our industry, that we ultimately saw previously in the oil industry. Huge companies such as Standard Oil and Ford dominated key parts of the oil industry. In our case, Google and have essentially got infinite computing power and know-how compared to any of us. The question is what long-term structural advantage does it give them? Are we getting the crumbs that fall off the capitalist table onto this chair for what we are and do we really have what it takes to compete in some of these domains? Facebook These companies are really hungry to build their talent bases globally and that creates a tension if you’re an entrepreneur because you can get from a Google or an Apple early into the lifetime of your business_._ fuck you money I still think a full staff matters_._ Uber is not a machine learning company but is worth 100 times more than the biggest AI exit so far and they have made a pretty significant commitment to automation_._ They’ve acquired Otto, they took the CMU robotics team and they used ML in lots of places in their business, not just in routing but even in the consumer app that some of us might still be using. It’s an amazing period of innovation. And responsibility. Today the products that you can build control our interface and access to all the services that we need. You have to adopt the mantle of civic leader in some level. You determine how our attention gets spent, you determine how we understand our news. You kind of determine how our civil society is functioning. I think it’s really important to stand up to those responsibilities as product entrepreneurs particularly when you are essentially going to be building what stands between me and the real world. You can read more about the most pressing issues in technology in my weekly newsletter. . SIGN UP FOR EXPONENTIAL VIEW HERE

State of AI: How did we get here, and where are we going next?

To explain why, we need to go through a future scenario of how we build a business in order to explore the future potential of AWS step functions. Building a business from a great idea, some future Monday It’s Monday, it’s the year 2025 and I’ve woken up with a great new idea. [Actually, it’s a pretty lousy idea but hey, I just spent a few minutes on the scenario so let’s just assume it’s great] I’m going to create a recommendation engine for stock picking based upon the mood of the internet. I quickly scribble down the user needs “make profitable trades” and “know what to buy” and write a basic map whilst grabbing breakfast. I have my map, I know the basic components that I need — the recommendation engine, trade feed etc. I start work at 8.30 am. I know Amazon provides one of the components as a service (the lambda platform) and several others can be found as AWS lambda services in the marketplace. The company I work for also provides a stock portfolio service. I mark up what I think we can use (where we are the consumer) and what we need to build (where we are the provider) e.g. the recommendation engine and the mood system. It’s 9.20 am, I send the map of to our spend control group. They act like an intelligence gathering organisation, collecting all the maps of everyone, comparing them and giving some feedback. They build profile diagram by finding common elements between the maps. I get a reply by 10 am with some details. They send me the profile diagram below. It seems some other team in the company has built a recommendation product. I’m the only person thinking about a mood system. In general, I’m roughly where everyone else. However, 16 different teams are using trade feeds and everyone else works with a well developed lambda service. Apparently lots of groups are using some utility service for a trading engine. I click on the profile for the details, it’s Amazon. They’ve also sent my map back, slightly modified. Ok, well at least this is not the like the bad old days of 2015 where my company had thousands of duplicated systems and endless rebuilding of stuff that already existed. It’s 10.15 am. I start thinking about some metrics. The trade feed system is going to be providing trades to the recommendation system. Each one will need a call to the mood system, the risk system and so on. I start marking out where all the metrics are. It’s 10.45am. I flip a switch and the map is converted into a business model. The same components, the same links, the same metrics. I start running a few scenarios, checking that I’ve made a truly variable cost business model. It’s 11.30 am, I send the map and the model to finance. They come back with some helpful comments . [in this case, it would be “how do we make money?” but then again the scenario took me a few minutes, so I’m taking liberties] It’s 12.00 am. I send the maps and the improved model to the executive group. Thirty minutes later I get the go ahead and a small budget of $20k. I know from the spend control profile that some other cells are already building this stuff. I give them a call, tell them what I’m upto. They already know, spend control told them. I know from the spend control profile that there is a group building a recommendation engine. I send them the map and model and outline my idea of adding a mood system to recommendation. We have a quick call and they’re up for it. We agree a metric of value for charging — everyone uses worth based development these days. Most of the stuff I need (i.e. 80%) is already built and provided as services. I just need a cell of pioneers to build the mood system, whatever that will be. I update my map with the organisation structure and load it with the build map and financial model to the company’s job portal. I wait. Our company operates in cells, using pioneers, settlers and town planners. We live in a constantly changing environment. Watch the movie! I love it. YouTube video on pioneers, settlers and town planners Because of this, we always have pools of people training and looking for their next cell to join. It’s 1pm and no-one has responded. I’m getting worried. I’m looking at the other exciting projects on the jobs board. Out of the blue, by 1.30 pm I’ve nabbed two pioneers willing to give this a go. They sign up. We’re off to the races! Of course, HR is constantly monitoring the flow of components through the maps, the cells being formed, whether we need more pioneers, settlers and town planners. This goes on in the background. They’re checking what we build vs what we buy and whether we have the right balance of attitudes. Long gone are those old days where dullards would try to convince us that a company could have one culture. Long gone are those days we were weren’t looking for the right skills (aptitudes) and the right attitudes. HR is on a bit of recruitment drive at the moment, we’ve been lacking enough settlers especially in finance and engineering. The pioneers start cracking away with the project. They’ve organised the cell the way they like it, recruit a few others and build the mood system. They understand the map and what they need to create. They have autonomy (their cell), mastery (their attitude e.g. pioneering) and purpose (the mood system and where it fits in with the wider scheme from the map). It only took a few hours for them to get the mood system up and running. Most of it just used existing lambda functions. They’ve added interfaces for the recommendation engine to call and we’ve all started monitoring whether consumers use it. I start monitoring flow in the system, where’s the money going, are there bottlenecks, how are we doing on those metrics? Those metrics act as the fitness functions for the cells. It’s important we keep track of them. Of course, we’re not the only ones monitoring. Part of the spend control group looks after strategy and they are already looking at the maps for new opportunities. Our stock portfolio system and recommendation engine are provided to other companies through public APIs. Spend control measure consumption of the services to identify future trends. But they’re also watching how the mood system is going, maybe we should provide it as a service to others and not just to our own recommendation engine? Spend control notice the mood system is picking up and they’ve heard rumours that other companies are looking into this space. Differentials don’t last long in this world, you measure them in weeks. Spend control decide we should push the evolution of this towards more of a utility. It’ll need development and in this case, they recommend an open approach is worthwhile. In the next few days, the project is soaring and I’ve noticed a new project on the company job board to turn the mood system into an open sourced project. Several settlers have joined our mood cell. By the way, if it wasn’t obvious, I’m a pioneering manager. I’m not actually part of the mood system cell, I belong to a hierarchy of managers that monitor cells, help initiate them, define the fitness functions, keep track on operational flow, build the business case and basically remove any obstacles I find. I specialise in the genesis of new projects and concepts. On rare occasions I have good ideas, most of the times I get them from others or from searching the ecosystems around our company. When I’m not looking after cells, I work in spend control. It’s not so much that I manage the cell, they are autonomous, it’s more like tending a garden and helping set the right conditions. I specialise in management and pioneering. I’m no different from those specialising in pioneering and engineering or finance or design except in aptitude (skillset). We all have the same attitude. We’re no different to settlers or town planners except in attitude. We’re all important. As pioneers we tend to discover the swamp and die off from malaria. We fail a lot, take huge risks. The settlers make the swamp liveable and the town planners build Rome. I’m always amazed by what they do. It’s the end of a week. I’m in a good mood. The mood cell is up and running, it’s even growing into an open source effort. The changes to the recommendation engine are working. The metrics look good. It’s turning into a nice little business. I have a relaxing weekend and get a good sleep. It’s Monday, it’s the year 2025 and I’ve woken up with a great new idea. Kitten internet where your kitten can order its own food! I check my messages. One of the pioneers in the mood cell has had a much better idea. I’m off to help her map it and see if we can’t get another cell up and running. — — The scenario was put together very quickly and is only an illustration designed to explain one thing. If you use a map then there is no reason why operations, build, strategy, finance, HR, strategy and other groups can’t happily work together without miscommunication, misalignment, duplication and bias. All of the above systems I’ve used in one form or another across multiple groups in a business over the last decade. Unfortunately there is currently is no integrated tool for doing this even though it promises a future where development, operation, HR and financial can be combined together through the use of mapping of some form. Before you go “we have maps” — the chances are you don’t. Maps at a minimum need to be visual, context specific, have position relative to an anchor (e.g. value chain relative to user or physical position relative to compass) and finally they need to visualise movement (e.g. the evolution axis). Where will such a tool come from? The practices and systems above already exist to varying degrees within a number of organisations. As for codification of these practices into some formal tool then we’ve already started down that path at the level of code with . It’s well worth watching the video. Despite the appearance of being technical, the future of business development is being born here. AWS Step Functions YouTube video on an Introduction to AWS Step Functions There’s quite a long way to go but eventually it’ll move up the stack and as systems become more complicated then it’ll have to cope with evolution itself. As useful as micro services are, you will eventually find that you have custom built components on top of layers of custom built components. Fragility starts to bite. You’ll find yourself having to deal with the problem that evolution causes. However, as soon as you start to visualise this then you’re on the path to creating a map. The future scenario above becomes possible and this is where AWS step functions will head, in my humble opinion. Almost every past practice in business will go boom! This is marvellous. Thank you Amazon. An alternative path comes from tools such as which have started with user needs and are making the journey down the value chain. Eventually these two approaches will overlap. Atlas One final note I often take things for granted and forget to spell things out enough. If it’s not clear the maps in the scenario above and the related systems (e.g. spend control) simply represent the codification of basic doctrine. If that word doesn’t mean much to you then can (also, if you don’t know what a map is — ) I suggest reading some basics of strategy start with chapter 1 I’ve highlighted below (in orange), the basic doctrine that the maps and systems cover in the scenario. If this is unfamiliar ground for you then spend sometime going through the scenario and checking them off. You’ll find them all hidden in there. When you think about AWS Lambda, AWS Step Functions et al then you need to view this through the lens of automating basic doctrine i.e. not just saying it and codifying in maps and related systems but embedding it everywhere. At scale and at the speed of competition that I expect us to reach then this is going to be essential. For some further background reading on all the above try Amazon is eating the software (which is eating the world) Why all the fuss about serverless? — — This post is provided as Creative commons Attribution-ShareAlike 4.0 International by the original author, Simon Wardley, a researcher for the Leading Edge Forum . Catch me on twitter as @swardley Originally published at blog.gardeviance.org .

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