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RealReal

the-realreal

The Covid-19 pandemic has catapulted a number of businesses towards embracing at a pace that couldn't have been anticipated as recently as January 2020. The impact of this massive push toward digital transformation has presented fresh challenges in keeping employees engaged. working from home (WFH) As employers grapple with the notion of keeping their workers focused and motivated towards their tasks in an entirely remote environment, is beginning to emerge as a key tool for businesses to successfully operate on a WFH basis. big data (Image: ) Business Wire As the chart above shows, 20% of respondents to an noted that remaining focused on their work whilst avoiding domestic distractions was the greatest challenge they faced when working from home. Adaptavist study Worryingly, other respondents cited fears for creating the right conducive working environment and their own mental health as further challenges. Such concerns can’t be taken lightly by employers, and it’s essential that companies create a functional environment that not only ensures employees can remain productive but that they can also keep well equipped, motivated and happy. Significantly, big data can play a major role in helping employers to identify the best measures to take with employees on a case by case basis and to help them to succeed in a WFH environment. Cater Directly to Employees on an Individual Basis Before big data and WFH, businesses typically papered over emerging problems with quick fixes, rather than getting to the bottom of what may be going wrong. One of the key issues here revolved around managing office culture. How can a company cater to employees based on their bevavior? Is the work culture positive? Is it reflective of the company? Despite as many as 80% of employers claiming to conduct surveys to gauge employee satisfaction, the believes that “many admit that they don't understand how to interpret the results nor what to do to improve survey scores.” Society for Human Resource Management Big data can change this trend in a fundamental sense. In a world where each employee is different, it may have been the case that we needed to see a big data intervention even during the days of in-house teams. Now, as employers are more distanced than ever from their workforce, and unable to communicate in a face-to-face manner as a means of seeing those important physical responses to queries and task management questions, big data has become imperative for reaching employees. Here, it’s to better understand your employees. Discover what inspires workers, what causes them to lose motivation, and what challenges, and avenues for communication that they’re more apathetic about to help improve their performance levels and happiness. essential to use data Much of these employee comprehension challenges can be found in the huge volumes of throughout businesses. From personality questionnaires to analysis surrounding employee performance and behavioral reactions to different forms of communication, it’s possible to gather plenty of relevant information surrounding important employee metrics for employers to comprehend and act upon. HR data already available By embracing the information our staff share on a daily basis surrounding their motivation and engagement, it’s possible for businesses to ensure that their workforce is happy and eager to reach their goals at all times. Acting on Macro Trends Today, the analytical data produced by employees has the potential to help businesses to identify micro and even macro trends before they develop into a wider problem. By spotting such trends in their early stages, HR departments can help the business to alter their focus in order to leverage stronger connections with employees and to avoid growing risk factors. “HR leaders who embed data into their regular weekly routine demonstrate focus, accountability and credibility that’s on par with other business units in the company,” , Chief People Officer at The RealReal notes Zaina Orbai Whilst spotting macro trends using big data can be a tall order from a more analogue perspective, there are many platforms that can operate behind the scenes to ensure that employees remain engaged throughout their tasks. One example of a big data employee engagement tool is IntelliHR, which continually analyzes employee sentiment surrounding business processes to help optimize the pursuit to task management among companies. This use of that are capable of engaging employee satisfaction and task management habits to the point where it can automate entire workloads for individuals can be an excellent way for companies to get the most from their staff without risking negatively impacting their happiness. big data platforms Such software can even be used to help optimize employee communication and collaboration tools within business models. For instance, remote work forces have increasingly been forced to use video conferencing to collaborate with one another. But when the microphones and webcams are switched off after a presentation, how can employers know the impact of their slides? With big data services charting employee sentiment and performance in the wake of remote presentations, companies can use the emergence of macro trends to optimize slides and create a . thoroughly engaging presentation Through the use of platforms like Powered Template, which works to deliver premium quality PowerPoint, Google Slides, and Keynote presentation templates, as well as a and infographic templates, employers can gauge feedback and modify their content piece by piece to create bespoke presentations to suit the needs of their teams. suite of data presentation Powered Template’s premium subscription services mean that businesses can create custom presentations that are pre-prepared and 100% editable to reach out and appeal to the right employees at the right time. Furthermore, the platform also features a wide range of stock images and graphics, meaning that presentation templates can be modified and adapted quickly to correspond with . wherever the data is pointing Although the age of WFH has been a shock for some businesses, big data can help to keep your workforce close and as engaged as ever with actionable advice and efficient workload suggestions. With the help of the right software, your business can be ready to continue innovating deep into the era of digital transformation.

How Big Data is Keeping Employees Engaged in the Age of WFH

A couple of months ago I was at the and had a conversation with Looker team. We’ve talked a lot about data analytics, existing solutions and approaches and before I left their representative gifted me a book that I want to review today. The book is called and it’s great because it gives you a clear path how to start working with data you own but probably don’t how to use properly. AWS Summit ‘Winning with data’ That was another reason why I enjoyed this book so much — it came right in time because at Scentbird we’ve reached that stage when we have a lot of actionable data, and it’s important to know screw it up from the beginning. And that’s one of the problem authors highlighted in the beginning. To be precious, there are four significant problems with : data — a lot of departments suffer because it’s hard to access the data; Data breadlines for the data-poor — there is no easy way to understand what kind of data is right for you; Data obscurity — big and medium organizations tend to create a lot of separated data sets that are not aligned; Data fragmentation problem — different teams treat the same data in a variety of ways. Data brawls These problems were the same for the different organizations, so that’s why we can find similar solution all over the : - Google with and - Facebook with - and many others. internet Sawzall Dremel HiPal AWS Redshift But you shouldn’t be at that scale to become data-driven. There are some examples from SMBs:- uses reports on a daily basis to understand what’s going on with their operations and revenue and how they should align their marketing and merchandise plan to improve it.- named one of America’s Most Promising Companies, has very complex operations, that requires to process and catalog thousands of items every day, so data-driven approach helps their teams to meet their KPI, understand customer engagement and see general trends.And there are more examples from Zendesk, Warby Parker, HubSpot, and DonorsChoose. The RealReal ThredUp So what does it take to become a data-driven company? Usually, there are some basic steps: — every time your business team wants something they ask one of the developers Ask the Engineer — your dev team creates a simple solution that allows exporting raw data (for example in CSV) Access Raw Data — in-house solution for solving data problems (sounds as a good solution, but still requires technical and business teams to work in a close touch) Bring Your Own BI (BYOBI) — next level BI that helps business team to access data in more or less convenient way (like , , , etc.) Data Fabric Looker RJMetrics Chartio But even the best tool is just a tool, and you should be very careful to avoid data biases. The most common is a “survivorship bias.” During World War II, the statistician Abraham Wald took survivorship bias into his calculations when considering how to minimize bomber losses to enemy fire. Researchers from the Center for Naval Analyses had conducted a study of the damage done to aircraft that had returned from missions and had recommended that armor be added to the areas that showed the most damage. Wald noted that the study only considered the aircraft that had survived their missions — the bombers that had been shot down were not present for the damage assessment. The holes in the returning aircraft, then, represented areas where a bomber could take damage and still return home safely. Wald proposed that the Navy instead reinforce the areas where the returning aircraft were unscathed, since those were the areas that, if hit, would cause the plane to be lost. ( ) Wikipedia There is an of fighting “survivorship bias” at Facebook. interesting case One of the approach to avoid this is to teach all your team in the same way like it’s done in Zendesk: — people learn the most basic language for asking data questions SQL — where to find all the different data sets Data architecture — a review of key metrics and their definitions Data dictionary — accounts of previous problems and how they were solved Case studies Basic statistical concepts — how to construct an argument with data and vizualisation Storytelling with data — determining whether this data analysis will result in a tangible change in the way the company operates Actionability When these steps are done, it finally comes to the most interesting part — asking the right questions. https://logianalytics.com/definitiveguidetoembedded/the-future-of-embedded-analytics/ And that’s we can find in between steps 2 and 3 in the Gartner data sophistication journey. This missing step is called described by John W. Tukey almost 40 years ago. One of the most important things about exploratory data analysis is that it’s easy to understand how good your questions is, just answer “What decisions would that analysis inform?” So, no matter what type of analysis you perform a proper action should always follow it. Exploratory Data Analysis And last but not least — you should know how to present your data, so it’s easy to understand, it’s not boring, and it’s actionable. I plan to cover this topic in the next about data visualization. book review “Winning with data” is a great, interesting book I recommend you to read. P.S.: This book has a lot of links to useful information, some of them I want to share: Data Warehousing and Analytics Infrastructure at Facebook With Amazon Redshift SSD, querying a TB of data took less than 10 seconds How Businesses Make Decisions and How They Could do it Better How Leading Organizations Are Adopting a Data-Driven Culture Why Google has 200m reasons to put engineers over designers Why Intuit Founder Scott Cook Wants You To Stop Listening To Your Boss Making data mean more through storytelling Resonate: Present Visual Stories that Transform Audiences

Winning with data — your guide to the data-driven world.

According to , the metaverse fashion industry could be worth as much as $55 billion by 2030. This rapid growth will be led by new technologies that aim to push the boundaries of what we currently know about fashion. Deloitte The current fashion landscape is evolving, and it is poised to completely change how, when, and why we shop, thanks to innovations like digital fitting rooms, in-store virtual assistants, and the ever-growing popularity of the metaverse. 1. Virtual try-on In the same way that brands like IKEA and have introduced augmented reality "try-ons" for home items. Brands are now turning to AI to offer customers virtual try-on services. This not only makes the at-home shopping process easier for the customer, but it also promotes mindful consumption and sustainability, too. Amazon In 2022, of all online clothing purchases in the U.S. were returned due to reasons like wrong size, color, or fit. Not only does this cost retailers roughly of the original item price, but this amount of product returns also generates nearly annually-a huge, and unfortunately negative, environmental impact. 26% 66% 4.7 million metric tons of CO2 Brands are using AI to generate custom 3D avatars based on 2D photos, which can then be used to generate custom fit and sizing recommendations. The algorithm calculates over 86 measurement points when creating the avatar, helping brands like 1822 denim and Burlington Medical accurately measure its customers . reduce returns by 30% 7.5 times faster 2.  "Phygital" blockchain tracking The blending of physical and digital (dubbed "phygital") is in its early stages now, but it will likely be a vital component of the fashion landscape in the near future. In the reality of the metaverse, brands can design, manufacture and sell fashion in brand-new ways, which means that consumers can explore style and fashion in ways they never have before, including having a “phygital” wardrobe that consists of both a physical item and its digital twin within the virtual worlds. Phygital innovations include everything from using 3D body scans of real people to authentic metaverse humans to utilizing the blockchain to track the journey of an article of clothing by embedding an encrypted physical NFC tag, allowing buyers to see the item’s entire history with just their smartphone. One example of phygital fashion is the use of NFC tags to track the transparency of sourcing materials, and creation of garments via the blockchain. Fashion designers like do this not only to tell the story behind each piece but also to create a conversation around sustainability and ethics in fashion. Martina Spetlova Phygital tags are also a valuable asset for verification of the authenticity of designer or luxury fashion pieces. Counterfeiting has become a major problem in the fashion industry. According to various sources, anywhere from to 20 percent of fashion products on the market today are likely to be fakes. 10 On top of that, the global counterfeit goods market is estimated to be worth , which hurts consumers and retailers around the world. Allowing consumers to track an item's "life" through the blockchain helps curb counterfeiting and assures authenticity. $600 billion annually 3. Fashionable tech wearables Tech wearables aren't new, but fashionable ones that consumers want to wear every day are a relatively new idea. New fashion-tech hybrid collaborations are becoming more popular than ever and expanding beyond the well-known fitness trackers. For example, Levi's and Google teamed up to create a stylish, highly functional jacket, dubbed "Project Jacquard," for . The conductive technology needed to sync with a cyclist's smart device is undetectably woven into the fabric of the jacket, allowing users to control music, incoming calls, and navigation seamlessly while riding. urban cyclists Other companies like NADI X have created yoga pants with built-in digital sensors to help wearers correct their form and posture as they move through yoga poses. The sensors vibrate gently to help users perfect their poses while also offering step-by-step guidance and audio via a connected app. 4. Circular fashion The digital revolution has become a platform for champions of a circular economy to create new, innovative ways to help fashion lovers enjoy shopping more sustainably. Marketplaces like The Real Real allow users to buy and sell "pre-loved" luxury items like clothing, shoes, makeup, accessories, and more, while extensions like Faircado aggregate secondhand alternatives to items users are searching for online, helping lower consumption and spending. Additionally, some brands are opting to establish resale markets on their own, such as Oscar de la Renta’s Encore or H&M’s . Rewear Other apps like Storey help users "shop their stash." Storey claims that people don't wear at least half of their wardrobe, so the app aims to alleviate this by allowing users to create a "digital wardrobe" of their clothing for more visibility. It also has an "outfit recommender" that uses AI to create inspiration based on what's in your closet. The Fashion Landscape is Shifting, and Digital Trends are Taking Over The fashion industry has always been a creative, cutting-edge market full of free thinkers and innovators, so it's no surprise that it is embracing the digital revolution. From NFT wardrobes in the metaverse and blockchain tracking to augmented reality shopping experiences and digitally enhanced physical clothing, we are sure to see an even more significant and more exciting transformation happen in fashion over the next few years.

The Future of Style: How Digital Innovations are Transforming Fashion 

https://www.youtube.com/watch?v=9RDY0KA8YeA?embedable=true CSS has a lot of different units that you can choose from. In many cases, there is one unit that’s clearly better than any others. However, one question that seems to have come up a lot throughout my career is whether you should use pixels or rems on certain properties where it doesn’t seem to make a clear difference. Today I’m going to answer that question. The Setup Let’s say we have a very basic page with two paragraphs: one sized with pixels and the other with rems: HTML <!DOCTYPE html>
<html>
<body>
 <h1>PX vs. Rem</h1>
 My font size is 24px
 My font-size is 1.5rem
</body>
</html> Pixels are an absolute unit, so when you set the font size to 24 pixels, it’s going to be 24 pixels. Rems, on the other hand, are relative units that are based on the document’s font size. The document’s default font size is 16 pixels, so 1.5rems x 16px is the equivalent of 24 pixels. The fact that rems are relative and they’re based on a default of 16 pixels makes them harder to work with than pixels. This is why, more often than not, I see folks using pixels. But I think it’s a mistake. The Not-so-real Problem In the past, there was some confusion around how or high-density displays affected pixels and . Without getting too far into it, there was a moment when pixels scaled weirdly, but that issue has since been fixed. And since that has been fixed, an argument I keep seeing is that users can scale the font size up and down by zooming the browser in or out, and both the pixel and rem sizes grow at the same rate. As a result, some folks say that it no longer matters whether you use pixels or rems. retina pixel density But it does! The Real-real Problem This issue actually relates to how CSS units respond to browser settings. Users can go to their browser settings and modify the browser’s default font size. This is great for users that have a visual impairment. However, if you check the browser, the paragraph with the absolute unit of 24 pixels will remain at 24 pixels the same regardless of what the user’s preference is. The relative unit, on the other hand, grows with the default settings of the browser. So this is really an accessibility concern. Therefore, any time you’re defining font sizes, you should absolutely (or relatively?) use rems. The Nuance Of course, because we’re talking web development, the discussion is nuanced. For example, what about other properties like padding and border? <!DOCTYPE html>
<html>
<body>
 <h1>PX vs. Rem</h1>
 
 My font size is 24px
 
 
 My font-size is 1.5rem
 
</body>
</html> In this example, we’ll compare pixels vs. rems for padding and border width in addition to font size. As you might expect, the second paragraph has larger padding and border width in addition to the larger font size because rem units scale up with the browser settings. And this brings us to the “it depends” of the conversation. Padding and border width are not really strictly related to accessibility. So, do you want your padding or border width - or any other property that could otherwise be pixels - to be set with rems and scale up if the user changes their settings? That’s up to you ¯\ /¯ (ツ) It gets even more confusing when you introduce media queries or container queries. It’s very complicated to explain, but basically, if your fonts scale up with the browser settings, you probably also want your media queries to respond in kind. This means you should define them with REM (or EM) units. Of course, there are a lot of factors that play in there and I don’t want to get too lost in the weeds. Fortunately, there was an article in 2016 that basically tackled that question called “ ” by Zell Liew. PX, EM or REM media queries It basically concluded by saying that EM units and REM units are going to be better for media queries than pixel units and because EM units are based on their parent element, but media queries affect the root styles, both EM and REM are pretty much the same. The only difference was due to a bug in Safari with REM units, therefore EM was a little bit more consistent than, but I think that bug has been fixed. So I would just stick to using REM. The Short(ish) Answer So to answer the question, once and for all, whether you should use pixels or rems, the short answer is… ! Just use rems Of course, there’s nuance. Of course, there are exceptions. Of course, there will be cases in which pixels actually better. are (You should test your application with various browser settings to make those calls). really BUT Rems are more accessible for font size. Rems are (probably) better for media queries. And I think it’s easier to just stick to one simple rule (with occasional exceptions) than it is to mix things. At the end of the day, it all depends on how things should scale based on the user’s browser settings, so it may not matter all that much to you. But it makes sense to me that everything scales up or down at the same rate. If you feel different or you would like to contribute to the conversation, I would love to hear your thoughts. Thank you so much for reading. If you liked this article, please . It's one of the best ways to support me. You can also or if you want to know when new articles are published. share it sign up for my newsletter follow me on Twitter Originally published here.

Just Use Rem: Choosing between Pixels and Rems in CSS

The Metaverse is becoming a reality faster than ever before, and soon enough, it will be a place for all of us to and earn money as well! Billions of dollars worth of investments are being poured into various different Metaverse projects, with almost every company trying to come up with their Metaverse. There are a whole bunch of potential job opportunities that are gonna pop up in the Metaverse, and in this article, I’ll be taking a look at some of the most exciting ones.  So, let’s take a look at some of the top possible future jobs in the Metaverse! work own What is the Metaverse? Before I move on to what sort of jobs you can have in the Metaverse, it’s important to understand what the Metaverse really even is. The Metaverse is considered the next big evolution that the internet will go through. Some also refer to it as Web3, while others consider that to be a different thing. Regardless, ‘The Metaverse’ is going to be the most immersive internet experience ever. According to the Coin Market Cap, Metaverse is going to be a $13 Trillion market by 2030 with over 5 billion users. Instead of having web pages, applications, and other things like that, there are going to be “spaces”. You can be virtually present inside these spaces and feel like you’re there with the help of VR and AR technologies. Another thing about these spaces is that you’ll be able to them in the form of NFTs. These NFTs can represent virtual lands, houses, clothes, items, and pretty much any sort of thing within the Metaverse. You could own your own house, live in it, sell it for a profit, and do so much more. It’s sort of like a recreation of real life on the internet. own Now, there are a lot of different you can have in the Metaverse as well, let’s take a look at what some of those are: jobs 1. Real Estate Jobs Real estate is one of the most obvious ways that you can make money in the Metaverse. If you take Decentraland, one of the most popular Metaverse platforms out there right now, as an example, you’ll know exactly why. Decentraland is an entire world with a limited number of land plots people can buy in the form of NFTs. On these plots, users can build almost anything they want, whether it’s a house, park, concert venue, billboard, or anything that you could possibly think of. Now, every single NFT holds value, and they can be to other people. As more and more people buy up plots in Decentraland, the higher the value of each individual plot is going to be because of its limited number. On top of that, all of the “cooler” plots with actual construction on them are going to be worth a lot more than just empty plots. This has paved the way for a real estate industry that works in almost the exact same way as it does in the real world. A lot of people could earn a lot of money from just buying and selling Metaverse properties, and on top of that, there could even be real estate agents within this world, opening up job opportunities for so many people. transferred Recently a plot of land was sold at $2.4 million, which is pretty much as expensive as real life. So, the sooner you get into this, you can make a lot of money, and you can make a career. For example, you can become a real estate agent, open your own agency in the metaverse and buy and sell lands and properties just like you do in real life. I know it is kind of unreal, but the future is all about virtual worlds and the metaverse. 2. Fashion Industry Jobs The fashion industry in the Metaverse is also going to be . Think about it, everyone in the Metaverse is going to have their own avatar who is going to represent them. That avatar is going to wear clothes and accessories, all of which will be NFTs. There are going to be a lot of different brands you could potentially buy outfits from. massive There are already certain brands that are present in the Metaverse, such as Nike, Louis Vuitton, and Gucci. These brands have opened up their own virtual Metaverse stores, where people can go and shop for virtual items. You’re probably wondering — why are people spending money on items that are completely cosmetic? Well, it isn’t anything new. Just take a look at any free-to-play game out there like Fortnite or Apex Legends. virtual In both of these games, you have the ability to buy cosmetic items like skins that bring no change to your gameplay, and you actually have to pay real money to do so. The Metaverse will be similar, but you could even these items yourself. Even on Snapchat, you can customize your avatar using designs from famous fashion brands like Ralph Lauren and Nike. sell Metaverse is going to have fashion designers and event planners. retail workers, stylists, and so many other jobs that are directly related to the fashion industry itself. The global fashion industry is already worth of dollars, and its launch into the Metaverse is just something that will definitely become more active. trillions 3. Influencers and Celebrities Another thing about Metaverse avatars is that some of them are going to be more popular than others. This can and eventually lead to the creation of Metaverse celebrities and influencers. Fans following fictional or virtual characters are nothing new at all, and it’s only a matter of time before it happens in the Metaverse as well. will It’s likely that Metaverse influencers will be directly tied to the fashion industry as well, and they’re always going to be the “trendsetters”, wearing all the latest trends and influencing fashion across platforms. Of course, just like in the real world, these influencers will be able to monetize their fame as well. They could do brand deals, advertisements, paid events, and so much more. It’s difficult to predict what it’s going to actually be like for Metaverse influencers, but it’s almost certain that they going to be a thing. are 4. Event Management Another thing about the Metaverse is that it’s going to have a lot of . As I mentioned, certain Metaverse influencers will hold events to meet up with their fans, just like influencers will do in the real world. There are going to be virtual performances, expos, and so many other things. Imagine the Dubai Expo taking place in the Metaverse! Something like that going to be a possibility very soon. In fact, certain celebrities like Snoop Dogg have already held virtual concerts inside the Metaverse. All of the attendees actually had to to attend this concert, and guess what? It got . There’s a very clear market for this, and it’s all backed by money. events is pay sold out real Because of this, there will also be the need for Metaverse event planners. Just like in the real world, there, event planners and managers will be needed for every event that is held there. There will eventually even come a time when companies like Apple announce their newest devices in the Metaverse, other events like E3 and Comic-Con might also move to the Metaverse, and all of the jobs that these events usually create are going to move to the Metaverse. Virtual jobs are already a thing, and the Metaverse is going to enhance their capabilities and scope. also 5. Architecture and Design This is another “industry” that is going to be directly related to the fact that you can own assets in the Metaverse. If you’re going to make a building or any sort on the piece of land that you virtually own, you can’t just do it all by yourself. Just like in the real world, you’re going to require the help of architects and designers. These jobs are going to play an important role in making the Metaverse actually look good. There’s no doubt that a lot of companies would be willing to pay some big bucks to architects and designers to make their buildings look better than anyone else. extremely There are even more jobs, such as interior designers, that will be required in the Metaverse once it becomes more mature in age. It’s not likely that these jobs are going to be “big” in the Metaverse early on, but those of us who can the market is probably gonna be set for . capture life 6. Advertising What’s the one thing that makes the internet more money than anything else in the world? Advertising. You might know Google as a search engine, the owner of Gmail, and YouTube, but Google is primarily an company. That’s the reason why it’s valued at almost a dollars. The Metaverse is pretty much for advertisement. There are going to be jobs in the Metaverse to not only create advertisements, but also to manage them, display them, and so much more. advertising trillion primed Eventually, there will be entire companies entirely the Metaverse where the sole purpose will be to create ads and earn money. These companies are going to bring a lot of jobs with them, just like how Google employs thousands of people around the world. Once again, the exact scale of this can’t be predicted, but it’s something that happen. within will Other Jobs There will also probably be a lot of other jobs in the Metaverse beyond some of the big ones I mentioned in this article. For example, there will likely be a lot of tech-related jobs, finance-related jobs, aviation, tourism, and other kinds of jobs in the Metaverse as well, along with some basic jobs that we do every day in the real world. At the end of the day, the Metaverse will become a reality sooner or later, and we don’t fully know all the kinds of jobs that Metaverse will create, but it’s going to be exciting to see it turn into a reality. new Do you think the average person will be making a lot of money in the Metaverse? Let me know in the comments below! Stay informed by visiting my YouTube Channel https://bit.ly/3720zFW

Top 6 Jobs in the Metaverse

2020 has been quite challenging for a lot of people. When the year started, the COVID-19 pandemic hit, and the majority of nations went into lockdown, which caused the global economy to plunge. A number of important industries have been negatively affected, and one of the sectors that suffered the most was the real estate space. A new report from the Urban Land Institute and PwC dubbed “ ” states that the COVID-19 is not done with the real estate market. In fact, it is expected that the coronavirus will cause some major changes in the way property is used, bought, and sold. Emerging Trends in Real Estate 2021 Now, when we look at the virtual real estate market, we see a completely opposite trend. Back in February 2020, crypto enthusiasts and the gaming community had collectively invested close to $1 million worth of fiat money into virtual land in just one week. At that time, the three largest virtual world games, , , and saw a total trading volume of their digital tokens surpass $940,000 USD, according to . The Sandbox Cryptovoxels Decentraland Nonfungible The cause of such popularity and value increase was reportedly promoted by a big virtual sale of land that took place in The Sandbox. At that time, the blockchain-fueled virtual world was selling around 7% of its land in its second land sale. In one week, the project saw $168,000 in land sales and registered 6,000 users. With things changing rapidly in the world, is it possible we might see virtual real estate take over the “real” real estate? Let’s discuss this. Virtual Land vs Real Estate: What Is the Difference? Real estate refers to the land, property, buildings, and air rights that are located above the land, as well as it includes the underground rights below the land. Real estate is a term that involves physical, tangible property. In other words, real estate refers to what you can see and touch. You can relax in your apartment, invest in the real estate market seeking profits, or rent your grandma’s old cottage. are the real estate of the virtual world – they represent the three-dimensional virtual world space. When users buy a piece of virtual land, they get a right to use the property however they please. We’ll touch on this topic a bit later. Virtual lands While the functions of virtual real estate are pretty much the same, there is one key distinction. Yes, you guessed it – it is not real, you can’t see or touch it. However, this does not mean you can’t enjoy it or that it does not have value. Quite the opposite – at the moment, virtual lands are rising in value and people are ready to pay big bucks for it. When it comes to pricing in the virtual estate market, it is still far away from that of the real world estate market. While the prices differ from country to country, if we take the US housing marketing as an example, the for a square foot to buy a home in New York’s Manhattan stands at $1,376. In contrast, a 1,100 square foot plot in the virtual world can be sold for $200,000 on Decentraland. average price Just like with any blockchain-fueled exchange, the value of the asset is determined by limited supply and increased demand. With virtual lands, there is a set amount of land produced – and it is usually gone before you know it. In fact, we are seeing a positive trend in the valuation of virtual lands. Just like that, a lot of big players in the industry are pouring their money into the digital land. For instance, one of the leading cryptocurrency exchanges, Binance, that it has purchased 4,012 LAND NFTs in The Sandbox. announced Source: https://nonfungible.com/ After The Sandbox metaverse saw an increase in demand for its LAND, the prices started climbing. In one of his latest Tweets, Sebastien Borget, the co-founder of the project, mentioned that The Sandbox ecosystem saw the sale of two estates at 210 ETH ~ $76,931 USD (28x original price of $1,400 each). What is the Use of Virtual Land? Real estate uses in the real world are obvious and easily understandable for the majority of us. We use real lands to build property, we live in apartments, we invest in the real estate market and we use the property for retail purposes. But when it comes to virtual land use, many people are confused – what am I going to do with it? Well, first of all, one of the key factors that attract thousands of investors to the virtual real estate market is the chance to “flip” the land. In other words, they are purchasing virtual land when it is still priced relatively low and then adopt a “wait-and-see” approach, until the price of that land rises to the point where they’d want to sell it. In addition, just like with real property, users can sell and rent their virtual property. They can build things on top of their lands, such as shops and malls, or run business enterprises. In fact, many claim that the virtual reality world is just as “real” as our world – thanks to great technologies and amazing graphics these virtual worlds employ, people are able to immerse themselves into a completely different dimension. Additionally, the virtual reality world allows users not just to be consumers, but also to be creators. Users can produce their own unique creations in these virtual worlds and sell them. The new vertical of the economy is potentially opening up in virtual reality and it attracts a lot of gaming enthusiasts and innovative entrepreneurs. How To Get a Piece Of Virtual Land? Now, when everyone is familiar with the process of purchasing real estate in the real world, how does one get his hands on a piece of property in the virtual world? While the exact processes of purchasing a virtual land vary from platform to platform, the overall steps are usually similar. Let’s take a look at the example of how one would get a LAND on The Sandbox metaverse. A LAND is a piece of the digital estate in The Sandbox virtual ecosystem that allows users to build various experiences on top of it. For instance, players can populate it with Assets and Games. A LAND is a non-fungible token built on the Ethereum blockchain (ERC-721). The first-ever presale of LAND on The Sandbox metaverse took place back in December 2019 – all the LANDs were gone in a few hours. Source: https://medium.com/sandbox-game Now, with The that takes place on November 12th, 2020, users still got the chance to get their hands on these digital properties. According to the from The Sandbox, users are able to purchase LAND by following four steps: Sandbox’s upcoming LAND Presale guide 1. Set up the digital currency wallet A user would need to create an account on The Sandbox’s website and connect a cryptocurrency wallet to it. Once the LAND is purchased, it will be stored in this digital currency wallet. 2. Buy $SAND and $ETH Once the user has set up the wallet, he/she needs to purchase $SAND and $ETH tokens. This can be done in a variety of ways, but the most common one would be to get tokens from a cryptocurrency exchange. 3. Transfer $SAND tokens to The Sandbox account Then, tokens would need to be sent to the user’s Sandbox account. The process is relatively simple and requires just 4 steps, according to the guide from the Sandbox. 4. Buy LAND on The Sandbox map Now, the user will be able to purchase LAND. In order to be able to buy LAND, the user would also need to have $ETH in his wallet to cover the transaction fees associated with the Ethereum blockchain network. Once ready, the user should go to , and choose among the available LAND parcels. Users will be able to see the information about the LAND’s size, location, blocks included, and its price. https://www.sandbox.game/en/land/ When the user has decided upon the desirable land, he/she would need to click on the “Buy LAND” button and complete the transaction via wallet. Conclusion Buying and owning property has long been seen as one of the most successful investment strategies. Yet, as we see the world going more digital, a unique new type of the real estate industry is emerging thanks to the developments of the Virtual Reality. While virtual worlds and lands are still at the very nascent stage, we’ve seen a growing interest from major investors and organizations toward this industry. In addition, the VR community has been working tirelessly on the research and advancements of the new virtual world concepts and we might just see the virtual land gain more momentum during the coming years. Some enthusiasts even predict that commercial brands might tap into the virtual worlds to promote their products. Just like the big brands are using the opportunity to push their services and products at football matches or music concerts, the same might apply to virtual reality events.

Real Estate vs Virtual Lands: New Verticals of a Global Economy

Wise, the leading embedded banking FinTech, that offers business banking via partnerships, announced today that it has closed a $12M Series A. This funding round was led by e.ventures, with participation from Grishin Robotics, and with continued investment from seed investors – Base10 Partners and Tech Stars. Six months after a $5.7M seed round, Wise raised the Series A funding to accelerate growth and partnerships across several verticals and to extend its breakthrough technology to support a fully-managed, first-of-its-kind embedded banking experience. Wise has raised $18M to date. "We built banking so our partners don't have to," said Arjun Thyagarajan, Co-Founder and CEO at Wise. "By embedding banking, Wise unlocks deep product offerings and better customer experiences for our partners. e.ventures built a thesis on exactly this, and we agree 100%." "Business banking has been broken for far too long. Poor user interfaces, payments delays, unnecessary fees, a lack of integrations, the list goes on and on," said Brendan Wales, Partner at e.ventures. "The team at Wise is bringing an Apple-like experience to the world of business banking with an embedded product that brings banking to where one’s business is managed." In addition to this round, Wise has also signed several new partnerships, where leading B2B companies are able to seamlessly offer banking, within their product experience, greatly expanding the value to their business customers. "In a world where more people are working remotely than ever before, it is important for RemoteTeam to provide its customers with a modern, instant payroll experience. Embedding banking solves a major pain point that makes RemoteTeam a standout offering in the payroll industry," says Sahin Boydas, CEO at RemoteTeam and a Wise partner. "Embedded experiences drive product engagement through the roof! It is a win-win-win proposition for everyone involved – Wise, its partner, and the small business that lives inside the partner ecosystem," said Raghav Lal, President at Wise. Prior to joining Wise, Lal launched several successful co-branded partnerships at AMEX and VISA. Before Wise, launching a banking offering could take months or in some cases, years. Now, SaaS B2B companies launch banking powered by Wise, with no-code and in just a few days – with the entire program managed and serviced by Wise. "We’re thrilled by Wise’s continued progress developing strategic partnerships with large SaaS partners," added Rexhi Dollaku, Principal at Base10 Partners. "This funding will accelerate Wise’s product and go-to-market efforts, so that they can continue to redefine the business banking experience for many more real economy businesses." Founded in December 2018, Wise is a Techstars NYC company headquartered in San Mateo, CA. Wise offers modern businesses a seamless way to bank, pay, and get paid. Wise embeds its all-in-one business banking product via partnerships. For more information, visit wise.us. About Wise Founded in 1999, e.ventures is the first tech-enabled global venture capital firm and invests in consumer and software companies at their inflection points from early to growth stage. The firm is headquartered in San Francisco and Berlin with global partners in Beijing, Tokyo, and São Paulo. e.ventures has combined its extensive, truly global network with local experience and insight to partner with over 250 startups globally. Notable US investments include Segment, Sonos, Appfolio, AngiesList, TheRealReal, GoPuff, Shipt, NGINX, and Acorns. About e.ventures Base10 is a San Francisco-based early-stage venture firm investing in Automation for the Real Economy. Founded by Adeyemi Ajao and TJ Nahigian, the firm invests in technology companies that are bringing automation to sectors of the Real Economy, including industrial logistics, consumer logistics, restaurants, financial services, and sales & customer service. Portfolio companies include ThePillClub, Virtual Kitchen Company, Acquire, PopMenu, and others. Connect via base10.vc. About Base10 Media Contact Amber Moore GMK Communications amber@gmkcommunications.com 503.943.9381

[Announcement] Wise Raises $12M To Accelerate Embedded Banking Partnerships

Thread: We all know managed marketplaces (where the platform provides additional value-add in terms of intermediating the service delivery) can create a step-function improvement in user experience, but despite that, they can actually struggle to scale as businesses. Examples of the functions that managed marketplaces often take on include vetting providers, handling logistics, or authenticating goods. This translates into a much better user experience, but can also mean greater operational overhead, lower margins, and difficulty growing. The complexity of intermediating the transaction is not trivial. Consider Beepi–a managed marketplace for used cars–which created an amazing user experience (90+ NPS), but ultimately shut down due to challenges becoming unit economic profitable in many markets. For Beepi, the costs associated with each transaction included rigorous inspections, free returns, delivery, and a guarantee to buy the car if it didn’t sell within a certain time frame. In categories where services are viewed by users as commodities and/or users are especially price-sensitive, the open version of a marketplace often wins out over more managed versions. For example, Craigslist and Thumbtack are much bigger businesses than marketplaces that have attempted to employ home services pros themselves and own the end-to-end experience. But for more emotional categories that are more ongoing in nature or  have variable outcomes, where each provider is meaningfully different, and the stakes or $ values are higher, the managed version often does better than the unmanaged version. Here’s some examples where managed marketplaces have gained ground: Uber (more managed w/ centralized matching and pricing) vs. Sidecar (double opt in, no centralized pricing) Lambda School (managed) vs. open MOOC platforms Rover vs. finding a dog walker on CL/via WOM TheRealReal vs. unmanaged consignment marketplaces What do these managed marketplace companies have in common? Focus on a service category where users value the experience differential and are willing to pay a premium that offsets increased costs Building software to improve efficiency Focus on high AOV & high frequency Another factor to consider is that labor/service marketplaces typically have more overhead than product marketplaces in terms of management. That’s because every aspect of a service can be managed end-to-end, and there’s frequently a geo-specific aspect to the overhead, vs. a product marketplace can just manage specific aspects of the transaction (validation, logistics) – much of which can be outsourced / centralized. With any unmanaged marketplace, there’s going to be variance in quality. For categories where there’s less tolerance for uncertain quality/experience and desire for more consistency/certainty, a managed approach can win out. For founders, the key is finding a way to provide a more delightful, managed experience where it matters, but doing so scalably, leveraging software. For instance, designer goods marketplaces can reduce the # of items needing manual authentication by predicting which items are most likely to be fake. In addition, validate that you can charge higher prices or increase take rate to cover the costs of managing the marketplace. TL;DR: Managed marketplaces can create a step-function improvement is user experience, but they can be complicated to operate & challenging to scale. There’s a number of factors to consider in whether to go unmanaged vs. managed, and to what degree. For more on managed marketplaces, see our blog post: https://a16z.com/2018/11/27/services-marketplaces-service-economy-evolution-whats-next/ Originally published as “ Pros and Cons of Managed Marketplaces "

Pros and Cons of Running a Managed Marketplace

During Hackers Congress Paralelni Polis (HCPP), I had a chance to interview Harry Halpin on AI, surveillance, collective intelligence and his latest project NYM. About Harry Halpin: Harry Halpin’s work is a unique blend of computer science, philosophy and ethics. Previously working at World Wide Web Consortium (W3C), he resigned after the W3C standards body standardized the Digital Rights Management (DRM). Harry is a strong advocate of open and unrestricted web and strong user privacy. His latest project is called NYM, which aims to introduce a mix network protocol with blockchain-enabled incentivization for sustainability. Motivating my work is the clear and present need to create an ethical foundation for the future technologies that enable fully realized and autonomous humans whose capabilities are extended by technology, rather than subservient to it. Harry Halpin's bio The Interview Some time ago you said on Twitter that AI is a bankrupt intellectual programme. What’s the idea behind that? KryptoJoseph (KJ): The question of artificial intelligence is a very old desire of humans to create forms of life that have the same properties as ourselves, or possibly even superior to ourselves. Harry Halpin (HH): The main problem with artificial intelligence is that it takes a very impoverished view of intelligence in the form of narrow problem solving, like identifying certain objects. More than intelligence itself, it relates to optimizing problems and finding efficient solutions to given problems. As has been pointed out by and other philosophers, the world is not partitioned to a set of discrete problems. Hubert Dreyfus World is a continuous flux that we have to make sense out of. This ability to make sense out of things autonomously in an open-ended system is really what defines intelligence and this aspect has been historically ignored by AI programs. Deep learning isn’t a magical shortcut to solve it. All that deep learning does is it takes the symbols of feature set for a given machine learning problem from lower level features. But that means the problem to solve has already been predetermined. This question of autonomy really I think reveals how bankrupt artificial intelligence is as an intellectual project insofar if anything, the project should be about how we as humans think and what is the nature of autonomy and self-determination. And these largely philosophical questions are barely touched by artificial intelligence research. So artificial intelligence as a program, while everyone is excited about it and tends to give it magical powers, is nothing more than efficiently solving problems and a straightforward extension of the industrial revolution, and an ability to solve certain kinds of problems with new kinds of machinery. I don’t think it’s a giant threat to human existence or on the other hand a giant boon to human prosperity. I’m deeply skeptical of any large impacts of artificial intelligence in the near future. Taylorism The danger of artificial intelligence lies in it acting as a distraction from the real fundamental problems that humanity is facing, like surveillance, control, climate change, economic collapse, social disorders. The ancient fantasy of creating a thinking machine is just that - a fantasy to distract people from the real problems we collectively face. KJ: In The Philosophy of Anonymous , you wrote: “Is it not ironic that the once idealistically lauded open-source software, thought to be a tool of freedom, now runs massive centralized server farms that provide the foundation for the most sophisticated regime of surveillance ever imagined?” Is narrow AI a tool for increasing the efficiency of mass surveillance? Artificial intelligence and surveillance have an intimate connection, particularly when it comes to machine learning. In order to have a relatively dumb algorithm appear intelligent, it has to be trained with a large amount of data. This data needs to be collected and processed, which basically requires surveillance - large data collection. The more data you can collect, the more effective and intelligent these algorithms appear - but I’d like to emphasize the word appear since the algorithms aren’t actually intelligent in a way that living things are intelligent. Since we don’t have a satisfactory theory in place on what constitutes intelligence, the best that machines can do is to pretend they are intelligent by exploiting large amounts of data to do essentially non-linear function fitting over predetermined objective functions. And that simply does require mass surveillance. HH: One problem the artificial intelligence could potentially solve is a problem of production - how to produce stuff in more efficient ways. But when there is no market for such algorithms, machine learning is naturally repurposed for social control, because the state will always want to buy machine learning algorithms to monitor its citizens, to make sure people will continue to exist in a way which is subservient to the state’s needs. While there is a huge movement by researchers trying to understand how they can eliminate bias and discrimination in AI, the real question is how we can eliminate surveillance and preserve freedom. And I think on that level, the obsession with AI has set back the computer science research. First of all, many people who don’t know much about AI get very excited about it. Anyone who has worked in the field and knows linear algebra ran some Bayesian classifiers and quickly understood the limits of artificial intelligence. Second, after Snowden’s revelations there began an emphasis in computer science on fighting surveillance, preserving privacy and building tools that enhance freedom, but unfortunately, this rhetoric, which naturally is anti-state, has been absorbed by a “fair” artificial intelligence crowd which essentially says “how can we be fairly spied upon? How can AI facial recognition recognize black faces as well as white faces?” But I don’t want to live in a world where AI-aided surveillance is considered normal and mandatory, and fairness is understood as being equally well observed. I’d rather live in a world where we’re not observed and controlled. So again, AI and the rhetoric surrounding it is a distraction from the real problem. KJ: In your work you sometimes juxtapose artificial intelligence and collective intelligence . Could you explain what is collective intelligence? Collective intelligence is, I think, a much better concept than artificial intelligence. It explores how humans and machines can enhance each other’s intelligence. Humans are very good at making sense of the world and making autonomous decisions, but humans have natural problems with memory, recall and processing large amounts of data - areas that machines are very good at. HH: Collective intelligence imagines a symbiotic and mutually beneficial relationship between humans and machines. There are different kinds of humans with different qualities and the same applies to machines, and the question is of the correct ensemble of humans and machines. I think this is a much better way of looking at intelligence and also a more individual-based take on artificial intelligence. All humans exist and act within society and our intelligence is to a large degree social; it’s dependent on a culture we come from, on people in our wider milieu. Thus collective intelligence makes much more sense as a way of extending our intelligence than hoping that we can be replaced by some kind of Roomba-style robot slaves. KJ: That reminds me of the vision for the semantic web. Semantic web, although pretty much a failed project now, is pretty interesting as it imagined we could get machines to process data in a way that is decentralized and thus extend our knowledge. The decentralized nature of Tim Berners-Lee’s vision of the semantic web is very admirable. That being said, giving every single piece of data an identifier in a reliable way is unworkable with original web technology. I am quite a fan of blockchain in this respect, as it offers some level of decentralization and cryptography and thus provides a better bedrock for social computing than the traditional web. HH: I’ve mostly moved on from my research of semantic web, as it’s only been used by large corporations for knowledge graphs and surveillance. KJ: Let’s talk about your project NYM. Could you describe what’s it about? NYM is the latest attempt to build a technology that could really defeat mass surveillance. TOR has been the best technology in this regard for the last 15 years but the problem with TOR is that while it does obscure geolocation by obscuring IPs, it assumes the adversary cannot watch the entire network and cannot correlate traffic between entry and exit points. These kinds of attacks, as we know from the NSA revelations, are possible. Early attacks focused on breaking the TOR browser, but today we know there are massive amounts of data collected and stored through mass surveillance. So it makes sense that NSA simply watches all the TOR entry and exit nodes, stores and correlates the data. You can correlate the data via the time the data was sent and the size of the data, from which you derive what’s called the patterns of data. Machine learning processes data automatically find out these patterns and deanonymizes TOR users. HH: NYM uses a combination of mix networking - mixing real data with fake cover data and time delays - and an incentive system using blockchain technology. I believe this combination of technology is actually resistant to NSA-level surveillance and therefore is something we need to desperately put out to the world ASAP. KJ: It seems to me that the incentivization was the missing element all this time - it simply didn’t pay off to be a TOR exit node and bear the risk. Do you think that’s it, that the ability do incentivize the infrastructure providers in a decentralized way is what we need to build the privacy-preserving network? Altruism definitely has its limits. It’s very hard to imagine many people in developing countries running TOR nodes simply out of altruism. The incentive structure is a way to get people to run nodes, but NYM is much more than that. TOR is a routing system, NYM is a mixnet. Mixnets are built for asynchronous messaging, not synchronous circuits like TOR. Unlike TOR, mixnets are resistant against global passive adversaries such as NSA or Chainalysis. HH: But yes, incentives play a huge role. If we didn’t use incentives, we would have to rely on the same kind of people that currently run TOR nodes - and why would they switch to something else? With incentives, we should see a market for running a decentralized privacy network emerge that attracts a much larger group of people than current TOR node operators. KJ: What is the path to adoption for mixnets like NYM? Who do you see as the early adopters? You always will start with a crowd who is more sensitive to the problem, so privacy extremists are the first developers for such projects. Since it’s incentive-based, we imagine cryptocurrency enthusiasts and blockchain hackers are the first early adopters. But of course the larger the user base, the better the privacy benefits, so we need better user-friendly apps that go beyond cryptocurrency use cases. I think messaging is a super important application. Messaging provides a lot of cover traffic for privacy, for example for cryptocurrency transactions. We’ll also eventually be interested in more consumer-oriented markets such as VPN. That being said, these use cases are all very different. For example, the VPN will require more symmetric and faster traffic than the existing sphynx packets that are useful for asynchronous traffic like messaging and cryptocurrency transfers. So we want to do each of these use cases one at a time. HH: Watch Harry’s talk: Code is a Weapon“ at Hackers Congress 2019 . Check out project NYM . Follow Harry Halpin on Twitter . Follow KryptoJoseph on Twitter . Follow TopMonks on Twitter .

"AI is a Distraction" — Interview with Harry Halpin; CEO of NYM

A story about the enormously destructive power of this thing 👉* Gather 'round and let me tell you about that time my teammates and I took down one of the platform's most critical services. For the sake of narrative, I’ll name my coworkers S (senior) and M(middle), but I changed the dates and some of the technical details in an effort to keep it as anonymous as possible. T’was a lovely Thursday afternoon at the end of July, 2016. Weather was milder than the days before and my teammates and I had just moved into a new space in the office. Life was mostly good. The week before had passed without the presence of our most senior dev, S, but me and M had managed to complete some tasks on our own. Those changes had some pretty heavy stuff (new database fields, new endpoints) so we decided to wait for S's review before we merged them. Database changes and migration scripts In the meantime another dev reviewed the changes and mentioned that the operations in our scripts could be a lot of work for the database server and may keep it locked for a while. So he suggested some alternatives. migration If you don’t know what a database migration is, it’s a series of SQL scripts that — when executed sequentially — create the whole database schema from scratch (tables, columns, default values, constraints, etc.). Usually they run on every deployment, but only if there’s something new to apply––that is, a new migration file. We didn’t want to run our change as a migration because then it would be executed by our continuous integration system and completely out of our control. We had to run it manually. So first we sat down with a replica of the production database and started playing around with queries trying to find the most efficient alternative. This was a fun while, the 3 of us trying to guess what would happen when we ran each script line separately. Would it take long? Or run instantly? And why? Where should we set the default value to prevent new entries from breaking it? Showtime! It was 5 PM and we were finally happy with our query. It did everything in the right order and didn’t really lock down for very long. We sent a ticket to the infrastructure team to run it directly on our servers, since obviously we didn't have credentials for that. You’ll see in just a moment. exactly why Infra was diligent about this. They’re a busy bunch, it’s okay if they take a while to do stuff. But not this time, this time the ticket was closed before I could blink twice. really Everything seemed ok. It was almost the end of the day so we split into our own desks and finished some tasks. Some minutes later, a member of another team came by and asked me if we were changing stuff on because it was throwing some errors. This hit me like an ice-bucket-challenge: that feature Oh no, I mean, yes… we f***ed it up. Can you guess what happened? I know it’s harder to find omissions than to find mistakes, but I think you could be able to know what we needed to do (and didn’t) without knowing the service, the feature, or the query. If you do, scroll to the bottom and comment it, I’ll trust you’re not peeping below this photo 👇 Photo by on 胡 卓亨 Unsplash Alright, if you have no idea what could have happened, that’s OK too. I feel I should have known, because this happened locally during development like . And I had been starting a very similar feature on my own that day and dealing with the same error. a million times Ready for it? Reality hits hard We added the column in the database, This resulted in the backend not knowing WTF to do with it, and throwing errors on 😱 but we never merged the code that handled this new data. all GET requests Now, this might not have happened in some languages, which probably would have discarded the extra data and moved on. I shouldn't disclose any more information about this, but I’ll say that we were using a technology that’s not as about rogue database columns, it demands that you tell it how to handle everything it receives. chill Not merging the code wasn’t the problem though. Here’s when our little evil villain comes in: meet * 😈 malefic, echoing laughter See, all of our retrieval queries were using the * (known as an or ), to bring back every field that it finds. This was the day I learned . asterisk star this is a very very very bad idea If we had had a list of the fields to retrieve instead of * nothing bad would have happened. But we didn't. And all of us 3 knew it. It just slipped our minds 😰 The real, real problem OK but, we’re humans, right? We make mistakes. No-one can keep all of the codebases in a system in their working memory. This is why we have tests. Not because our code is fragile and error prone, but because our minds are. And it’s our minds that create the code. So the problem wasn’t really that we broke it. The problem was that . no alarms went off We had production tests, but they weren’t notifying anyone. We had error alarms in the logs, but they weren’t monitoring the thing that caused the most errors. We had end-to-end tests, but they were disabled and marked as “broken”. This is what was truly unacceptable 🍋 Epilogue Ultimately, though, it was a big opportunity for learning. You never learn as when you f*** up. That’s a lesson that never leaves you. as hard So, for you children out there, here’s my list of learnings from that day: use * in a query in your code. Even if you have to write all the column names, it's better like that. NEVER, I MEAN NEVER Be scared of database changes, may fear guide you into caution. When you introduce a database change, make sure all the code is already in place and that it can handle the previous db state, and the one after the change. Have happy-path tests in place on production for your critical features, working and notifying the right people. Test database changes as they are impacted and monitor the logs for a couple of minutes later (depending on the amount of traffic that you get). as soon Aaand brush your teeth before you go to sleep. 🙂 This is a story told by the less experienced and knowledgeable of its characters. If you have any input about it, to add to or correct what I say I would really enjoy reading it

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