A 31-year-old woman was shot as she made her way off a cruise ship early Saturday at Navy Pier, Chicago police said.

Woman shot while leaving cruise ship at Navy Pier: CPD

A woman was wounded in a shooting as she was leaving a cruise ship early Saturday at Navy Pier, according to officials.

Woman wounded in shooting as she was leaving cruise ship at Navy Pier

The agency is investigating whether the incident caused any contamination, noting that the vessel was carrying some 13,000 gallons of fuel and 250 gallons of lube oil. The ship, named Bonnie G ...

Coast Guard rescues 12 after cargo ship runs aground near Virgin Islands

The Severn hit shallow ground and broke on the western shoals of the Bruce Peninsula, while the Africa was lost with all 11 members of the crew on board. The wreck was discovered in June by Yvonne ...

A ship that sank on Lake Huron 128 years ago is found nearly intact off Ontario's Bruce Peninsula

Early voting will again be offered for the November general election. The voting will run from Oct. 28 through Nov. 5. The interest in early voting "is really kind of hard to measure," said Monroe ...

Early voting starts Oct. 28 in Monroe County. Here's what you need to know.

A Royal Caribbean International cruise ship helped evacuate U.S. nationals from Israel on Monday. The line’s Rhapsody of the Seas vessel had been sailing in the region but canceled its ...

Royal Caribbean cruise ship evacuated Americans from Israel

A new blood test could help diagnose cancer cases earlier. Researchers from the University of Southern California (USC) developed a blood test to detect early onset ovarian cancer. The test ...

Ovarian cancer could be detected early with a new blood test, study finds

Swifties won’t have to wait until the end of the week to watch Taylor Swift ’s highly anticipated Eras Tour concert film, as the superstar revealed on Wednesday (Oct. 11) that the movie will ...

Taylor Swift’s ‘Eras Tour’ Film to Open Early ‘Due to Unprecedented Demand’

PORTLAND, Maine (WGME) — Officials say a crew member was burned after an explosion in the engine room of a cruise ship in Portland, Maine, on Wednesday. Portland Fire Department Chief Keith ...

Crew member burned following explosion on cruise ship in Maine

ShipEarly

shipearly

Early Bitcoin and Ethereum investors have earned significant profits on their coins. All they needed to do was tinker around with new tech, learn how to mine, or just use the first dApps that were rewarding their users with free coins. Today, Bitcoin is over a decade old and Ethereum has already lived through its best years. In this environment, everyone’s now asking “Who’s next?” Well, the answer to this is what tech-enthusiasts like to call Blockchain 3.0! In this article, we’re going to discuss the and analyze why it’s one of the most promising technologies today, and what projects were developed on it in 2020. Cosmos network Cosmos is not a blockchain. Cosmos is a decentralized network of independent parallel blockchains, each powered by BFT consensus algorithms, such as the Tendermint consensus. Being an ecosystem of multiple blockchains, the network can scale up to meet the current traffic needs. As such, project developers won’t have to worry about scalability anymore. If the decentralization market faces mainstream adoption, every dApp built on the Cosmos network will be ready for it. Bitcoin and Ehtereum are both following an old isolated architecture. Bitcoin was the first public blockchain that introduced the Proof-of-Work (PoW) mechanism. Ethereum offered the possibility to build decentralized applications on top of this, so having one blockchain to sustain all of the traffic is not currently possible. That’s why Ethereum has seen network congestion. Blockchain manifests itself differently, however; instead of going down like traditional servers, it just becomes slow and very expensive to use. Beyond this, we can’t even talk about other blockchains, as the most popular ones are either a fork of one of the codebases built on top of these blockchains or are simply in an experimental phase. Plus, the scalability limitations are not specific to Ethereum but to all protocols that use a single blockchain. Cosmos is making blockchain interoperable. You can see their vision as creating an “Internet of blockchains” in which the individual networks can communicate with each other in a decentralized way. Being part of the same ecosystem, Cosmos can guarantee that the transactions are quickly processed and blockchains can maintain sovereignty. The team made it easy for developers of any kind to build their project on top of the Cosmos network. Open-source tools like Tendermint, the Cosmos SDK, and IBC (Inter-Blockchain Communications Protocol) are publicly available to connect and interact with the Cosmos blockchains. This ecosystem is growing fast with new projects joining the network and building decentralized applications ready to use right from day one. Let’s discover a few of these projects that were started in 2020! TomiEx Exchange is a new-generation cryptocurrency exchange whose coin TEX is based on the Cosmos blockchain. The exchange is using the innovative Proof-of-Stake (PoS) technology to reward members for supporting the community. TomiEx The project issued a symbolic coin called TEX and imposed a strict limit of 575,000,000 TEX coins. TEX is developed using the Cosmos-SDK framework, which made it easy for the team to implement the PoS algorithm securely. With PoS, the TomiEx exchange has a built-in marketing tool to attract new users. As soon as the number of unique users reaches 200,000, the PoS technology will be suspended and a reverse mechanism for burning token emissions will be activated. The number of burned tokens will be determined by the number of users. If fewer users are using the exchange, more tokens will be burnt. If the number of users goes up again, the coin issuance will continue. The exchange economy is essentially governed by the PoS algorithm. The whole mechanism won’t be possible without the Cosmos ecosystem. Cosmos is using the PoS method which makes the consensus mechanism completely virtual. We are talking about 200,000 unique users on a single blockchain. That is not possible on any other blockchain protocol. Cosmos is making it possible and TEX holders can be assured in knowing that they will receive their daily rewards generated in real time. Band Protocol is a decentralized oracle framework that uses a data delivery network, a blockchain built on Cosmos-SDK to accommodate user-defined data requests, and a support data oracle on multiple blockchains all in one. With Cosmos, Band becomes a cross-chain data oracle. As a quick refresher, a data oracle is a service that can aggregate and connect real-world data to decentralized applications and smart contracts on a blockchain. Band Protocol Initially, Band Protocol was using common datasets that Ethereum smart contracts could request data from. At the time, the protocol relied on the team to keep these datasets updated. They were communicating with data providers, but the onboarding of each entity was very slow. Later on, the team joined the Cosmos network to create a new, specialized oracle protocol that would be faster, cheaper, and more developer-friendly. The new BandChain is built using the Cosmos SDK, which makes it simple for Band Protocol to implement an oracle on virtually any blockchain, making it a true blockchain-agnostic service. Aragon is a decentralized autonomous organization (DAO) that allows third parties to easily create their own DAOs by using pre-defined smart contracts. Aragon Chain is being developed on the Cosmos network that uses a PoS consensus mechanism to allow for fast transactions between DAOs on the network at a very low cost. Aragon The team sees governance as the top of any given human structure, so they are making it easy for any project to implement such a system within its network. Governance means constant interaction with the community, a load that can’t be sustained by Ethereum. That’s why the team chose to build Aragon Chain’s features using Cosmos SDK. By default, the chain will support EVM, which makes it easy for them to deploy their existing apps on the newly created chain without future development. Later on, Aragon Chain could become a chain in the Cosmos network and interoperate with other chains, even Ethereum, instead of using a direct bridge to the Ethereum mainnet. Bluzelle is a data storage blockchain that offers decentralized applications an easy way to access and maintain a decentralized database. Bluzelle Chain is based on Cosmos, which allows its solution to be easily accessible in a fast and affordable way by any dApp. Bluzelle With Cosmos, Bluzelle expands from database offerings to data services. The project will soon be able to offer data wallets, data feeds, and data oracles. Not only will this help the ecosystem scale, but it also gives Bluzelle access to PoS where farmers can earn BLZ coins for good behavior. BLZ holders can become delegators and pool tokens with a farmer to increase the stake and share rewards. These are all original features that Bluzelle can implement and ship faster thanks to the Cosmos integration. On top of everything, the Cosmos ecosystem expands Bluzelle horizons as it can dynamically connect to other applications using the IBC protocol. That makes it even easier for other dApps to access Bluzelle services. OKExChain is a public blockchain developed by the OKEx cryptocurrency exchange team. The chain is based on a Cosmos SDK forked chain and is used as the underlying architecture for the exchange’s ecosystem. OKExChain The chain is structured in a way that any participant can become a super-node, allowing developers and businesses to build decentralized applications or issue digital assets with ease. To achieve a scalable, efficient, and user-friendly development experience, OKExChain is developed on top of the Cosmos SDK. In this way, OKExChain supports integration with multiple ecosystems, allowing data transmission between different isometric chains. The OKEx team is offering a cross-chain toolkit containing various cross-chain protocols for new and existing apps to be able to communicate with the other chains with ease. OKExChain wouldn’t be able to allow interoperability without the cross-chain features of the Cosmos SDK. OKDEX will be the dApp launched on OKExChain, and one of its main features will be the ability to trade pairs on the other chains within the Cosmos ecosystem. These are five projects that are being integrated within the Cosmos ecosystem. Cosmos makes blockchain powerful and easy to develop with the modularity of its Cosmos SDK. If you are a developer, feel free to reach out to the team members of any of these projects to discover how easy the implementation process was for each of them. If you are a blockchain enthusiast, the user-friendliness, performance, and low transaction fees of these apps will amaze you. Cosmos showed the dApp ecosystem that decentralization can be achieved without scalability compromises. Are you ready for a seamless product experience?

Who's Building dApps On COSMOS: 2020 UPDATE

How can teams perform at their full potential? In 2015, Google conducted to determine what helped teams succeed. They found team dynamics (or culture) to be the biggest predictor, corroborating findings from many other studies. In this post, we examine the kinds of frameworks that help organizations succeed — and help you evaluate your own organization's culture. an organization-wide study Focus: Culture, CI/CD and DevOps The Continuous Delivery movement is taking over the software delivery world. This new philosophy, along with brand new DevOps practices are setting new standards for organizational performance. The book is based on extensive research on continuous delivery practices and goes into detail into the technical and cultural practices that create high performing teams. This book and some of the primary sources it references, form the backbone of this article. This is recommended reading for any leader looking to find ways to improve both culture and performance in their team. Accelerate What kind is your organization? According to research by DevOps Research and Assessment (DORA) and the Google study referenced earlier, "Psychological Safety" is a major predictor of organizational success. It came as no surprise that high-trust organizations that treat their people well are best placed for success. Below is a table with which you can evaluate your own team, and see what kind of organization you're working in. from Google to survey your teammates anonymously and get the answer for your own team. Here's the prevalence of these organization types from a survey: Use this questionnaire were 21% of teams and are usually the highest performing. Generative or Self-Directed environments were 48% of teams and are usually medium performers Bureaucratic work environments were 31% of teams and are known to perform the worst. Pathological or Toxic At , our goal is to build software that helps break down bureaucracy and enables self-directed teams to perform at their full potential. But if you're in a Pathological team that offers low psychological safety, it would be good to reference this research and ask your manager this question: Nirvana How to improve culture Improve Technical Practices Improving Technical Practices are the first step to improving company culture. CI/CD practices emphasize high-quality, high-frequency, low-risk releases to the customer. Sure, this improves the quality of your software, but why does it improve culture? Think of it this way: A disruption (or bug) in your software causes disruption (a bug?) in your team. Because as soon as your product stopped its smooth functioning, your team had to spring into action, and its smooth functioning was also interrupted. This is why implementing technical practices that improve the quality of your output is the first step to improving culture. Research shows that better delivery practices are highly correlated with developer happiness and team performance. So, what is continuous delivery? Here are 3 key principles: Invest in quality - Test & deployment automation, observability and other DevOps practices are paramount.Automate repetitive tasks - People should solve problems, not do repetitive, automatable tasks.Work in small batches - The Principles of Product Development flow emphasizes this point more than any other. We should split work into very small chunks and ship early and often. If you're struggling with the last 2, try Nirvana! Minimize Deployment Pain While this is a part of technical practices, the idea of "Deployment Pain" or "Deployment Anxiety" requires its own section. Deploying new code to your customer is an important event - new software is reaching your customer. This should be cause for celebration! But is it? If you're building features your customers want desperately, you should be happy that you created impact, and that you solved problems. But are you anxious that you might break something instead? With just the experience of this one event, you should be able to understand the health of your team's software delivery practices. Everyone should be shipping early and twice as often, but they won't if the act of shipping is always connected with a feeling of anxiety. If this is a problem for your team, it means that your deployment process is complex and unreliable. It's time to build a fully automated deployment process. to get started. Here's a guide Fight Burnout Unproductive, wasteful work, and toxic, pathological organizations are the leading cause of burnout. This feeling of mental, physical and emotional exhaustion should be fought in every way possible in favor of employee happiness and a feeling of accomplishment. Creating a generative culture described above is a good first step to reducing the risk of burnout. Employees should have the authority to make decisions that affect their work and their jobs, especially in areas where they're responsible for the outcomes. by researchers at UC Berkeley, these were found to be the leading reasons for burnout: In this paper High Workload Inability to influence decisions that affect your job Insufficient rewards, whether social or monetary Unsupportive work environments Lack of fairness in decision-making processes Mismatch in value systems We sincerely hope that none of these apply to your workplace. If the only problem is that workloads are high or expectations are unrealistic, can fix it. Nirvana Conclusion At the end of the day, treating people well is the only winning strategy. When individuals solve problems and meet their full potential at work, it will reflect in their collective performance. And if your team is doing tasks that don't demand their creativity, or if they're spending time on tasks that don't directly create impact for your customer, these tasks should be automated. Previously published at https://nirvana.work/posts/happy-high-performing-teams

Secrets Your Parents Never Told You About Creating High-Performing Teams

shouldn’t need any presentation, but just in case, let me give a quick intro. Y Combinator Y Combinator is an American seed accelerator launched in March 2005. It has been used to launch over 2,000 companies including Stripe, Airbnb, Twitch, DoorDash, Coinbase, Instacart, and Dropbox, to name a few. The combined valuation of the top was over $155 billion as of October, 2019. YC companies While nowadays Y Combinator includes mentors and coaches coming from the gotha of the startup elite, the mind behind the company is , a very well known tech-guru that I would credit for the contribution he made to language and for the launch of , among all his other achievements. Paul Graham Lisp Hacker News I was tracking down Y Combinator Startup School (YCSS) for a couple of years, and well, this time was the right one. The 8-week online course for startups is totally free, and from 2019 it’s held twice a year, so it’s not so hard to get a spot. All you need is to send some information about yourself and your project and grant some commitment. There aren’t specific milestones to pass, like exams or things like that but you need to attend a number of peer reviews to graduate. In the end, the value of this course it’s mostly up to yourself: if you’re willing to study the lectures, take parte in the forums and AMA sesh, interact with other students and attend the video lessons, it’s definitely worth your time. Otherwise, it’s no more useful than scrolling a  Reddit thread ( ). /r/startups The YCSS is structured in an eight-week time frame. Each week you have to submit your goals for the week and the main challenges you are facing. This is the base for the bi-weekly peer review. Then there are the lectures, videos and live sessions with the coaches. Y Combinator even created a dashboard where you can handle the totality of the course, with links to forums, special deals, Telegram group chat, video lessons, Q&A, and more. A video conference room is integrated as well, so you don't need any other tool than a laptop with an internet connection. I liked the YCSS pretty much, considering that it’s a free program. It also provides a good insight over Y Combinator method and the approach of their mentors. I was positively impressed by diversity within the classes: participants were from Indonesia, Thailand, India, North Africa, Russia, of course a lot were from the US West Coast (be ready to attend video confo at wee hours of the morning). And no matter what part of the world you come from, what background you have, what project you are working on: for better or worse we are all facing the same problems, with the same difficulties and constraints. As a side comment, I would not have minded to have a little bit of challenges here and there. A sort of final examination is something that is missing at the moment. But let’s jump back to the purpose of this post. What the hell did I learn during this process? I had many A-HA moments, but let me sum up my 10 most important takes. 1. Talk to your users: Talking to your users is essential. Perhaps the most important thing you should do. You would never ever make a product that nobody wants. Worst, to spend billions of marketing to push it down the customers’ throat. As you may know, having no market is still the first reason startups fail, accounting for more than 40% of the deaths. YCSS program is stressing a lot on that point, even asking you how many surveys you made and what feedback you got from your customers on a weekly basis. You have to become a problem seeker. You need to understand people's real problems. Don’t look for loonshot solutions addressing nobody issues. “Make something people want.” If this list would had to be a single bullet point, it would have been this one. 2. It’s not your customers’ job to give you solutions: A common mistake I see almost everyday it’s asking people what they want, instead of asking them which problems they have. “If I had asked people what they wanted, they would have said faster horses”, as Henry Ford said. It's not up to your users to tell you what they want, they just have to tell you their problems. Then it’s your job to find solutions for them. You are the product owner, not them. 3. No problem is too big to be a show-stopper: No problem is too big to have no workaround around it. During the peer reviews sessions, we discussed very different problems and issues each one of us was having at the time. And believe me, there were some hella big problems coming out. But the mood was always very good and positive. Bigger problems just need bigger workarounds. And that’s good. Let’s keep it going. 4. MVP everything: Don’t even think about spending half a year to develop a finite product. MVP, Minimum Viable Products, is your to-go word. Start small, test, develop, implement, repeat. Don’t waste away your money and your time to work on a product nobody wants or that would take so long to develop that, once it gets to the market, it would be already obsolete. 5. ABS - Always be Shipping Ship early, ship often, ship no-f*ckin-matter what. Design short product sprints, with frequent deploy. If it takes you six months to get to your first deployment in the production environment, your startup is probably going to be dead before you  get another chance to launch. 6. Forget about that “it doesn’t scale” thing: Y Combinator mentors told us this little story: it was rather common to find post-MBA folks who used to discard every single startup pitch they were evaluating by commenting “well, it doesn’t scale”. As a startup in its early stage, please, don’t deal with that. Ok your idea doesn't scale. Fine with that. It’s the starting point for everybody. First validate the concept, then worry about scaling your business. Some of the most valuable, and, well, scalable, startups on the market, started by doing things by hands or mimicking features they still had not. Who cares about that. In a world where the most ground-breaking tech is just next door, there's plenty of room to get your products to scale later on. 7. “Good product instincts” is a trap: Get rid of the  “I’m trusting my guts” BS asap. Nobody has it, and Steve Jobs is dead. Measure all your experiments and don’t rely on “instinct”, “guts”, or “good taste”. You may be surprised by the results, discovering that the ugly-looking template is converting way more than the polished, trendy one, because, well, the former has a better CTA. 8. Build a solid Company Culture: Company culture is often ignored by startups. The mood is like, “money first, culture later”. But well, there is no “later”. You have to set up culture in the very early stage of your company. It’s easy to share a culture statement among ten people, but then try to do it when the company grows to one hundred employees. Culture should work as a de-facto guideline: this is how we behave when there aren't further rules around. And culture should guide you in hiring your first employee, getting your first customer, dealing with product issues, and so on. Remember how much the simple “don’t be evil” quote meant to Google employees, driving their business and growth strategies for almost a decade. So don’t forget about culture and settle it down as soon as possible. 9. Leaders don't brag. You can’t say “I am a good leader”. That's something other people have to say. Do you want to find who’s a true leader? Ask the people around them, who they work with, but also their friends, the bartender where they have their coffee, their neighbors. Leadership is not something you turn on or off when you enter the office. And, by the same means, be careful when someone is claiming out loud their leadership skills. 10. Don’t get sad: This was from YC President Geoff Ralston’s parting advice, during the last lesson of the course. I loved that one. I never bought into the “creating startups is the coolest thing in the world” adage. Creating a biz from scratches is hard, it’s often painful. Things can go disastrously wrong in a startup and the founders feel sadder and sadder. And sadness leads to inaction. It leads to apathy. It leads to depression.  Don't do that. Don't get sad. Go, do, write code. Talk to users. Make your  product better. Always make forward progress in spite of sadness, anger, frustration. In the end it’s not the best that succeed, but the more resilient and prone to rise up failure after failure. And help others, too. If you see someone in trouble, another entrepreneur in distress, reach out to them. We live in an open ecosystem, let it thrive. End notes: "Keep it going" . Well, that’s it. Hopefully you found some inspiration and hint in my story. At least now you know a little bit better what this YCSS is about and around which pillars the course is built. If there’s something you’d like to discuss further, write me in the comments! Get back to work now. And don’t quit!

The 10 Things I’ve Learned Attending Y Combinator Startup School 2020

There is a famous long-running discussion in software engineering that goes under the title “ ”. I’ve never gotten my two cents in, so I thought I’d talk about it a bit here. This is also an opportunity to try to apply the perspective from my experience with software development at Microsoft. Worse is Better This discussion was first framed by Richard Gabriel. He characterized the two different approaches as the “MIT” vs. the “New Jersey” approach. These labels came from the approach taken by the Common Lisp and Scheme groups out of MIT and the contrasting Unix approach coming out of Bell Labs in New Jersey. I found the discussion especially interesting because I did 4 internships at Bell Labs while getting my BS and MS at MIT. So I managed to cross over both schools of thought. Of course, Unix itself was in some sense a counter-response to the “MIT approach” that Ken Thompson and Dennis Ritchie were exposed to while working with MIT on the Multics project (my dad led the Bell Labs team working with MIT on Multics and subsequently managed the Bell Labs research team that developed Unix, so I had additional roots across both camps). For the MIT approach, the essence is “the right thing”. A designer must get the following characteristics right. To paraphrase: : the design must be simple, both in implementation and interface. It is more important for the interface to be simple than the implementation. Simplicity : the design must be correct in all observable aspects. Incorrectness is simply not allowed. Correctness : the design must not be inconsistent. A design is allowed to be slightly less simple and less complete to avoid inconsistency. Consistency is as important as correctness. Consistency : the design must cover as many important situations as is practical. All reasonably expected cases must be covered. Simplicity is not allowed to overly reduce completeness. Completeness The New Jersey or “worse is better” approach is slightly different. To paraphrase: : the design must be simple, both in implementation and interface. It is more important for the implementation to be simple than the interface. Simplicity is the most important consideration in a design. Simplicity : the design must be correct in all observable aspects. It is slightly better to be simple than correct. Correctness : the design must not be overly inconsistent. Consistency can be sacrificed for simplicity in some cases, but it is better to drop those parts of the design that deal with less common circumstances than to introduce either implementational complexity or inconsistency. Consistency : the design must cover as many important situations as is practical. All reasonably expected cases should be covered. Completeness can be sacrificed in favor of any other quality. In fact, completeness must be sacrificed whenever implementation simplicity is jeopardized. Consistency can be sacrificed to achieve completeness if simplicity is retained; especially worthless is consistency of interface. Completeness Gabriel viewed his description of the New Jersey approach as a caricature; clearly it was a worse design strategy. So why was it better? He considered it “better” because it was clearly winning — the early rise of Lisp systems out of the MIT / Stanford community did not end well. As a plethora of mini-computers and workstations sprang up, Unix was easy to get up and running on these machines — it was performant and simple and survived well in the rapidly evolving hardware landscape. The Lisp machines were highly tuned hardware/software systems and could not evolve with the rapidly changing hardware and technology landscape. One of the key divergences between the approaches was clearly the focus on implementation simplicity. In the New Jersey approach, this ends up trumping everything — even correctness! There are a number of consequences of this. One consequence is a tendency away from building “the perfect jewel” and towards getting something built and out there and used. Clearly this is consistent with all the various software methodologies with guidance that focuses on speed to real usage and driving a feedback process (“ship early and often” or “minimum viable product”). The approach also enables the developer to be “locally pragmatic” — to be willing to make tradeoffs in complexity rather than being driven to over-invest in characteristics of the system that end up not providing value for cost. Of course there is room for failure in misinterpreting or misapplying “must not be overly inconsistent” — it is not an argument for capricious design. And “locally pragmatic” and “lazy” lie on a continuum. There are another set of issues that I would group together around , and overall approachability. In a system with significant internal complexity, there is an inevitable risk of that complexity leaking out in unintended ways. A very common leakage to see is performance inconsistency — where certain ways of using an API are fast and predictable and other ways result in unpredictable performance consequences (in the worst cases turning a predictable local computation into one that involves unbounded remote communications — yes, there are very heavily used Microsoft APIs that do this). leaky abstractions accidental complexity One of the problems I had with the design of Windows Presentation Foundation is they provided great power and flexibility in how visual transformations and animations for building user interfaces could be applied, but some effects were efficient in terms of GPU/CPU communications and memory bandwidth and some were extremely expensive. Without knowing details of the implementation, it was very easy to misuse the system and produce results that did not scale well (across data set size or across devices with different performance characteristics). In this case, the system was providing “artificial consistency” — in form the API appeared consistent but in practice it was not. The original source of the discussion gives another example of performance inconsistency. Highly tuned systems often have challenges in responding to a rapidly changing technology landscape. It is harder to really leverage rapidly improving hardware that changes important assumptions about how different parts of the system should interact. In practice this failure to adapt is both a business and technology issue. If the cost to adapt to the changing hardware environment is high, the business case must be very strong to warrant the investment. Failures to adapt are usually consequences of a blend of technical and business cost/benefit factors. Accidental complexity occurs as characteristics of the complex implementation leak out through the interface — client applications and the overall end-to-end system then become dependent on these characteristics which makes the system hard to evolve. It seems intuitively obvious that the more complex the internal implementation is, the harder it is to prevent that complexity from leaking out (and those intuitions are borne out by many examples). Approachability is a characteristic that might not seem so obvious. Shouldn’t a system/API that strives for consistency and completeness be more approachable? My experience using Unix for many years is that it doesn’t quite play out that way. I was reading a comparison of ASP.Net and PHP at one point that resonated strongly with me (sorry, can’t track down the reference). It talked about reading a book like the “Professional ASP.NET” manual and coming away with the feeling “Wow, those guys are smarter than me”. In contrast, you read “Programming PHP” and every step and new capability that is revealed seems reasonable and understandable — you understand how you might have built it yourself but you’re thankful that they’ve included it in the system. Obviously that’s not an holistic comparison of these two very different systems but it is relevant to how internal complexity plays out in the important characteristic of approachability. way The success of NodeJS is another example where approachability ends up having a large consequence on ultimate success. The focus on completeness can be particularly pernicious, especially as it introduces tension around simplicity. Both completeness and consistency lead to increasing the size N of the feature set which leads to growing internal complexity (features interact so complexity grows much faster than linear with the size of the feature set). This internal complexity makes it harder for the component or system to adapt over time to external changes. The goal of consistency can often lead to motivation for significant internal mechanism, especially when a component is layering other elements that might have their own inconsistencies. In fact, for the component builders, this papering over of underlying inconsistencies itself becomes a feature that is being provided. Unfortunately, this consistency almost always comes with performance expense and tradeoff decisions that have now been taken out of the hands of any users of the component. End-to-end arguments in general stress much caution when going down this path.

My $0.02 on Is Worse Better?

CommentBox.io is a hosted commenting system that serves as a beautiful, ad-free alternative to Disqus. On October 24th, we finally launched after 4 months in development. It was made by me, Shaun Persad 👋🏽, and it’s my first product after 8+ years building them for other people. Here’s my story. I always liked reading the stories on and elsewhere about Day. You hear about the anticipation, the nerves, the excitement, the sadness, and the joy of launching your own product. Well, I found out first-hand that it’s all true. Indie Hackers Launch But first, let’s take a step back. There was a Launch Day, yes, and it was interesting. But there was also all the things and work and energy that led up to Launch Day, and it deserves just as much attention. Similarly, there is much work to be done now that Launch Day is over. We’ll cover that too. Pre-launch Prior to this moment, I spent 4 months of , tweaking, refactoring, and even restarting. The journey towards building a good product doesn’t usually go as smoothly or take the amount of time you think it will. But I’m not one of those “build the scrappy version in two weeks and ship” makers. I’m well aware of the “ship often, ship early” mantra, but I’m also well aware of the type of person I am, and the amount of pride I take in my work. coding If I don’t feel good about how something works, I keep at it until I do. Passion projects don’t always make good business sense in terms of hours spent, but when it came to Launch Day, it made all the difference in terms of how I felt. And I’ll tell you this: CommentBox.io is a damn solid product, and in the long run, it will save both time and money to build atop a solid platform. User feedback and “soft” launch Throughout the build-out phase, I kept in close contact with a small group of people who offered their constant help, support, and advice. Whenever I thought of a new feature or wanted to change something, they were there to bounce ideas off of, and to get feedback. It was a small sample size, but not an insignificant one. What really took me by surprise was the “soft launch” that I did on . The feedback I received both publicly and in private was incredibly constructive. I seriously learned so much from just one weekend of exposure. It was all laid bare for critique: everything from the pricing to the website to the messaging to having to defend why the product exists. Indie Hackers It’s an overly vulnerable feeling to finally show strangers your work, but it was wholly, unequivocally, necessary. And it helped give me the polish I needed for Launch Day a few days later. The main event — Launch Day There are quite a few platforms people choose to launch their product. For indie makers, the Big Two are and . I chose both, and I chose to do them both on the same day. I figured doing even one of these is nerve-wrecking as hell, so maybe one full day of is better than two! Product Hunt Hacker News nerve-wrecking-as-hell-edness Product Hunt Launching on Product Hunt almost certainly requires you to wake up earlier than any human should, due to their product rankings resetting at 12:01am PST. So, I woke up at 5am EST, thinking that was early enough (narrator: ). it was not early enough From what I’ve read and now experienced, to make it to the top 3 products of the day, you need a few things: Friends and/or a large network of people who don’t dislike you. A certain level of virality/novelty to your product. The ability to effectively convey your message to the PH audience. Luck. Your mileage may vary. For CommentBox.io, I did not have #1. I did, however, have bits of #2 and #3. The jury is still out on #4. What worked for me was having a product that was interesting and appealing to privacy-minded individuals. I had a pretty decent message as well (which was improved during the day thanks to some great feedback from ). Davis Baer But you need to have decent levels of each, or excessive levels of a few. If you only have one or two factors met, you better have enormous levels of those one or two. And #1 is a doozey. Having a large network is perhaps the most effective mechanism, and probably the hardest to attain. With it, the cadence of engagement (voting, commenting, sharing) is both constant and high, which is basically the PH rocket ship. Without it, your engagement may be high but not constant, or constant but not high. CommentBox.io was the latter. People liked it enough to engage consistently. But there wasn’t quite as many people exposed to it, because . I didn’t have many people to bring with me from my network Hacker News Hacker News is a whole different beast. A simpler, more vicious beast. Where Product Hunt had many requirements, HN seemingly has just this: make a good, interesting product (for varying levels of “interesting”). Timing the post may play a factor, but not as big as you might think. Earlier votes do seem to count more than later ones, but a later surge can bring you from oblivion to page 1 just as easily. In my case, I posted at around 8 or 9am EST. I can’t say for certain what the best time is. But there was very little momentum to start with. In about two hours, the post had faded several pages. Then, several hours later, we shot up to page 2. I cannot explain why, but I do know that once we got going, we got quite a bit of feedback (and page views — more-so than Product Hunt), and stayed on page 2 for around 24 hours. Interestingly, the feedback was quite positive and constructive. The sharp edges HN is often known to exhibit were almost non-existent. I take that as a good sign. Results - Product Hunt: #17 for the day, at around 80+ votes and 13 comments. .- Hacker News: 64 points and 25 comments. .- Website: 2,500 page views and 60 sign ups (all to the free plan).- Body: Millions of wrecked nerves. Pain in the finger that hits the page refresh button. Link here Link here Post-launch It’s been 5 days since Launch Day. Looking at just the numbers, you might think it was a failure. I don’t think it was. I feel great about the launch. The numbers were “mediocre” by some standards, but the experience wasn’t. And the idea that those who did take the time to try the product out had positive experiences, made the time and effort worthwhile. If I hadn’t spent as much time on things, I might have blamed myself. It wasn’t a perfect product, but I know from the words of many strangers that CommentBox.io was ready to have its moment. The product is out there now. People know about it. Maybe not a lot of people, but enough. I saw a total stranger on Twitter and another on Reddit recommend it to someone else. I still receive at least 2 pieces of constructive feedback or feature requests a day. At least 5 people per day have been signing up. Oh, and it’s being used in production on a few sites! I consider all of these anecdotes to be successes. There is interest in this product. There is a place for it. And that’s an excellent motivator. So what’s next? Promotion. New channels. New ways to get the message out there. New problems to solve. And of course, continuing to listen to the users and what they want out of the platform. Launch Day wasn’t the end. It was just the beginning. It was step 1 in a long, ongoing series of upward moves. That said, here’s our tentative product roadmap, which I’m happy to say aligns very well with what our users have been asking for since we launched: Product Roadmap A Wordpress plugin to replace Wordpress comments with CommentBox.io. Import comments from existing sources (starting with Wordpress). Single sign-on/custom auth. Shadow banning. Several other integrations (including Zapier). Super-cool mystery feature ;) And of course, if there are any features you’d love to see, please let me know. - Shaun Originally published at commentbox.io .

Dissecting a “Mediocre” Product Launch

(Original 📸 by ) Rob Lambert Browser extensions give us the ability to enhance services that we love but do not control… Medium is one of the best platforms for online publishing with unparalleled writing experience! As much as I love writing on the Medium I have to say that the provided statistics are extremely basic and lack even the simplest stuff like a summary row with total count of the views, reads, etc… This frustration leads to the creation of which is an Chrome extension. The extension is currently used by more than 100 people and took around 3 months to develop even though it was far from full time engagement… Medium Enhanced Stats open source There have been couple of observations and which I would like to share with you to help you to get to the results faster and prevent repeating my mistakes! lessons learned Ship early, add features and listen to the users Leverage the modern JavaScript Predict and ask for reasonable set of permissions from the start Automate the collection of specific feedback Realize that fixing of a bug can take longer than you would expect Every Chrome extension can be used also as an Opera addon 1. Ship Early, Add Features And Listen To The Users Release early! Build something functional in the most basic form and release it. As cliche as it may sound it is actually a great piece of advice. Ship something and keep building on top of that based on user feedback. Perfection from the start is not necessary and can be actually harmful. Passing time will slowly uncover a lot of opportunities for improvement and optimisations which might not have been so obvious in the beginning! Evolution of the “Total reach popup” feature as an example of “Ship early” approach The original “Total reach popup” was implemented as a simple tag with a formatted text. Over time it evolved into full blown component with many features and much better design! title 2. Leverage The Modern JavaScript (No Browsers, No Cry…) Modern JavaScript is great! The ES6 stuff, modules, async methods, you name it… The only thing holding web back is the need to support some of the older browsers. This is usually solved by introducing a whole galaxy of tools like transpilers and bundlers in standard frontend projects. Chrome extension development is different! Chrome is a evergreen browser so every user can be assumed to run the latest version which supports all the great stuff! This enables us to write good old (ehm new😅) JavaScript and just run it as it is. Directly include and run plain JavaScript file? Seems like we have come full circle! Example of using new JavaScript features without the need for transpilation Also, as I was reminded by this fact enables us to get a bit fancy and use WebComponents without much worries as they are well supported by the Chrome! Martin Hochel 3. Predict And Ask For Reasonable Set Of Permissions From The Start Most Chrome extensions will need to ask for at least some of the permissions to be able to do anything useful. For example, being able to make requests to the target website or sending logs to our server can be pretty useful. User has to confirm set of requested permissions during the initial extension installation. Similarly, user has to confirm any additional permission that we add in future versions of our extension. This unfortunately disables default behaviour and can significantly prolong update timeframe. In the worst case scenario it can even lead to high uninstall rates because of the mistrust on the user’s side. auto update It is much better to ask for a reasonable set of permission from the start instead of asking for a new permission with every new release! For example, during the development of Medium Enhanced Stats I could have foreseen the need for logging and the related URL permission even though it was added much later. Similarly, it would made sense to ask for permission which is needed to implement any “over time” features like checking if user has reached the next milestone or how have the views changed compared to the last month… storage Permissions currently used by Medium Enhanced Stats Follow me on Twitter to get notified about the newest Angular blog posts and interesting frontend stuff 4. Automate The Collection Of Specific Feedback Getting quality feedback is one of the most important things in the whole software development endeavour The more feedback we can get the faster we can fix all the issues which are not obvious to us as developers but are painstakingly clear for the end users! Wouldn’t it be great to get feedback from users who uninstalled our extension? I mean, they liked it enough to install it in the first place so something must have gone wrong... Was it riddled by bugs? Did it keep crashing? Did they expect it to do something else? The truth is we have no clue and the best way to figure this out is to give users the opportunity to vent their frustration in the most frictionless way possible! Chrome extensions provides us with a feature that enables us to which can be used to collect this kind of feedback. The implementation involves setting of an uninstall URL for every new user (the event) and also for every existing user updating to a latest version of the extension (the event). setUninstallURL install update Implementation of the uninstall feedback collection The uninstall URL can then point to the fancy form on our website or even to a modest Google Form which can work just fine while requiring very little investment to get it up and running! ROI 🤑🤑🤑 Example of a Google extension uninstall feedback collection with help of Google Forms 5. Realize That Fixing Of A Bug Can Take Longer Than You Would Expect (Mobile Devs Know…) We’re used to being able to fix bugs immediately, at least in the web application development. The fix is live immediately after it was deployed for all new user sessions. This is the case with extension development. NOT Fixing the bug is just the beginning. Once fixed we have to create a new release that needs to be published in the Chrome Web Store. The fix may still take quite some time until it will be distributed to all our users. Check out the following versions chart. It can easily take more than five days until the majority of the users update to the next version! It can take quite some days until user upgrade to the next version of the extension This brings us to the conclusion that we have to pay extra attention during the testing because the problems we may introduce can take quite some time to fix once they appear on the end user machines! 6. Every Chrome Extension Can Be Used Also As An Opera Addon! Not everybody uses Google Chrome and that’s all right! Unfortunately this limits the potential user base of a Chrome extensions straight from the start. Luckily there is a way to broaden this user base without any additional effort! Opera comes with an addon system similar to the Chrome extensions. One of the available addons is called . This addon does exactly what you would expect it to do and it does it well! Install Chrome Extensions Medium Enhanced Stats seems to be working perfectly using this approach but always test carefully before recommending your users to try this approach! The installation flow for Opera users is to install the addon first and then simply navigate to standard Chrome Web Store and install desired extension in the same way as when using Google Chrome! Install Chrome Extensions Are You Writing On Medium? The extension which was an original inspiration for this article is called . Its main goal is to provide additional information and convenience when working with the very basic Medium stats page. Medium Enhanced Stats Feel free to try it out at ! The extension itself is so you can explore how it works in greater detail… Chrome Web Store open sourced on GitHub That’s It For Today! I hope you enjoyed this article! Please support this guide with your 👏👏👏 to help it spread to a wider audience 🙏 and don’t hesitate to ping me if you have any questions using the article responses or by sending a DM on Twitter . @tomastrajan And never forget, future is bright Obviously the bright future! (Starcraft 🤟🏻) If you made it this far, feel free to check out some of my other articles about Angular & frontend software development… _Today, I am going to share with you the most important lessons I have learned by building Release Butler — a Twitter…_hackernoon.com The 7 Biggest Lessons I’ve Learned By Building A Twitter Bot 🐤🤖 _Introducing Release Butler — A Twitter Bot That Helps You To Stay Up To Date With Releases Of Popular Frontend…_medium.com How To Stay Up To Date With Releases Of Popular Frameworks _Budgets is one of the less known features of the Angular CLI which helps you to keep application bundle sizes in check…_medium.com How Did Angular CLI Budgets Save My Day And How They Can Save Yours

The 6 Pro Tips For Building Great Chrome Extensions

Nowadays everyone talks about (fine grained service oriented architecture). Some of them like Martin Fowler suggests to go for a approach. One of the benefits is avoiding chaty-ness of boundaries. Hence you can ship early and cut off your domains later on one by one. microservices monolith first There is no silver bullet. Different macro architectures have different trade-offs. There are also other aspects that matter for side projects. For example to get with a special kind of architecture. I usually check if an architecture of my interest fits well to my project. Hence I hit two birds with one stone. There are a lot of great lectures and talks about microservices. But as soon as you start using them you realize what really matters. Only a few talks and experience reports go into details about the bad and the ugly parts of their architecture. Companies spent millions to get it done. Marketing, reputation and hiring people are the reason to keep those secrets. But as soon as you drink the 4th beer with an experienced developer you get real insights. For instance a honest answer when you ask: practical experience Would you go for the same architecture again if you could just travel back in time keeping the experience you have right now? Before I go into detail of my project I will define microservice based architecture. Afterwards I talk about disadvantages. If you want to hear pros for microservices go to youtube, get a book or google for it. In short, the microservice architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API. These services are built around business capabilities and independently deployable by fully automated deployment machinery. There is a bare minimum of centralized management of these services, which may be written in different languages and use different data storage technologies. (M. Fowler) programming I will now introduce my common server setup. Followed by the description of my project. Afterwards I will sketch the complexity growth of my services and the experience I made. And in the end I will summarize the bad things and try to find conclusions of my learnings. Infrastructure Usually I rent virtual servers from “oldschool” hosting provides. Right now I am happy with . It’s a german hosting provider. Their virtual servers base upon . Therefore running docker is possible like on bare metal. Netcup KVM For 1 year I am a fan of cloud solutions like Amazon Web Services (AWS). I can add things like caches or load balancer to applications. This saves time and money. Most notably it reduces the complexity of applications. Cloud solutions come with a drawback, their pricing. You will pay 200% until 400% more in comparison to a regular hoster. High peeks related to the daytime allows scaling on demand. Then you can maybe save money, maybe… In an early state I put everything I need for a side project on one virtual server. Hence other people who are part of the project are not able to harm other projects. Additionally each project can scale individually. As soon as one projects gets bigger and requires more resources I add more servers. Separating the production environment from my ci-system and testing environment allows better scaling and increases security. Furthermore I move the tools for team distributed work to an autonomous machine. For this project I start with the following setup: Intel® Xeon® E5–2680V4 6 GB DDR4 RAM (ECC) 2 dedicated cores 40 GB SSD This setup costs about 8 € and can handle all infrastructure parts. It serves up to 1000 Users simultaneously for simple applications. Online competition platform One side project of mine is an online platform for people who love playing multiplayer games. There you can create and attend in game races and the best players can win prizes. There is a frontend monolith implemented with React. Additionally there are multiple backend microservices separated by their : domain A user can create and manage races to display and signup for available races. Race service: Fetches, processes and stores match detail data. This is that basic data to calculate rankings. Stats service: Stores and updates player profile data to show player attends. Furthermore it stores won prices and results of the past races. Profile service: Iterations In the beginning I started with a to manage competitions in general. This services has a couple of endpoints to create, read, update and delete races. Participants are able to join when the races has not started. Related to the state of the race (upcoming, running, finished) a various set of other constraints exists. races service My initial setup was: Spring boot for the races services, Gitlab and Gitlab-CI to host the code, run tests and deploy the code, Docker and docker compose to create deployable units for dev, testing and prod, React for pure frontend behavior, Basic NodeJs express app for a landing page and basic authentification using Oauth2. First CD pipeline In the beginning this was quiet simple. One frontend, one backend, a quick build and automated tests. Adding features was a charm compared to a big enterprise application. The whole CI-pipeline run about 15 minutes and a new version was live. I always try to test everything to have a good feeling as soon as I push code. Therefore I added functional tests that fires Rest requests to my service. There is already a task that dockerizes my services. For testing I start all services using another container name prefix. Additionally I change the ports to non production ports. As soon as all instances are up and running I can run my tests. These fires requests to my application and expect certain responses. To make sure that the whole application works I added based end to end tests. They help to make sure that the frontend works. Furthermore it reveals whether the backend communication operates correctly. I only test the happy path of creating a race. CasperJs At this point a full pipeline execution required about 20 minutes. As I added more and more features complexity grew. The second services was the . First I copied the existing Spring based service, changed the port and added new CI steps. Coming from 20 minutes CI runtime I was already up to 30 minutes. I copied the build, test, rest integration and end-to-end test tasks. Furthermore besides the admin frontend I added a user frontend to access races. Stats service At this point each service has hardcoded names and ports of other services. At least it was partly dynamically using environment variables: requestedServicePort = basePort + requestedServicePortOffset Hence test systems starts separately. Therefore I can deploy my application with no downtime. This works by changing the port redirection as soon as the new application is up and running. At this point the application survived the first user tests successfully. Accordingly my team decided to go further. Time went by and I added the profile service to persist global user statistics. Now the strikes in. Instead of wire all those services together I went for a more scaleable and flexible solution. I use a service discovery called . I needed insights about availability and healthyness of my services. A Spring based admin dashboard communicates with Eureka and gives me all the data I need. rule of three Eureka On my machine it worked very well. It felt like a great system. No static links, no additionally configuration. Each service only registers itself at Eureka and asks Eureka for other service’s IP and port. For client side load balancing I use . Hence the load can spread between multiple service instances. To achieve fault tolerance I also use . Ribbon Hystrix After adding all these services my server worked up sweat. CI-tasks started to fail sometimes. Deployments took a lot of time. The machine runs out of memory and swap. At this state I would have to invest more time and money to scale vertically and horizontally. The easiest solution would be to get a more expensive virtual server. Anyways, I started to think about what slows me down: : Services need to call other service’s endpoints to fetch data synchronously using a . Compared to a simple method call it’s complex. Complex service communication circuit breaker repository : Keeping models in sync is annoying. It usually happens that they exists in multiple services. Hence changing them requires adapting services. Especially in the beginning of new projects this happens a couple of times. The same issues exists for copied configuration files. They changes and I need to keep them in sync manually. Duplicated Code Each microservice uses external dependencies. To keep my project healthy I try update packages every 2 weeks. For new package releases I usually need to update service by service. Update external dependencies: When you test interactions between components it’s usually harder compared to unit tests. In a microservice world you need to test interactions on another layer. Execution is slower and they tend to break a lot more often. Additionally refactorings usually break them. In a pure backend project my IDEs are smart enough to automatically fix the issue or at least throw an compile time error. Integration tests are more complex: Usually each service should be independently deployable. This keeps build times fast and complexity low. But if you have only a few developers which work on all services this does not make sense in an early state. Additionally you usually want to run some integration tests that affects multiple services. Having a single version control system keeps things simple. Therefore you need a lot of ci-jobs. For each service you need tasks for building, testing and packaging. CI execution is slow for small projects: All these downsides sounds harsh. I am a microservice fan but as I said, this thread will only highlight the bad things. Summing pros and cons up I decided to migrate to a more monolithic like backend. The target now was to put the race, stats, profile service into a single one. Additionally I could get rid of the admin and eureka service and reduce service communication. It took me about 6 hours. Having different test layers saved me so much time. My first target was, after copying the tests to the “monolith”, to make the tests work again. After I fixed all Java based tests I did the same with the Rest and CasperJs tests. I also tidied the CI pipeline a bit up. I could get ride of t he building task. An application build was also part of the testing stage. In the and I was back to 15 minutes build time having a lot of tests and a very safe deployment process. Afterwards the code looked a lot better. I used for my core concepts. The services I had before the refactoring now exists in one service within different package structures. This allows me to check the dependencies between packages later on. Therefore this enables me to cut off microservices again very quickly as soon as I need better horizontal scalability. domain driven design So my learnings for future projects are: architecture . When I think microservices are the right architecture I will cut off microservices later on. Everyone should try to challenge this. This project was totally worth the effort when I think about the learnings I got from it. Never go for microservices on a greenfield project A and a is mandatory for a system that evolves. Refactoring into microservices and visa versa are easier and less error-prone. good micro-architecture solid code coverage Services should be . Otherwise build times explodes. This sounds easy but is hard for services that depend on other services. independently deployable are a good way to reduce the responsibility of end to end tests. They give fast feedback and they point directly to the issue. Hence refactorings are easier. Additionally end to end tests can be executed after your deployment to reduce time to market. Consumer driven contracts is great and I should use it more and more often. My development, testing and production systems are easy to setup and to start. Especially for microservices it’s important to have such an isolation. But also for a monolith it’s definitely worth the effort. Docker Domain related microservices needs other basic services like a service discovery. All services needs a to work reliable. Especially the JVM does not know about docker (cgroup) based restrictions. They cause issues when defining memory limits. decent amount of memory Software development is only about trade offs. Before developers commit on a new they should get a feeling about the pros and cons. For example by playing around with them. The down sides of microservices are dramatically and can be the reason why projects fail. If handled well a microservice architecture can be a reasonable decision. It accelerates the development process and gives developers more freedom. technology The biggest benefit comes for companies that have many development teams for a certain project. Being able to develop and deploy a service independently . That means the developers feel for what and how they implement requirements. Additionally they are able to escort a feature from dev, to test, to production. In combination with for instance production bugs can be heavily reduced. Scalability is also a characteristic of microservices but in comparison relatively irrelevant. increases ownership more responsible canary releases I hope you enjoyed the reading. Feel free to send me feedback and questions using the platform of your choose. I appreciate any follower on because this is my main communication tool to you. Twitter

Backpedal a microservice architecture of a greenfield project

Without growth your startup will die. At startups, growth means increasing revenue or customers. Once your product is working for customers, and not before, you should be aiming for . Here’s how to hit that goal: 10% weekly growth Push Engagement Real growth is based on positive recommendations from engaged customers — the people who love your product. These customers use your product everyday and generate organic, sustainable growth. Definition: Once you’ve identified your engaged customers, talk to them — . Ask them: “What do you like about the app?”, “What do you dislike?”, “What problems do you face in your daily work?”. Identify patterns across these customer surveys and use the data to create a roadmap for your future experiments (see ‘Run Experiments’ below). Execution: all the time Ignore top-line vanity metrics like signups or downloads. These can be easily swayed by PR or similar short term spikes, which are not real growth. In addition, don’t go crazy with metrics, you probably don’t need more than . Avoid: 3 core metrics for the business Run Experiments Experiments should be directed by customer feedback from a) happy customers, b) churning customers, c) disengaged customers and d) potential customers who chose a competitor. Experiments can be run on every aspect of the business from user experience to sales and marketing to customer support, essentially any customer touch point. Definition: Test only 1–2 things concurrently and decide what success looks like in advance for each test. When budgeting resources, allocate 75% to existing operations and 25% to new experiments. This split allows you to get the benefit of known operations working well, while giving yourself a good chance to find something better. Optimizely and LaunchDarkly are popular tools for live experiments on production systems. Execution: Steer clear of big projects. You can work on larger projects after hitting your growth milestones for your current product. Don’t optimize for 100% reliability in an experiment, if it works you can always rebuild it. Right now you need to ship early and often. Avoid: Hire at Choke Points Your business will come under steadily more pressure as your customer base grows. You’ll need to hire people in the areas under the most strain, the ‘choke-points’, as these issues tend to recur in growth situations. Definition: Once a choke-point is identified, search for great people who can solve that specific problem**.** For example, if your website is running slow, you should hire a platform engineer, not a mobile app developer; if new customers aren’t engaging, hire in customer success, not sales**.** Execution: Don’t hire for roles you don’t currently need, even if the person is truly great. , you can’t afford to invest that time in someone who will not drive near term growth. Explain the situation honestly and hire them later. Avoid: It takes months to find the right person Building a product people use is a good start but it’s only one ingredient of a successful startup. Achieving 10% weekly growth begins with listening to customers and acting on their feedback. Thanks to Kaego Rust for reading drafts of this.

Stories, News & Mentions about SHIPEARLY

Shipearly’s Stories on HackerNoon

Shipearly's News & Mentions