Eliq’s purpose is to enable the home energy transition by helping utilities, banks, and smart-home providers to empower their customers to make intelligent and sustainable home energy choices. We drive digital transformation through our SaaS platform that leverages AI and data collected through unique customer interactions to generate insights that inspire and empower customers to join the fight against climate change. The platform enables active customer relationships based on targeted and highly personalised offers, for non-commodity business growth at a transformative scale. We are advocates for the utilisation of open energy data, for an acceleration in the home energy transition. The fight against climate change is one that we need to tackle together, and we believe in creating strong partnerships with organisations that share our values and passion for a sustainable future. We're entering a phase of rapid growth and are looking for people who are passionate about creating high-quality user experiences and want to be part of our fun, friendly and hard-working team.

Eliq

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) D.Sinclair, Imense Ltd, and email: david@imense.com;
(2) W.T.Pye, Warwick University, and email:  willempye@gmail.com. Table of Links Abstract and Introduction
Interrogating the LLM with an Emotion Eliciting Tail Prompt
PCA analysis of the Emotion of Amazon reviews
Future Work
Conclusions
Acknowledgments and References 2. Interrogating the LLM with an Emotion Eliciting Tail Prompt In this work we used Facebook’s open source LlaMa2 7 billion weight LLM as the core engine [2]. It was necessary to use a LLM that allowed access to raw token probabilities after a prompt. The model ran on a Mac Studio with 32 gigabytes of RAM. With this combination of hardware and model it took 2 minutes to compute the probabilities of the emotion descriptors in the emotion dictionary given below. 2.1. The Emotion Dictionary The English language is blessed with many words and an extensive literature providing examples of the usage of these words in appropriate contexts. For the purposes of LLMs, it is the context of a word that conveys it’s meaning. A reader will infer the meaning of an unfamiliar word through the context they find the word used in, provided they understand the context. As an example, ‘The shotgun discombobulated the rabbit.’ shows how meaning can be moderated by context. The context created by a tail prompt will favour an associated class of words. For the experiment detailed in this paper the following tail prompt was used to elicit emotion descriptors, ’Reading this makes me feel’. It is likely that specific emotion eliciting tail prompts will favour specific sub classes of descriptor but studying this is beyond the scope of this paper The following words were chosen to provide a broad sample of emotion descriptors. acceptance, admiration, adoration, affection, afraid, agitation, agony, aggressive, alarm, alarmed, alienation, amazement, ambivalence, amusement, anger, anguish, annoyed anticipating, anxious, apathy, apprehension, arrogant, assertive, astonished, attentiveness, attraction, aversion, awe, baffled, bewildered, bitter, bitter sweetness, bliss, bored, brazen, brooding, calm, carefree, careless, caring, charity, cheeky, cheerfulness, claustrophobic, coercive, comfortable, confident, confusion, contempt, content, courage, cowardly, cruelty, curiosity, cynicism, dazed, dejection, delighted, demoralized, depressed, desire, despair, determined, disappointment, disbelief, discombobulated, discomfort, discontentment, disgruntled, disgust, disheartened, dislike, dismay, disoriented, dispirited, displeasure, distraction, distress, disturbed, dominant, doubt, dread, driven, dumbstruck, eagerness, ecstasy, elation, embarrassment, empathy, enchanted, enjoyment, enlightened, ennui, enthusiasm, envy, epiphany, euphoria, exasperated, excitement, expectancy, fascination, fear, flakey, focused, fondness, friendliness, fright, frustrated, fury, glee, gloomy, glumness, gratitude, greed, grief, grouchiness, grumpiness, guilt, happiness, hate, hatred, helpless, homesickness, hope, hopeless, horrified, hospitable, humiliation, humility, hurt, hysteria, idleness, impatient, indifference, indignant, infatuation, infuriated, insecurity, insightful, insulted, interest, intrigued, irritated, isolated, jealousy, joviality, joy, jubilation, kind, lazy, liking, loathing, lonely, longing, loopy, love, lust, mad, melancholy, miserable, miserliness, mixed up, modesty, moody, mortified, mystified, nasty, nauseated, negative, neglect, nervous, nostalgic, numb, obstinate, offended, optimistic, outrage, overwhelmed, panicked, paranoid, passion, patience, pensiveness, perplexed, persevering, pessimism, pity, pleased, pleasure, politeness, positive, possessive, powerless, pride, puzzled, rage, rash, rattled, regret, rejected, relaxed, relieved, reluctant, remorse, resentment, resignation, restlessness, revulsion, ruthless, sadness, satisfaction, scared, schadenfreude, scorn, self-caring, self-compassionate, self-confident, self-conscious, self-critical, self-loathing, self-motivated, self-pity, self-respecting, self-understanding, sentimentality, serenity, shame, shameless, shocked, smug, sorrow, spite, stressed, strong, stubborn, stuck, submissive, suffering, sullenness, surprise, suspense, suspicious, sympathy, tenderness, tension, terror, thankfulness, thrilled, tired, tolerance, torment, triumphant, troubled, trust, uncertainty, undermined, uneasiness, unhappy, unnerved, unsettled, unsure, upset, vengeful, vicious, vigilance, vulnerable, weak, woe, worried, worthy, wrath. This set of words is not intended to be complete or definitive in any way. Using the tail prompt without restricting the return to emotion descriptors elicits general waffle responses that are not straightforward to extract sentiment form. 2.1.1. Estimating the emotion probability vector LlaMa2 [2] has been released in such a way as to allow developers to access estimated token weights returned in response to a prompt. LlaMa2 has an internal vocabulary size of roughly 30,000 tokens. This means that when LlaMa 2 estimates the probability of the next token in a sequence the probability vector will have 30,000 elements. Some of the words in the emotion descriptor list are made up of more than one token in which case forward conditional probabilities are used. Figure 2.1.1 shows the scaled probability distribution over words from the emotion dictionary elicited by the tail prompt for the Amazon review text, ‘I read a lot of negative reviews about the Fitbit inspire 2, I took a chance and hoped the one I ordered would be one of the great ones that worked. Unfortunately that was not the case. I unpacked it, charged it, downloaded the app. I took a walk with it on before the sun went down. I have the Google Fit app on my phone that tracks my steps also. The phone was in my jeans pocket. When I got home I compared the two, Google Fit said 4,458 steps, Fitbit said 1,168. Apparently Fitbit works with wrist motion which I don’t have while pushing a walker around the neighborhood. I downloaded the manual and noticed you can put it on a clip (that wasn’t included). That would work for me. So I started to scroll through the different features except I couldn’t scroll through all of them. While scrolling I must have turned on the stopwatch. I couldn’t turn it off. Then I couldn’t scroll through anything except water lock feature. I had to turn on the water lock to get back to the stopwatch. Then the side buttons stopped working. I had it a total of 5 hours. I packed it up and started the Amazon return. I did get a full refund. Very disappointing.’ The text from 50 Amazon reviews of a book was borrowed from https://www.amazon.com/dp/B000WM9UK2. The reviews were for the most part favourable. Example review texts include: ‘The Children of H´urin is a great tragedy mixed with grace. The genealogical records at the beginning may be difficult to get through, but the story very quickly gains speed. I only gave the story four stars because of the difficulty of the first few chapters, much like Matthew’s genealogy of Christ at the beginning of his gospel. Although such records are important in both they are nonetheless difficult to get through. I still definitely would recommend this book, though, as it depicts the horrible effects of evil powers on good men and women, and yet, we must continue to resist evil no matter the tragic end. It is very telling that in Tolkien’s world, at the end of days when Morgoth returns, that it is T´urin, a man, who ends him once and for all. Those whom Satan most destroys in this life are they who will ultimately deal his death blow, as the Revelation says, “They overcame him by the blood of the Lamb and by the word of their ‘martyria,’ [witness, testimony],” those like T´urin, or in Scripture, those like Job.’ Figure 2.1.2 shows the emotion vectors for all 50 processed reviews. The 10 most probable emotions experienced from purchasing the product were: depressed, kind, nostalgic, tired, hopeless, lonely, hope, calm, lazy, confident. This paper is available on arxiv under CC 4.0 license. Authors: (1) D.Sinclair, Imense Ltd, and email: david@imense.com; (2) W.T.Pye, Warwick University, and email:  willempye@gmail.com. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) D.Sinclair, Imense Ltd, and email: david@imense.com; (2) W.T.Pye, Warwick University, and email:  willempye@gmail.com. Table of Links Abstract and Introduction Interrogating the LLM with an Emotion Eliciting Tail Prompt PCA analysis of the Emotion of Amazon reviews Future Work Conclusions Acknowledgments and References Abstract and Introduction Abstract and Introduction Interrogating the LLM with an Emotion Eliciting Tail Prompt Interrogating the LLM with an Emotion Eliciting Tail Prompt PCA analysis of the Emotion of Amazon reviews PCA analysis of the Emotion of Amazon reviews Future Work Future Work Conclusions Conclusions Acknowledgments and References Acknowledgments and References 2. Interrogating the LLM with an Emotion Eliciting Tail Prompt In this work we used Facebook’s open source LlaMa2 7 billion weight LLM as the core engine [2]. It was necessary to use a LLM that allowed access to raw token probabilities after a prompt. The model ran on a Mac Studio with 32 gigabytes of RAM. With this combination of hardware and model it took 2 minutes to compute the probabilities of the emotion descriptors in the emotion dictionary given below. 2.1. The Emotion Dictionary The English language is blessed with many words and an extensive literature providing examples of the usage of these words in appropriate contexts. For the purposes of LLMs, it is the context of a word that conveys it’s meaning. A reader will infer the meaning of an unfamiliar word through the context they find the word used in, provided they understand the context. As an example, ‘The shotgun discombobulated the rabbit.’ shows how meaning can be moderated by context. The context created by a tail prompt will favour an associated class of words. For the experiment detailed in this paper the following tail prompt was used to elicit emotion descriptors, ’Reading this makes me feel’. It is likely that specific emotion eliciting tail prompts will favour specific sub classes of descriptor but studying this is beyond the scope of this paper The following words were chosen to provide a broad sample of emotion descriptors. acceptance, admiration, adoration, affection, afraid, agitation, agony, aggressive, alarm, alarmed, alienation, amazement, ambivalence, amusement, anger, anguish, annoyed anticipating, anxious, apathy, apprehension, arrogant, assertive, astonished, attentiveness, attraction, aversion, awe, baffled, bewildered, bitter, bitter sweetness, bliss, bored, brazen, brooding, calm, carefree, careless, caring, charity, cheeky, cheerfulness, claustrophobic, coercive, comfortable, confident, confusion, contempt, content, courage, cowardly, cruelty, curiosity, cynicism, dazed, dejection, delighted, demoralized, depressed, desire, despair, determined, disappointment, disbelief, discombobulated, discomfort, discontentment, disgruntled, disgust, disheartened, dislike, dismay, disoriented, dispirited, displeasure, distraction, distress, disturbed, dominant, doubt, dread, driven, dumbstruck, eagerness, ecstasy, elation, embarrassment, empathy, enchanted, enjoyment, enlightened, ennui, enthusiasm, envy, epiphany, euphoria, exasperated, excitement, expectancy, fascination, fear, flakey, focused, fondness, friendliness, fright, frustrated, fury, glee, gloomy, glumness, gratitude, greed, grief, grouchiness, grumpiness, guilt, happiness, hate, hatred, helpless, homesickness, hope, hopeless, horrified, hospitable, humiliation, humility, hurt, hysteria, idleness, impatient, indifference, indignant, infatuation, infuriated, insecurity, insightful, insulted, interest, intrigued, irritated, isolated, jealousy, joviality, joy, jubilation, kind, lazy, liking, loathing, lonely, longing, loopy, love, lust, mad, melancholy, miserable, miserliness, mixed up, modesty, moody, mortified, mystified, nasty, nauseated, negative, neglect, nervous, nostalgic, numb, obstinate, offended, optimistic, outrage, overwhelmed, panicked, paranoid, passion, patience, pensiveness, perplexed, persevering, pessimism, pity, pleased, pleasure, politeness, positive, possessive, powerless, pride, puzzled, rage, rash, rattled, regret, rejected, relaxed, relieved, reluctant, remorse, resentment, resignation, restlessness, revulsion, ruthless, sadness, satisfaction, scared, schadenfreude, scorn, self-caring, self-compassionate, self-confident, self-conscious, self-critical, self-loathing, self-motivated, self-pity, self-respecting, self-understanding, sentimentality, serenity, shame, shameless, shocked, smug, sorrow, spite, stressed, strong, stubborn, stuck, submissive, suffering, sullenness, surprise, suspense, suspicious, sympathy, tenderness, tension, terror, thankfulness, thrilled, tired, tolerance, torment, triumphant, troubled, trust, uncertainty, undermined, uneasiness, unhappy, unnerved, unsettled, unsure, upset, vengeful, vicious, vigilance, vulnerable, weak, woe, worried, worthy, wrath. This set of words is not intended to be complete or definitive in any way. Using the tail prompt without restricting the return to emotion descriptors elicits general waffle responses that are not straightforward to extract sentiment form. 2.1.1. Estimating the emotion probability vector LlaMa2 [2] has been released in such a way as to allow developers to access estimated token weights returned in response to a prompt. LlaMa2 has an internal vocabulary size of roughly 30,000 tokens. This means that when LlaMa 2 estimates the probability of the next token in a sequence the probability vector will have 30,000 elements. Some of the words in the emotion descriptor list are made up of more than one token in which case forward conditional probabilities are used. Figure 2.1.1 shows the scaled probability distribution over words from the emotion dictionary elicited by the tail prompt for the Amazon review text, ‘I read a lot of negative reviews about the Fitbit inspire 2, I took a chance and hoped the one I ordered would be one of the great ones that worked. Unfortunately that was not the case. I unpacked it, charged it, downloaded the app. I took a walk with it on before the sun went down. I have the Google Fit app on my phone that tracks my steps also. The phone was in my jeans pocket. When I got home I compared the two, Google Fit said 4,458 steps, Fitbit said 1,168. Apparently Fitbit works with wrist motion which I don’t have while pushing a walker around the neighborhood. I downloaded the manual and noticed you can put it on a clip (that wasn’t included). That would work for me. So I started to scroll through the different features except I couldn’t scroll through all of them. While scrolling I must have turned on the stopwatch. I couldn’t turn it off. Then I couldn’t scroll through anything except water lock feature. I had to turn on the water lock to get back to the stopwatch. Then the side buttons stopped working. I had it a total of 5 hours. I packed it up and started the Amazon return. I did get a full refund. Very disappointing.’ ‘I read a lot of negative reviews about the Fitbit inspire 2, I took a chance and hoped the one I ordered would be one of the great ones that worked. Unfortunately that was not the case. I unpacked it, charged it, downloaded the app. I took a walk with it on before the sun went down. I have the Google Fit app on my phone that tracks my steps also. The phone was in my jeans pocket. When I got home I compared the two, Google Fit said 4,458 steps, Fitbit said 1,168. Apparently Fitbit works with wrist motion which I don’t have while pushing a walker around the neighborhood. I downloaded the manual and noticed you can put it on a clip (that wasn’t included). That would work for me. So I started to scroll through the different features except I couldn’t scroll through all of them. While scrolling I must have turned on the stopwatch. I couldn’t turn it off. Then I couldn’t scroll through anything except water lock feature. I had to turn on the water lock to get back to the stopwatch. Then the side buttons stopped working. I had it a total of 5 hours. I packed it up and started the Amazon return. I did get a full refund. Very disappointing.’ The text from 50 Amazon reviews of a book was borrowed from https://www.amazon.com/dp/B000WM9UK2. The reviews were for the most part favourable. Example review texts include: ‘The Children of H´urin is a great tragedy mixed with grace. The genealogical records at the beginning may be difficult to get through, but the story very quickly gains speed. I only gave the story four stars because of the difficulty of the first few chapters, much like Matthew’s genealogy of Christ at the beginning of his gospel. Although such records are important in both they are nonetheless difficult to get through. I still definitely would recommend this book, though, as it depicts the horrible effects of evil powers on good men and women, and yet, we must continue to resist evil no matter the tragic end. It is very telling that in Tolkien’s world, at the end of days when Morgoth returns, that it is T´urin, a man, who ends him once and for all. Those whom Satan most destroys in this life are they who will ultimately deal his death blow, as the Revelation says, “They overcame him by the blood of the Lamb and by the word of their ‘martyria,’ [witness, testimony],” those like T´urin, or in Scripture, those like Job.’ ‘The Children of H´urin is a great tragedy mixed with grace. The genealogical records at the beginning may be difficult to get through, but the story very quickly gains speed. I only gave the story four stars because of the difficulty of the first few chapters, much like Matthew’s genealogy of Christ at the beginning of his gospel. Although such records are important in both they are nonetheless difficult to get through. I still definitely would recommend this book, though, as it depicts the horrible effects of evil powers on good men and women, and yet, we must continue to resist evil no matter the tragic end. It is very telling that in Tolkien’s world, at the end of days when Morgoth returns, that it is T´urin, a man, who ends him once and for all. Those whom Satan most destroys in this life are they who will ultimately deal his death blow, as the Revelation says, “They overcame him by the blood of the Lamb and by the word of their ‘martyria,’ [witness, testimony],” those like T´urin, or in Scripture, those like Job.’ Figure 2.1.2 shows the emotion vectors for all 50 processed reviews. The 10 most probable emotions experienced from purchasing the product were: depressed, kind, nostalgic, tired, hopeless, lonely, hope, calm, lazy, confident.

Estimate Emotion Probability Vectors: Interrogating the LLM with an Emotion Eliciting Tail Prompt

আবেগ সম্ভাবনা ভেক্টর অনুমান করুন: একটি আবেগ এলিসিটিং টেইল প্রম্পটের সাথে এলএলএমকে জিজ্ঞাসাবাদ করা

Schätzen Sie Wahrscheinlichkeitsvektoren für Emotionen: Abfragen des LLM mit einem Emotionen hervorrufenden Tail Prompt

Estimar vectores de probabilidad de emociones: interrogar al LLM con un mensaje de cola que provoca emociones

Estimer les vecteurs de probabilité d'émotion : interroger le LLM avec une invite de queue suscitant des émotions

भावना संभाव्यता सदिशों का अनुमान लगाना: भावना उद्घाटित करने वाले टेल प्रॉम्प्ट के साथ LLM से पूछताछ करना

感情確率ベクトルの推定: 感情を喚起するテールプロンプトによる LLM の調査

감정 확률 벡터 추정: 감정 유도 꼬리 프롬프트로 LLM 조사

Estimar vetores de probabilidade de emoção: interrogando o LLM com um prompt de cauda que provoca emoção

Оценка векторов вероятности эмоций: опрос LLM с помощью хвостовой подсказки, вызывающей эмоции

Duygu Olasılığı Vektörlerini Tahmin Edin: Yüksek Lisans'ı Duygu Ortaya Çıkaran Kuyruk İstemi ile Sorgulamak

Ước tính các vectơ xác suất cảm xúc: Thẩm vấn LLM bằng lời nhắc gợi ý cảm xúc

估计情绪概率向量：用引发情绪的尾部提示询问法学硕士

Going from a mediocre team to an elite team can seem daunting, especially when we need to figure out where to start. The DevOps Research and Assessment (DORA) can be our north star, helping us build the habits and practices we need to be elite. We'll look at DORA, the challenges of building habits, and how to form habits that stick. What Is DORA? The DevOps Research and Assessment (DORA) report focuses on four key areas to measure elite teams: Lead time: How long does it take from code committed to running in production
Deploy frequency: How often does our organization deploy to production
Change fail percentage: How often do we need to rollback, patch, hotfix, or fix forward after a change
Failed deployment recovery time: How long does it generally take to recover service The challenge here is going from knowing about those four areas that need to be worked on so that we go from being a mediocre team to an elite squad scoring a ten on the DORA quick check. The four measurements of an elite team are: Lead time is less than one hour


Deploy frequency is on-demand (multiple deploys per day)


The change fail percentage is ideally 0%


Failed deployment recovery time is less than one hour To see where tour team currently places, try the DORA quick check. This blog will focus on the tools, technologies, practices, culture, and philosophies that will help teams become elite. Improvements in our work take time since we need to break old habits that don't serve us well and build new ones. This blog will keep that in mind as we move through different topics. Each post will have an invitation to try out what we learn. If there are any questions or issues that need to be covered, make use of the comments section to submit the question. The Challenges of Forming New Habits We've all seen New Year's Resolutions and possibly have had some of our own. According to the Forbes report in 2024, 53% of those surveyed had given up on their New Year's Resolutions by the end of March. For many people, sticking to a new resolution or goal is challenging. There is now a day known as Ditch New Year's Resolution Day, which during 2024 fell on January 17th. While the media paints a picture of a significant stumbling block, statistics show it's less troublesome than perceived. We can see the reality of the quit rate in the chart below: Source Why Do People Fail in Their New Resolutions/Habits? In an article by James Clear, he outlines five reasons our new habits might fail: Trying to change more than one thing at a time


Setting big goals without breaking them down into smaller steps


Seeking a result, not the ritual


We have not changed the environment in which we perform our good habits, so we quickly revert to our bad habits


Assuming small changes don't add up However, there are ways to set ourselves up for success. In the book Atomic Habits, James talks about three key lessons: Small habits make a big difference.
Forget about setting goals. Instead, focus on the system.
Build identity-based habits. The Impact of Habits Building identity-based habits means, for example, instead of saying I go running, we say we're runners, or instead of saying we paint, we say we're painters. There is a subtle difference in the wording, but if we start to think we're runners, that can lead to thinking, what does a runner do? It could mean changing the food we eat, how often we train, when we train, and the goals we set for ourselves. If we focus on getting 1% better every day in one year, we'll end up being 37 times better than when we started. It means that anything we set our mind to can profoundly impact us. It may not be noticeable at first, but as the changes compound over time, we will notice that we're a different person than when we started. Like a cliff being eroded over time by the waves, at the start, we overlook the impact each wave has, but over time, we see how the cliff face changes in its shape. How Do I Go About Creating and Maintaining Habits? In the Habits Cheatsheet, James Clear talks about the four laws to create a good habit: The 1st law (Cue): Make it obvious
The 2nd law (Craving): Make it attractive
The 3rd law (Response): Make it easy
The 4th law (Reward): Make it satisfying As an example, let's say we've decided that we want to drink more water every day. We could make it obvious by placing a water bottle on our desk so that we can't miss it. Having a nice bottle or putting some lemon or mint in the water would be attractive. To make it easy, we fill the water bottle the night before so we don't have to think about it in the morning. Then, to make it satisfying, we could have a calendar above our desk where we put a sticker to mark each day that we've managed to empty our water bottle. How Do I Beat My Old Bad Habits? Again, in the Habits Cheatsheet, there are the inverse laws for avoiding our bad habits: Inversion of the 1st law (Cue): Make it invisible
Inversion of the 2nd law (Craving): Make it unattractive
Inversion of the 3rd law (Response): Make it difficult
Inversion of the 4th law (Reward): Make it unsatisfying Let's say we want to watch less TV. We could make it invisible by placing the TV out of view, moving it to another room, or inside a cupboard. We might unsubscribe to our streaming accounts and TV subscriptions to make it unattractive. To make it difficult, we place the TV's power cord or remote control in another room. Finally, to make it unsatisfying, we could have an accountability partner that we check in with, with whom we will have to confess that we ended up watching TV. The Next Steps As we reflect on our DORA scores, we have an opportunity to identify areas where we can improve by forming new habits. The DORA quick check provides guidance on key areas we can work on to improve our score. In our team, we can decide what to work on to raise our score, moving us from developers to software craftspeople. Then, we can form habits to help us make lasting changes. For example, if we identify a need to reduce lead time, we may realize our review process is slowing us down. When we explore it, we recognize we need to set aside time to review the code. We could take a habit-stacking approach. For example, when we open our laptops in the morning (our current habit), we first review all of the pull requests that are pending review for us. Another could be first to review pull requests after our lunch break. To make it attractive, we might realize that the pull requests lack enough information, so we add a pull request template so all the information is there. Then, to make it easy, we could have a simple way for people to launch the application and see the change. To make it satisfying, we could recognize a person each week who does a great job of meaningful reviews and helps speed up the delivery of features. Conclusion We've explored the DORA report and how it measures teams' ability to deliver software. We've examined how habits are the foundation of meeting our goals/resolutions, looking at good and bad habits. Our challenge is to move from software developers to software craftspeople, using our daily habits to help us transform. References State of DevOps Report: https://cloud.google.com/devops/state-of-devops
DORA quick check assessment: https://dora.dev/quickcheck/
Forbes article on New Year's Resolutions Statistics: https://www.forbes.com/health/mind/new-years-resolutions-statistics/
5 Common Mistakes That Cause New Habits to Fail: https://jamesclear.com/habits-fail
Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits
Summary of the Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits-summary
Continuous Improvement - How It Works and How to Master It: https://jamesclear.com/continuous-improvement
Habits cheatsheets: https://jamesclear.com/atomic-habits/cheatsheet
Habit stacking: https://jamesclear.com/habit-stacking The lead image was generated using Microsoft Designer. Going from a mediocre team to an elite team can seem daunting, especially when we need to figure out where to start. The DevOps Research and Assessment (DORA) can be our north star, helping us build the habits and practices we need to be elite. We'll look at DORA, the challenges of building habits, and how to form habits that stick. What Is DORA? The DevOps Research and Assessment (DORA) report focuses on four key areas to measure elite teams: report report Lead time: How long does it take from code committed to running in production Deploy frequency: How often does our organization deploy to production Change fail percentage: How often do we need to rollback, patch, hotfix, or fix forward after a change Failed deployment recovery time: How long does it generally take to recover service Lead time: How long does it take from code committed to running in production Lead time: Deploy frequency: How often does our organization deploy to production Deploy frequency: Change fail percentage: How often do we need to rollback, patch, hotfix, or fix forward after a change Change fail percentage: Failed deployment recovery time: How long does it generally take to recover service Failed deployment recovery time: The challenge here is going from knowing about those four areas that need to be worked on so that we go from being a mediocre team to an elite squad scoring a ten on the DORA quick check. The four measurements of an elite team are: The four measurements of an elite team are: Lead time is less than one hour Deploy frequency is on-demand (multiple deploys per day) The change fail percentage is ideally 0% Failed deployment recovery time is less than one hour Lead time is less than one hour Lead time is less than one hour Deploy frequency is on-demand (multiple deploys per day) Deploy frequency is on-demand (multiple deploys per day) The change fail percentage is ideally 0% The change fail percentage is ideally 0% Failed deployment recovery time is less than one hour Failed deployment recovery time is less than one hour To see where tour team currently places, try the DORA quick check . DORA quick check DORA quick check This blog will focus on the tools, technologies, practices, culture, and philosophies that will help teams become elite. Improvements in our work take time since we need to break old habits that don't serve us well and build new ones. This blog will keep that in mind as we move through different topics. Each post will have an invitation to try out what we learn. If there are any questions or issues that need to be covered, make use of the comments section to submit the question. The Challenges of Forming New Habits We've all seen New Year's Resolutions and possibly have had some of our own. According to the Forbes report in 2024, 53% of those surveyed had given up on their New Year's Resolutions by the end of March. For many people, sticking to a new resolution or goal is challenging. There is now a day known as Ditch New Year's Resolution Day, which during 2024 fell on January 17th. While the media paints a picture of a significant stumbling block, statistics show it's less troublesome than perceived. We can see the reality of the quit rate in the chart below: Source Source Why Do People Fail in Their New Resolutions/Habits? In an article by James Clear, he outlines five reasons our new habits might fail: article article Trying to change more than one thing at a time Setting big goals without breaking them down into smaller steps Seeking a result, not the ritual We have not changed the environment in which we perform our good habits, so we quickly revert to our bad habits Assuming small changes don't add up Trying to change more than one thing at a time Trying to change more than one thing at a time Setting big goals without breaking them down into smaller steps Setting big goals without breaking them down into smaller steps Seeking a result, not the ritual Seeking a result, not the ritual We have not changed the environment in which we perform our good habits, so we quickly revert to our bad habits We have not changed the environment in which we perform our good habits, so we quickly revert to our bad habits Assuming small changes don't add up Assuming small changes don't add up However, there are ways to set ourselves up for success. In the book Atomic Habits , James talks about three key lessons : Atomic Habits three key lessons three key lessons Small habits make a big difference. Forget about setting goals. Instead, focus on the system. Build identity-based habits. Small habits make a big difference. Forget about setting goals. Instead, focus on the system. Build identity-based habits. The Impact of Habits Building identity-based habits means, for example, instead of saying I go running, we say we're runners, or instead of saying we paint, we say we're painters. There is a subtle difference in the wording, but if we start to think we're runners, that can lead to thinking, what does a runner do? It could mean changing the food we eat, how often we train, when we train, and the goals we set for ourselves. If we focus on getting 1% better every day in one year, we'll end up being 37 times better than when we started. It means that anything we set our mind to can profoundly impact us. It may not be noticeable at first, but as the changes compound over time, we will notice that we're a different person than when we started. Like a cliff being eroded over time by the waves, at the start, we overlook the impact each wave has, but over time, we see how the cliff face changes in its shape. How Do I Go About Creating and Maintaining Habits? In the Habits Cheatsheet , James Clear talks about the four laws to create a good habit: Habits Cheatsheet The 1st law (Cue): Make it obvious The 2nd law (Craving): Make it attractive The 3rd law (Response): Make it easy The 4th law (Reward): Make it satisfying The 1st law ( Cue ): Make it obvious Cue The 2nd law ( Craving ): Make it attractive Craving The 3rd law ( Response ): Make it easy Response The 4th law ( Reward ): Make it satisfying Reward As an example, let's say we've decided that we want to drink more water every day. We could make it obvious by placing a water bottle on our desk so that we can't miss it. Having a nice bottle or putting some lemon or mint in the water would be attractive. To make it easy, we fill the water bottle the night before so we don't have to think about it in the morning. Then, to make it satisfying, we could have a calendar above our desk where we put a sticker to mark each day that we've managed to empty our water bottle. How Do I Beat My Old Bad Habits? Again, in the Habits Cheatsheet, there are the inverse laws for avoiding our bad habits: Inversion of the 1st law (Cue): Make it invisible Inversion of the 2nd law (Craving): Make it unattractive Inversion of the 3rd law (Response): Make it difficult Inversion of the 4th law (Reward): Make it unsatisfying Inversion of the 1st law ( Cue ): Make it invisible Cue Inversion of the 2nd law ( Craving ): Make it unattractive Craving Inversion of the 3rd law ( Response ): Make it difficult Response Inversion of the 4th law ( Reward ): Make it unsatisfying Reward Let's say we want to watch less TV. We could make it invisible by placing the TV out of view, moving it to another room, or inside a cupboard. We might unsubscribe to our streaming accounts and TV subscriptions to make it unattractive. To make it difficult, we place the TV's power cord or remote control in another room. Finally, to make it unsatisfying, we could have an accountability partner that we check in with, with whom we will have to confess that we ended up watching TV. The Next Steps As we reflect on our DORA scores, we have an opportunity to identify areas where we can improve by forming new habits. The DORA quick check provides guidance on key areas we can work on to improve our score. In our team, we can decide what to work on to raise our score, moving us from developers to software craftspeople. Then, we can form habits to help us make lasting changes. For example, if we identify a need to reduce lead time, we may realize our review process is slowing us down. When we explore it, we recognize we need to set aside time to review the code. We could take a habit-stacking approach. For example, when we open our laptops in the morning (our current habit), we first review all of the pull requests that are pending review for us. Another could be first to review pull requests after our lunch break. habit-stacking pull requests To make it attractive, we might realize that the pull requests lack enough information, so we add a pull request template so all the information is there. Then, to make it easy, we could have a simple way for people to launch the application and see the change. To make it satisfying, we could recognize a person each week who does a great job of meaningful reviews and helps speed up the delivery of features. Conclusion We've explored the DORA report and how it measures teams' ability to deliver software. We've examined how habits are the foundation of meeting our goals/resolutions, looking at good and bad habits. Our challenge is to move from software developers to software craftspeople, using our daily habits to help us transform. References State of DevOps Report: https://cloud.google.com/devops/state-of-devops DORA quick check assessment: https://dora.dev/quickcheck/ Forbes article on New Year's Resolutions Statistics: https://www.forbes.com/health/mind/new-years-resolutions-statistics/ 5 Common Mistakes That Cause New Habits to Fail: https://jamesclear.com/habits-fail Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits Summary of the Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits-summary Continuous Improvement - How It Works and How to Master It: https://jamesclear.com/continuous-improvement Habits cheatsheets: https://jamesclear.com/atomic-habits/cheatsheet Habit stacking: https://jamesclear.com/habit-stacking State of DevOps Report: https://cloud.google.com/devops/state-of-devops https://cloud.google.com/devops/state-of-devops https://cloud.google.com/devops/state-of-devops DORA quick check assessment: https://dora.dev/quickcheck/ https://dora.dev/quickcheck/ https://dora.dev/quickcheck/ Forbes article on New Year's Resolutions Statistics: https://www.forbes.com/health/mind/new-years-resolutions-statistics/ https://www.forbes.com/health/mind/new-years-resolutions-statistics/ https://www.forbes.com/health/mind/new-years-resolutions-statistics/ 5 Common Mistakes That Cause New Habits to Fail: https://jamesclear.com/habits-fail https://jamesclear.com/habits-fail https://jamesclear.com/habits-fail Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits https://jamesclear.com/atomic-habits https://jamesclear.com/atomic-habits Summary of the Atomic Habits book by James Clear: https://jamesclear.com/atomic-habits-summary https://jamesclear.com/atomic-habits-summary https://jamesclear.com/atomic-habits-summary Continuous Improvement - How It Works and How to Master It: https://jamesclear.com/continuous-improvement https://jamesclear.com/continuous-improvement https://jamesclear.com/continuous-improvement Habits cheatsheets: https://jamesclear.com/atomic-habits/cheatsheet https://jamesclear.com/atomic-habits/cheatsheet https://jamesclear.com/atomic-habits/cheatsheet Habit stacking: https://jamesclear.com/habit-stacking https://jamesclear.com/habit-stacking https://jamesclear.com/habit-stacking The lead image was generated using Microsoft Designer. The lead image was generated using Microsoft Designer . Microsoft Designer Microsoft Designer

Elite Teams Are Built on Strong Habits

When in-game cheating becomes the norm, does the gaming industry have a major problem on its hands? A global study of the gaming industry would say yes. It was found that 77% of online gamers are likely to stop playing a multiplayer game online if they think other players are cheating, and 48% of online gamers are likely to buy less in-game content. Add in the accrued value of digital assets as a key feature of blockchain gaming, and developers have an obligation to tackle this problem head-on. An attractiveness to bending the rules is not something limited to the world of online gaming; it is rife in all parts of society. However, as social psychologist Corey Butler points out ‘anonymity (playing with strangers or online) and opportunity can tip the scales toward greater cheating. When strong incentives like money or grades are on the line, otherwise honest people might be tempted to cheat. If somebody with a competitive nature is presented with the opportunity to easily outperform the other at a task, then it's safe to say that many will bite the bullet and risk the reward for the easy win—factor in the monetary value of rewards in Web3 gaming, and this desire to win increases significantly. However, when it comes to multiplayer online games, the competition is designed around entertainment, fun, and the community. These core values of gaming make cheating a stain on the industry as a whole. Cheating is the new norm. Cheating in some of the largest games has become an economy of its own, with many platforms and YouTube channels dedicated to introducing cheating, hacks, and navigating the ways to cheat. Don't believe us, simply type fortnite cheat terms into a google search. Combating this trend is critical for maintaining the reputation of these brands. Simon Vieira, CEO of MixMob, a Solana-based gaming platform, believes the temptation to cheat is rife, but it is nothing new, “Web3 games offer enhanced incentives due to the tangible value of game coins and digital items. However, this also creates a greater temptation to cheat. That said, traditional gaming has previously addressed similar issues. For instance, real money gaming employs methods such as biotic randomness to obscure certain game aspects like matchmaking. This approach reduces predictability, thus diminishing the incentives to cheat while still maintaining a skill-based gaming environment. We apply these strategies at MixMob to ensure fairness and keep the game engaging for all players,” says Vieira. When hacking games, cheaters now have an endless stack of tools to choose from when it comes to infiltrating game mechanics with glitching and farming to using aimbots in the software and speed hacks. This problem is exacerbated in Web3 gaming as it lacks an authoritative host. “Fair play is crucial in multi-player games as it directly impacts player engagement and retention. A fair environment ensures that players feel valued and that the game remains competitive and enjoyable for everyone,” notes Vieira. Furthermore, with AI, it is easier than ever to predict patterns of player behavior and create new ways to exploit and manipulate gaming data. So, how can this problem be addressed without compromising the gaming experience? Speaking to Tashi Protocol CEO Sandeep Bhatia, it is clear that consensus will play a future role in blockchain gaming. “Dynamite as the network transport for multiplayer games can prevent certain forms of cheating like 'lag switching' or local state hacking. The benefit of having consensus on top of a peer-to-peer network layer ensures that players cannot cheat, and the architecture reduces costs.” Frustration with the publishers Publishers are tackling the issue of one player, or several players at a time, by banning them and using anti-cheat software. Just last month, Activision, a gaming giant and creator of Call of Duty, banned 27,000 accounts from the game. However, this isn't deterring new cheats coming into the sector. Tackling it from the outset in the process of the game studio is the only way to ensure that both the publishers and the gamers benefit in the long run. To restore confidence, creators of blockchain games must demonstrate trust from the outset. “Shifting from a traditional gaming infrastructure to adopt a decentralized, serverless framework will optimize the entire Web3 gaming experience and solve the issue of cheating from the ground up. Not only can we reduce the costs by eliminating the need for centralized servers, but Tashi's Dynamite ensures fair distribution and protection against common security threats,” says Bhatia. Once a player sees that a game is compromised, it ruins the fun element and may even deter them from entering the environment because of security fears. In addition, the influx of bots and other hacks has led to unfair advantages within some of the most loved games. What can blockchain game publishers do? Gaming studios must take the necessary steps to demonstrate their commitment to fair play. This is essential in the blockchain space as it continues to build trust with the traditional gaming communities. At MixMob, they leverage blockchain transparency to allow the community to participate in monitoring and reporting cheaters actively. “This community refereeing not only helps maintain fairness but also fosters a sense of responsibility and integrity among players, and it has worked great for us,” says Vieira. “Web3 game publishers must take decisive steps to limit cheating. The actions taken should vary based on the severity of the cheating incident. Potential measures include banning, suspending, or permanently removing players involved in unfair practices. Additionally, publishers can adopt proven strategies from traditional gaming, such as introducing randomness to some parts of the game to reduce predictability, which helps deter cheating,” he continues. Game developers who are keen to implement anti-cheat measures are often outplayed by hackers who have mastered the art of cheating and the avoidance of detection. Sure, developers can ban cheaters who are caught in the act or embed cheat detection software. However, this doesn't prevent cheating from occurring from the outset. The vulnerabilities have already been exploited by the time the developer has their hands on the activities. If, however, a game creator starts the development process using the Tashi Consensus Protocol, it has eliminated the act of cheating from the initial design stage. “Gamers rely on trust that game developers would have implemented the best practices to ensure cheaters are punished. That is why Tashi works to educate all its gaming partners on the novel ways blockchain solves cheating issues. We make our tech easy to use and guide all our partners who might come from the Web2 world and are new to using blockchain tech,” added Bhatia. While anti-cheat software like Riot Game's Vanguard or Activision Blizzard's Ricochet stands as the frontline defense, the second layer can utilize the transparency provided by blockchain technology to fight against bad actors. Implementing innovative approaches to game development, like the Tashi Dynamite Consensus Engine, pushes gaming to a new era of fair play and reclaims the values that true gamers want to see in the game development stage. In addition to fostering a culture of fair play, a paradigm shift is necessary in the approach to combating cheating in online gaming. By 2027, the number of users in the Online Games market is expected to amount to 1.2bn users. The projected revenue in the Online Games market worldwide is expected to reach US$27.97bn in 2024. Reclaiming the gaming sector for true gamers who value the entire gaming experience is crucial as blockchain games position themselves alongside some of the gaming giants. When in-game cheating becomes the norm, does the gaming industry have a major problem on its hands? A global study of the gaming industry would say yes. It was found that 77% of online gamers are likely to stop playing a multiplayer game online if they think other players are cheating, and 48% of online gamers are likely to buy less in-game content. Add in the accrued value of digital assets as a key feature of blockchain gaming, and developers have an obligation to tackle this problem head-on. study study An attractiveness to bending the rules is not something limited to the world of online gaming; it is rife in all parts of society. However, as social psychologist Corey Butler points out ‘anonymity (playing with strangers or online) and opportunity can tip the scales toward greater cheating. When strong incentives like money or grades are on the line, otherwise honest people might be tempted to cheat. If somebody with a competitive nature is presented with the opportunity to easily outperform the other at a task, then it's safe to say that many will bite the bullet and risk the reward for the easy win—factor in the monetary value of rewards in Web3 gaming, and this desire to win increases significantly. However, when it comes to multiplayer online games, the competition is designed around entertainment, fun, and the community. These core values of gaming make cheating a stain on the industry as a whole. Cheating is the new norm. Cheating in some of the largest games has become an economy of its own, with many platforms and YouTube channels dedicated to introducing cheating, hacks, and navigating the ways to cheat. Don't believe us, simply type fortnite cheat terms into a google search. Combating this trend is critical for maintaining the reputation of these brands. Simon Vieira, CEO of MixMob, a Solana-based gaming platform, believes the temptation to cheat is rife, but it is nothing new, “Web3 games offer enhanced incentives due to the tangible value of game coins and digital items. However, this also creates a greater temptation to cheat. That said, traditional gaming has previously addressed similar issues. For instance, real money gaming employs methods such as biotic randomness to obscure certain game aspects like matchmaking. This approach reduces predictability, thus diminishing the incentives to cheat while still maintaining a skill-based gaming environment. We apply these strategies at MixMob to ensure fairness and keep the game engaging for all players,” says Vieira. When hacking games, cheaters now have an endless stack of tools to choose from when it comes to infiltrating game mechanics with glitching and farming to using aimbots in the software and speed hacks. This problem is exacerbated in Web3 gaming as it lacks an authoritative host. “Fair play is crucial in multi-player games as it directly impacts player engagement and retention. A fair environment ensures that players feel valued and that the game remains competitive and enjoyable for everyone,” notes Vieira. Furthermore, with AI, it is easier than ever to predict patterns of player behavior and create new ways to exploit and manipulate gaming data. So, how can this problem be addressed without compromising the gaming experience? Speaking to Tashi Protocol CEO Sandeep Bhatia, it is clear that consensus will play a future role in blockchain gaming. “Dynamite as the network transport for multiplayer games can prevent certain forms of cheating like 'lag switching' or local state hacking. The benefit of having consensus on top of a peer-to-peer network layer ensures that players cannot cheat, and the architecture reduces costs.” Frustration with the publishers Publishers are tackling the issue of one player, or several players at a time, by banning them and using anti-cheat software. Just last month, Activision , a gaming giant and creator of Call of Duty, banned 27,000 accounts from the game. However, this isn't deterring new cheats coming into the sector. Activision Activision Tackling it from the outset in the process of the game studio is the only way to ensure that both the publishers and the gamers benefit in the long run. To restore confidence, creators of blockchain games must demonstrate trust from the outset. “Shifting from a traditional gaming infrastructure to adopt a decentralized, serverless framework will optimize the entire Web3 gaming experience and solve the issue of cheating from the ground up. Not only can we reduce the costs by eliminating the need for centralized servers, but Tashi's Dynamite ensures fair distribution and protection against common security threats,” says Bhatia. Once a player sees that a game is compromised, it ruins the fun element and may even deter them from entering the environment because of security fears. In addition, the influx of bots and other hacks has led to unfair advantages within some of the most loved games. What can blockchain game publishers do? Gaming studios must take the necessary steps to demonstrate their commitment to fair play. This is essential in the blockchain space as it continues to build trust with the traditional gaming communities. At MixMob, they leverage blockchain transparency to allow the community to participate in monitoring and reporting cheaters actively. “This community refereeing not only helps maintain fairness but also fosters a sense of responsibility and integrity among players, and it has worked great for us,” says Vieira. “Web3 game publishers must take decisive steps to limit cheating. The actions taken should vary based on the severity of the cheating incident. Potential measures include banning, suspending, or permanently removing players involved in unfair practices. Additionally, publishers can adopt proven strategies from traditional gaming, such as introducing randomness to some parts of the game to reduce predictability, which helps deter cheating,” he continues. Game developers who are keen to implement anti-cheat measures are often outplayed by hackers who have mastered the art of cheating and the avoidance of detection. Sure, developers can ban cheaters who are caught in the act or embed cheat detection software. However, this doesn't prevent cheating from occurring from the outset. The vulnerabilities have already been exploited by the time the developer has their hands on the activities. If, however, a game creator starts the development process using the Tashi Consensus Protocol, it has eliminated the act of cheating from the initial design stage. “Gamers rely on trust that game developers would have implemented the best practices to ensure cheaters are punished. That is why Tashi works to educate all its gaming partners on the novel ways blockchain solves cheating issues. We make our tech easy to use and guide all our partners who might come from the Web2 world and are new to using blockchain tech,” added Bhatia. While anti-cheat software like Riot Game's Vanguard or Activision Blizzard's Ricochet stands as the frontline defense, the second layer can utilize the transparency provided by blockchain technology to fight against bad actors. Implementing innovative approaches to game development, like the Tashi Dynamite Consensus Engine, pushes gaming to a new era of fair play and reclaims the values that true gamers want to see in the game development stage. In addition to fostering a culture of fair play, a paradigm shift is necessary in the approach to combating cheating in online gaming. By 2027, the number of users in the Online Games market is expected to amount to 1.2bn users. The projected revenue in the Online Games market worldwide is expected to reach US$27.97bn in 2024. Reclaiming the gaming sector for true gamers who value the entire gaming experience is crucial as blockchain games position themselves alongside some of the gaming giants.

Is It Game Over for Cheaters? Using Blockchain Technology to Eliminate Unwanted Gaming Behavior

In this article, we will take a look at the Erlang ecosystem, focusing on the underlying architecture of Elixir and Erlang, two functional programming languages, and see how they utilize a shared runtime system known as BEAM for code execution To grasp the full potential and innovation behind Erlang and it's crucial to delve into their origins and the principles that guide their development. Elixir, The development of began in the mid-1980s in . At that time, Erlang was designed to provide a better way to "build telephone applications"[1]. It was developed for writing that can run without interruption. Erlang Ericsson's laboratory concurrent programs What makes Erlang exceptionally , as well as , is its process-based approach. These processes do not share memory and can communicate with each other using asynchronous messages. Processes can also restart each other, which allows for easy system recovery in case of errors. These processes belong to the programming language rather than the operating system. In addition to sending and receiving messages and commands among themselves, they can also send them outside the kernel, allowing the system to scale by adding more processing units. Erlang also has a mechanism for changing code within the program without stopping its execution called . concurrent and scalable fault-tolerant hot code swapping is a dynamic created for building and , with prominent applications in , , and development[2]. It was created by José Valim in 2011 to offer a solution to common concurrency issues in programming that he faced during the time he worked as a Ruby/Rails developer[3]. At the same time, the intention was to achieve the competitive robustness of Erlang. Therefore, Elixir was developed based on the Erlang Virtual Machine (BEAM), inheriting Erlang's capabilities for creating resilient, distributed applications. The interoperability of Elixir and Erlang is further facilitated since both languages compile into a common bytecode format, allowing seamless integration and use of libraries from both languages. Elixir functional language scalable maintainable applications communication networks real-time systems web application (ERTS) compiles the original Erlang program code into bytecode, which is then executed on , Erlang's virtual machine. BEAM runs as a single process of the operating system (OS), and unless specified otherwise, the number of threads that this process executes corresponds to the number of OS cores[4]. BEAM does not have any information about system information or OS processes but serves only to execute commands that are written in special registers. All processes implemented within Elixir or Erlang are fully executed by BEAM, on just one OS process. compared to threads and processes of the operating system, which allows for the creation of many such processes where each performs its task, isolated from the rest of the program. BEAM efficiently allocates and manages these lightweight processes through its scheduler threads. in BEAM are designed to dynamically distribute tasks (processes) across available cores, thus optimizing program execution without unnecessary load on a single core. The Erlang Runtime System BEAM These processes are small and lightweight Scheduler threads To wrap up, understanding the architecture that underpins Elixir and Erlang offers fascinating insights into how these languages manage to achieve remarkable levels of concurrency, scalability, and fault tolerance. From Erlang's original design to revolutionize the development of telephone applications to Elixir's creation for enhanced maintainability and scalability in modern applications, both languages demonstrate the power of functional programming in managing complex, distributed systems with ease. References https://www.labouseur.com/courses/erlang/history-of-erlang-armstrong.pdf https://elixir-lang.org https://semaphoreci.com/blog/elixir-creator-jose-valim https://www.erlang.org/blog/a-brief-beam-primer

Inside BEAM: How Elixir and Erlang Leverage a Shared Runtime for Resilient Applications

Do you love working with arrays in ? They are awesome for storing and managing multiple values in one variable. But sometimes, you may have a problem with duplicate objects in your array. This can mess up your code’s performance, memory, and logic. JavaScript Don’t worry; I have some solutions for you! Use a set() to get rid of duplicate objects in your array Use a map to filter out duplicate objects in your array Use Lodash to simplify the process of removing duplicate objects in your array In this blog, you will learn how to do all these things! Method 1: Using to remove duplicate set() The sets are awesome! is one of the . They let you store unique values of any kind. You can even put objects in them. How cool is that? To make a set from an array, use the new Set() non-primitive data types in JavaScript Set() Here’s an example of using Set() to remove duplicate numbers: const numbers = [1, 2, 3, 4, 5, 1, 2, 3];
const uniqueNumbers = new Set(numbers);
console.log(uniqueNumbers); 
// Output: { 1, 2, 3, 4, 5 } Look at this! The set has no duplicates from the . How cool is that? You can turn the set into an array again with or the array Array.from() spread operator (…). Here’s how you do it: const numbers = [1, 2, 3, 4, 5, 1, 2, 3];
const uniqueNumbers = new Set(numbers);
const arrayFromSet = Array.from(uniqueNumbers);
console.log(arrayFromSet); 
// Output: [ 1, 2, 3, 4, 5 ]

const arrayFromSpread = [...uniqueNumbers];
console.log(arrayFromSpread); 
// Output: [ 1, 2, 3, 4, 5 ] Here’s a cool trick to get rid of duplicates in a JavaScript array. Make a set from the array and turn it back into an array. Like this: You might think you can use to remove duplicates from an array of objects. Let's try: Set() const colors = [
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 2, name: "Green", hexCode: '#00FF00' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
  { id: 1, name: "White", hexCode: '#000000' },
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
];
const uniqueColors = [...new Set(colors)];
console.log(uniqueColors);
/*
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 2, name: "Green", hexCode: '#00FF00' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
  { id: 1, name: "White", hexCode: '#000000' },
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
*/ But that won’t work. Why? Because doesn’t care about the properties of the objects. The only care about their references. That means two objects that look identical but have different references are not identical for . For example: Set() Set() set() const color1 = { id: 1, name: "Red", hexCode: '#FF0000' };
const color2 = { id: 1, name: "Red", hexCode: '#FF0000' };
console.log(color1 === color2);
// Output: false In the above code, and look the same, but they are not. They live in different places in the computer’s memory. So, thinks they are different, too, and keeps them both. color1 color2 Set() But don’t worry; there are other ways to remove objects that look the same. You can use an or . You will see this in detail in the next sections. map Lodash The advantages of this method are: It is simple and easy to use It is fast and efficient Work only with value types The disadvantages of this method are: It does not work with objects It does not allow you to specify a custom criterion for uniqueness Method 2: Remove duplicate objects from an array using a Map() A is like a table with two columns: one for and one for . You can use any value as a key or a value, even an object. To make a map from an array, you need a function that tells how to fill the table. The function takes an element and its position in the array and returns a pair of keys and values. For example: map() keys values const numbers = [1, 2, 3, 4, 5, 1, 2, 3];
const mapFromNumbers = new Map(numbers.map((n, index) => [n, index]));
console.log(mapFromNumbers);
//  Output: Map { 1 => 5, 2 => 6, 3 => 7, 4 => 3, 5 => 4 } The map has the array’s values as keys and their last positions as values. You can make the map an array again with or Array.from() spread operator (…) For example: const numbers = [1, 2, 3, 4, 5, 1, 2, 3];
const mapFromNumbers = new Map(numbers.map((num, index) => [num, index]));
const arrayFromMap = Array.from(mapFromNumbers);
console.log(arrayFromMap); 
// Output: [ [ 1, 5 ], [ 2, 6 ], [ 3, 7 ], [ 4, 3 ], [ 5, 4 ] ]

const arrayFromSpread = [...mapFromNumbers];
console.log(arrayFromSpread); 
// Output: [ [ 1, 5 ], [ 2, 6 ], [ 3, 7 ], [ 4, 3 ], [ 5, 4 ] ] Here’s a cool trick to get rid of duplicates in a JavaScript array. You make a from the array and then turn it back into an array. Like this: map const colors = [
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 2, name: "Green", hexCode: '#00FF00' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
  { id: 1, name: "White", hexCode: '#000000' },
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
];

const mapFromColors = new Map(
  colors.map(c => [c.id, c])
);

const uniqueColors = [...mapFromColors.values()];
console.log(uniqueColors);
/* Output:
[ {"id":1,"name":"Red","hexCode":"#FF0000"},
  {"id":2,"name":"Green","hexCode":"#00FF00"},
  {"id":3,"name":"Blue","hexCode":"#0000FF"}
] */ The advantages of this method are: It is flexible and customizable. It allows you to specify a custom criterion for uniqueness, such as a property or a function. The disadvantages of this method are: It is more complex and verbose. It may not work with complex objects that have circular references or non-primitive keys. Method 3: Remove duplicate objects from an array using the Lodash library is awesome! It’s a JavaScript library that helps you do many things with data. You can use to manipulate arrays, objects, , numbers, and more. It’s easy to get in your project. You can use npm or a CDN to install and import it. Lodash Lodash JavaScript strings Lodash Here’s how to add the reference to the Loadsh library: // Using npm
npm install --save lodash
const _ = require("lodash");

// Using CDN
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js"></script> Do you want to remove duplicate objects from an array? You can use Lodash’s method. It’s easy and powerful. You just need to give it two things: the and the or the criterion. _.uniqBy() array property The property is a key of the object, like a string or a symbol. The criterion is a function that returns a value to compare. Here’s an example of how to remove duplicate objects from an array using Loadsh: const colors = [
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 2, name: "Green", hexCode: '#00FF00' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
  { id: 1, name: "White", hexCode: '#000000' },
  { id: 1, name: "Red", hexCode: '#FF0000' },
  { id: 3, name: "Blue", hexCode: '#0000FF' },
];

const uniqueColorsById = _.uniqBy(colors, "id");
console.log(uniqueColorsById);

/* Output:
[ {"id":1,"name":"Red","hexCode":"#FF0000"},
{"id":2,"name":"Green","hexCode":"#00FF00"},
{"id":3,"name":"Blue","hexCode":"#0000FF"}]
*/ The advantages of this method are: It is convenient and readable It provides many options and features for removing duplicates The disadvantages of this method are: It requires an external dependency It may not be compatible with older browsers or environments Best practices for working with arrays and objects in JavaScript Check the length and type using the JavaScript typeof keyword before doing anything with it. Use to declare your variables unless you need to change them. const Use clear and meaningful names for your variables and functions. End your statements with semicolons. Compare values with (`= `) strict equality operators ` and `! Test and verify your code with or other debugging tools. console.log() Conclusion You just learned a cool skill! You can now remove duplicate objects from an array in JavaScript. How awesome is that? There are different ways to do this. You learned three of them: using a set, a map, or Lodash. Each duplicate removal method has its pros and cons. If you want to remove duplicate value types from an array, you can Set() method. If you want to remove duplicate objects from an array, use Map() or Loadsh method. I hope you learned something new from this blog. I would love to hear your thoughts or questions in the comments. Also published . here

Mastering JavaScript Arrays: Eliminating Duplicate Objects

Every year, there are registered ice hockey players in Canada. Almost none of them will ever sniff the NHL, professional hockey’s highest level. more than 500,000 Less than 8,000 players have ever suited up for an NHL game, each considered among the sport's elites. Getting to that point in any career should be considered a success, but what about those with their sights set even higher? Chris Pronger, a recent guest on the , is one of 294 players in the Hockey Hall of Fame and one of only eight defensemen to ever win the Hart Trophy, awarded to the league’s most valuable player. Success Story Podcast After a long, successful playing career, he has transitioned into the business world and now operates with his wife, Lauren. Well Inspired Travels I wanted to pick his brain about true greatness and how he never stopped trying to improve. The endless pursuit I know this might shock you, but I’m not quite as athletic as Chris. So when I think about playing in the NHL, that seems like enough. Suiting up for your hometown team, listening to the crowd cheer as you hit the ice. It would be one of the most exhilarating feelings in the world. But there seems to be a common theme for the ones that reach the very peak of any industry. Good was never good enough. Michael Jordan, arguably the most significant sports icon in history, would famously focus on his failures more than his successes: “I’ve missed more than 9,000 shots in my career. I’ve lost almost 300 games. Twenty-six times I’ve been trusted to take the game-winning shot and missed. I’ve failed over and over and over again in my life. And that is why I succeed.” Chris referenced the same mindset, using every missed assignment or fumbled pass to fuel his training. As a reason to go to work every day. As the inspiration to improve. It’s that kind of never-ending that I’m interested in. How can the rest of us learn from these high-level performers? What can we take back to our own pursuits (ones that might not necessarily be televised)? growth Turn up the difficulty One of the most interesting parts of our conversation wasn’t even about business or the NHL. We discussed how he chose to play junior hockey in the CHL instead of following his brother’s footsteps to college (CHL contracts make a player ineligible for the NCAA). He immediately pointed out that it allowed him to play against Eric Lindros, the “next big thing” in hockey. Lindros played for the Oshawa Generals, just a short drive from Chris’s Peterborough Petes. Putting yourself up against the best, making it as hard as possible, gives you the ammunition needed to improve. It could have proven too difficult and ended his career before it started. But instead, it allowed him to hone his skills and improve at a greater pace. Recognizing opportunity These opportunities exist for us as well. Whether it’s chasing a new title at a different company, volunteering to lead a major project, or starting your own business. You have to be able to recognize them, though, and be ready to jump through the door as soon as it opens. Leaning in When an opportunity presents itself, making the most of it requires total commitment and a proactive approach. Here are five ways to fully "lean in" to any opportunity: Take the time to learn everything you can, including potential benefits and risks. Do your research: Recognize these emotions, acknowledge their source, and consciously choose not to let them overpower you. Embrace failure as a learning experience and remind yourself that not taking action is often the biggest risk of all. Overcome fear and self-doubt: Networking can open doors to new opportunities, while collaboration can enhance the value of those opportunities by pooling knowledge, resources, and ideas. Actively seek out opportunities to meet and engage with like-minded individuals and organizations. Network and collaborate: Embrace this challenge by being open to new ideas, willing to learn from others, and prepared to pivot if necessary. Adopt a flexible and adaptable mindset: Once you have decided to pursue an opportunity, set specific, measurable, achievable, relevant, and time-bound (SMART) goals as a roadmap to success. Break these goals into smaller, actionable steps that can be tackled individually. Set clear goals and take action: Commit to taking consistent action, track your progress, and celebrate your wins. This goal-setting and action-taking approach will keep you focused, motivated, and ready to lean into the opportunity. Escaping mistakes But not every path taken is the right one. Sometimes, you make a mistake and pursue something that was never meant to be. You know what, though? That's totally okay. Mistakes are just a part of being human and can be pretty valuable. Instead of beating yourself up, try looking at it as a learning opportunity. After all, we wouldn't grow or improve without making a few wrong turns here and there. Grab that lesson, tuck it under your arm, and use it to make better choices. Talent’s not enough No matter how often I hear it, I’m still shocked when an all-time great athlete talks about what got them to the highest level. They never talk about how they are lucky enough to have more talent than the rest of the competition. It’s always about their work, the coaching they received, and a mentor that taught them the “right way to do it.” It reminds me of a Calvin Coolidge quote: “Nothing in the world can take the place of persistence. Talent will not; nothing is more common than unsuccessful men with talent.” Innate ability helps, sure. But it won’t get you all the way. Surround yourself with greatness Just like when Chris went up against the best competition, he also got close to the people already at the level he was chasing. When the St. Louis Blues traded for him, he immediately latched onto Al MacInnis, another one of the greatest NHL defensemen of all time, who was in the latter part of his career. Chris credits him for putting him on the track to true elite status. The mentor relationship Mentorship is valuable at all levels. Most of us understand that already, but so few of us seek out experienced help. A few years ago, Olivet Nazarene University published a study showing 76% of respondents believed a mentor was important, but . only 37% admitted having one That disconnect likely comes from our fear of vulnerability. We naturally avoid situations that give us a sense of fear, anxiety, or danger. Opening up to a mentor can be all those things, even when the relationship works properly. But it is also one of the only ways to unlock your full potential because an experienced leader can see things you will never recognize in yourself. Stay humble Too often, the ego can get in the way; of mentorship, of personal growth, of maximizing potential. Chris used a phrase obviously taken from some personal experience. “A lot of people think they’re working hard until they’re next to someone who is.” It’s easy to fall into the trap of self-aggrandizing. Patting yourself on the back, even if it was not your best effort. When you’re put face-to-face with someone whose work ethic dwarfs your own, it can be a shock. But it can also be inspiring if you are humble enough to recognize it. The Success Story podcast is that tool for me. Sitting down and talking with an expert rejuvenates my work ethic and makes me double down. That only works, though, if you’re willing to admit that there is room for growth. Stay humble, and let others show you the limit. Adapt tradition That doesn’t mean you have to follow everyone’s advice. The elite of the elite don’t get there through tried-and-true means. They adapt, innovate, and find new ways to get even more out of traditional methods. Take time-tested practices and infuse them with fresh perspectives, innovative ideas, and modern technology. The result often improves efficiency, effectiveness, and success. By building upon the strong foundations of these established techniques and remaining open to change, we can create a powerful synergy between old and new strategies. This fusion enables us to tackle contemporary challenges, capitalize on evolving opportunities, and remain competitive in a constantly changing landscape. Final thoughts Not everyone is going to reach the top 0.1% of their field. But you can still learn a lot from those who do. They never luck into that success. It’s a mixture of hard work, circumstance, and preparation. Talent’s not enough. If you want to hear more from Chris, including his thoughts on investment strategies and financial planning for athletes, check out the full interview on the Success Story YouTube channel. Otherwise, I’ll be back next week with some more insights. Remember, keep your head up and your stick on the ice! If you enjoyed this article, I’d love to hear from you. Also published here.

Talent Can Only Take You So Far: Lessons on Elite Performance

Let's face it: for the business world, automation is like the flashy new $5,000 Weber barbecue you saw in your neighbor's yard last summer. You bought it because it seemed like the 'thing to do', but when it arrived at your doorstep, you realized – I've got no freaking idea how to use this thing. So, you did what most people do: threw some meat on there and hoped for the best. And look, the meat was edible. It just wasn't as good as it could have been. (And it definitely wasn’t medium-rare). I feel like so many of us have started using these automated tools without knowing how to truly utilize their potential. For a lot of businesses, the result has been an over-implementation and over-reliance on these tools, to the point where they've become completely counter-productive to our goals. So the question is, how can we strike a balance between automating our sales process and still maintaining that all-important human touch? In my opinion, we simply need more guidance. I brought onto the show to help us all out. Shawn Finder Shawn Finder, CEO of Autoklose Ever heard of a friendly platform called Autoklose? It's an AI-powered sales engagement platform that helps sales reps take the repetitive, mundane tasks out of their day-to-day so they can focus on selling, building relationships – and ultimately – closing more deals. Shawn is the definition of an intelligent seller. I interviewed him on the Success Story podcast last year (you can listen to it ) and all throughout our conversation, he emphasized the importance of personalization. That's pretty rare for an automation guru, believe it or not. here At just 24, Shawn stepped into the entrepreneurial world and never looked back. He started out importing packaging from the Orient and selling it to top retailers in North America. With sales being his passion, Shawn founded the list-building company ExchangeLeads in 2013; the platform helped salespeople build quality prospect lists in far less time. In early 2018, Shawn parlayed ExchangeLeads into his second startup called Autoklose, which is a new, revolutionary sales automation platform used by thousands of sales professionals around the world to help them save both their time and money. He scaled Autoklose to 50+ people and sold it to Vanillasoft a Soft in 2020. This is exactly why I brought Shawn onto the show; he's lived and breathed sales since he was a young entrepreneur. And now, he's using his experience to build an incredible company that's changing the sales landscape as we know it. But we'll circle back to him soon. What's the Problem With Automation? I just found out that are using automation somewhere along their marketing pipeline. Some have even automated the whole darn thing. over half of companies Why? Because without sounding cringeworthy, automation really is the future. We're not living in the days of Henry Ford's factory anymore; his moving assembly line has gone digital, and the sales tasks we used to dread can now be completed with the click of a button. But here's the thing: even though sales automation has come a long way, it's not a stand-in for your human sales team. It can't empathize, it can't automatically add our 'human' touches like social personalization, and it can't build relationships (unless you're Joaquin Phoenix in the movie Her. But even then I'm not convinced). The Crux of the Matter Over-reliance on automation is a real problem for sales teams. It was great at first, but now everyone kind of sounds... well, we sound exactly the same. Our cold customers can smell an automated email from a mile off. Keep in mind that there are only a few reasons why someone will shell out their hard-earned money – and disingenuous sales pitches are not one of them. Think about the sales emails you actually open when they pop into your inbox. I'm willing to bet it's the ones that sound different or the ones that seem to eerily know lots of information about you. In other words, the ones that sound like they were written by a real person – for you, and you alone. So, what's the deal here? Do we ditch automated emails altogether, or is there a balance we can strike? Top Tips From Shawn Finder Now, I'm well aware that the term 'automation' covers so much more than a sales email campaign. In the interest of today's topic, though, I'm specifically talking about sales marketing automation; think campaigns, funnels, cold emails, and the like. Shawn and I talked about so many things in our interview, but we devoted a fair chunk to discussing his top tips for automating sales emails without eliminating the human touch. 1. Keep It Short “I think the biggest mistake people make with automation is they keep everything long and depersonalized. You can write an automated email and make it feel like it's a one-to-one email – and you can make it very short.” I absolutely love this tip because it taps into something we've all forgotten since automation took the reins, which is this: just because emails take less time to write and send these days does not mean they should be any less value-packed. It's tempting to say, 'Great! Emails take 90 percent less time now, so I'll pack in as much extra information as possible.' But the reality is that no one wants to read a 2,000-word email, no matter how good your copy is or how consistently you send them. 2. Personalize the Heck Out of Emails “I actually wrote 30 of the top sales podcasts an email; it was very personalized. All 30 replied and said, ‘Yeah, I'd love to have you on the show.’ Everyone thought it was a one-on-one email. So it all depends on if you're being salesy, or genuine and personable.” Yes, I was one of the people Shawn reached out to – and I said yes, so it evidently worked! Hah. “People just rely on the automation, and they write long emails selling their product – ’My name is Shawn, I'm a company that does ABC, I can help you with a, b and c’– it doesn't work," Shawn explained. To explain this in a bit more detail, imagine you received an email from me. There's a big difference between this: Hi [recipient], Welcome to the newsletter! Here at Scott D Clary, we talk about all things sales and marketing. If you are in the market for some helpful resources, be sure to check out our blog. Our company started in 2010 and we have been in the industry for even longer than that. With a driven team of experts, we are confident that we can provide you with the best resources and advice possible. ...and this: Hey Scott, Just wanted to drop you a quick note and say thanks for subscribing to my newsletter. I know you're busy hustling and doing your thing, so I'll get right to it: if you're ever in need of a helpful resource on sales or marketing, be sure to check out my blog. You seem like just the kind of person who'd be interested! See the difference? The first email is full of impersonal fluff, while the second is direct, personal, and to the point. Even if you sent that one email to 500 people, they would all feel like you were writing just to them. 3. And Be Strategic About It! This is a bit of an extension on the previous tip; Shawn told me about one of his own automation efforts that is absolutely genius. “I had a webinar of 540 people, but we had 26 people that were named Michael. And I made a video saying, ‘Hey, Michael, I just want to thank you for coming to the webinar yesterday, and for your input.’ And Michael received it thinking it was one-to-one, but it was sent to 26.” How sneaky and strategic is that? People love to see and hear their own name – it's a psychological trigger that gets us to pay attention. By spending a little extra time to group people with similar names, Shawn basically had his cake and ate it, too; he saved time through automation, but still gave each person that important feeling of being seen and heard. “The key is personalization; you need to make that prospect feel like it's a one-to-one, even if it's not.” 4. Use Intangible Touches And for our final tip of the day, I'm sharing this term Shawn introduced to me during our interview: intangible touches. Basically, this is anything you can do to make a prospect feel special without it being a huge time suck. Shawn uses them at the company he's currently running. “We email, we add them as a connection on LinkedIn, we send them a message, and then we do another email; the then we'll what I like to call ‘intangible touches’, which could be to comment on Scott's podcast and give feedback as a comment.” It's the perfect sandwich of engagement – a little personalization, a little human connection, and then more content to keep them coming back for more. The main thing is to make sure your prospects are seeing your name pop up everywhere they look. For instance: if I had a list of ten high-value potential clients that I really, really wanted to land, I could send them an automated email sequence. But I could also make sure to drop a personal comment on one of their LinkedIn posts that same week – and then follow up with an email referencing that comment, if I had the time, or even just another automated email that looks and sounds personalized. The key is to make sure that your prospects are seeing your name in multiple places. When they get a sales pitch from you, they'll think, "I know that name. He commented on my post last week. He's been emailing me helpful information." And that, my friends, is the recipe for a sale. Wrap Up If you're in the world of sales, is one you really can't afford to miss. He's sitting on a wealth of knowledge and experience; we talked about his serial entrepreneurship, how to scale, pivoting from company to startup, and so much more. my interview with Shawn I hope the four tips I shared with you today help get your creative juices flowing about how you can use automation in your sales process. Just remember: don't eliminate the human element, be strategic, and use intangible touches to make your prospects feel special. Automation is a wonderful tool, but no automation is an island. Pair it with a healthy dose of personalization, human connection, and good old-fashioned elbow grease, and you'll be closing deals in no time.

Automate, But Don't Eliminate: We Still Need A Human Touch

Automatice, pero no elimine: aún necesitamos un toque humano

Automatisez, mais n'éliminez pas : nous avons toujours besoin d'une touche humaine

स्वचालित करें, लेकिन समाप्त न करें: हमें अभी भी एक मानवीय स्पर्श की आवश्यकता है

自動化しますが、排除しないでください: まだ人間のタッチが必要です

Automatize, mas não elimine: ainda precisamos de um toque humano

Tự động hóa, nhưng không loại bỏ: Chúng ta vẫn cần sự tiếp xúc của con người

自动化，但不要消除：我们仍然需要人性化

Revolutionizing Healthcare: Andy Schoonover's Playbook for Disrupting Entrenched Industries

বিপ্লবী স্বাস্থ্যসেবা: প্রবেশ করা শিল্পগুলিকে ব্যাহত করার জন্য অ্যান্ডি শুনোভারের প্লেবুক

Revolutionierung des Gesundheitswesens: Andy Schoonovers Strategie zur Umwälzung etablierter Branchen

Revolucionando la atención médica: el manual de Andy Schoonover para revolucionar industrias arraigadas

Révolutionner les soins de santé : le manuel d'Andy Schoonover pour perturber les industries bien établies

स्वास्थ्य सेवा में क्रांति: स्थापित उद्योगों में बदलाव के लिए एंडी स्कूनओवर की कार्यपुस्तिका

ヘルスケアの革命: 定着した業界を変革するためのアンディ・シューノーバーの戦略

의료 혁신: 고착화된 산업을 혁신하기 위한 Andy Schoonover의 플레이북

Revolucionando a saúde: o manual de Andy Schoonover para desestabilizar indústrias entrincheiradas

Революция в здравоохранении: книга Энди Шуновера по разрушению устоявшихся отраслей

Sağlık Hizmetinde Devrim Yaratmak: Andy Schoonover'ın Yerleşik Endüstrileri Yıkmaya Yönelik Başucu Kitabı

Cách mạng hóa hoạt động chăm sóc sức khỏe: Sách hướng dẫn cách phá vỡ các ngành công nghiệp cố thủ của Andy Schoonover

医疗保健革命：安迪·斯库诺弗颠覆根深蒂固行业的策略

ELIQ

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ELIQ

eliq.io

51-200 employees

Since 2015

COMPANY RANKING

ELIQ

EVERGREEN INDEX #4104

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