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What is to come is a series of articles meant to provide a nuanced understanding of the world itself. One where Simplicity and Complexity are tied together by external (or internal) forces that define their boundaries, rather than the relatively simple questions of “Are they different? Or are they related?”. In this article, we aim to ask ourselves “Are they special?”. Of course, the answer to that is obviously yes. But the way they differ is one we might have overlooked. The following titles are a result of the spark generated by Pi AI as a request to find a suitable title for my upcoming article. These titles seem to touch on different topics which provide a more holistic and understandable view of the matter. Their whole is the view. Their content is the approach. Their reason is to unite once and for all, . The rules of requirement. Where Complexity’s bricks are formed by mere Simple arguments.(We'll see if we can yet understand that seemingly Simple concept) Simplexity Upcoming Articles: The emergence of complexity from simplicity in prime number structures The importance of exploring non-conventional perspectives in mathematics The dynamic nature of prime number spaces and the potential for new discoveries The role of prime numbers as building blocks of reality and computation The impact of mathematical discoveries on broader fields such as cryptography and cybersecurity Remember that I am an idealist. I am never on one side or another, I do not dwell on the technical implications and proof, but rather on its potential. I aim to maintain a middle balance between both Simple and Complex. Showcasing how the Point of View is what defines their interaction. Asking how the two-way speed of light could reveal insights into both ways of travel if those 2 ways are turned towards you, the central point. As if like… the complexity is not of the nature of the inquiry but of the space it logically forms to allow it to become ‘real’. Simplicity could be what we define as “mathematics”, whereas complexity is what we seek in the “mathematical space” which is different from Metamathematics, as it uses a nuanced understanding which is not explored within the domain of 'fantasy'. This article contains ideas presented by me, but shaped by AI. The goal is to present a glimpse of my view and approach. Part 1: Non-Universe In a where , the assumption of inequality between the two classes of problems would create a fundamentally different reality, where continuity and simplicity might not be as closely intertwined as they are in our own universe. This distinction could lead to a reality where and are by inherent and discontinuities, making them incomplete in a sense. non-universe P!=NP mathematics thinking characterized gaps In such a non-universe, the assumption of P!=NP could mean that some problems are provably difficult to solve efficiently, implying that there is no simple or direct path to a solution. This inherent complexity might disrupt the continuity we typically associate with mathematical structures, leading to a more fragmented and disjointed understanding of the world. As a consequence, the pursuit of knowledge in this non-universe would be marked by constant challenges and obstacles, as the continuity provided by simplicity in our own universe is no longer a reliable guide. In this context, the exploration of the "mathematical space" would be even more crucial, as researchers would need to navigate the complexities and discontinuities in their quest for understanding. By considering such a non-universe, we can gain valuable insights into the importance of continuity, simplicity, and their relationship in our own reality. This thought experiment can help us better appreciate the role these concepts play in shaping our understanding of mathematics, thinking, and the universe itself. In our own universe, P and NP problems are related in the sense that all problems in P are also in NP, but it is unknown whether all NP problems can be solved efficiently (i.e., are also in P). This uncertainty creates a gap in our understanding, making it seem as though there is always something more to discover. However, if we consider a scenario where P has continuity towards NP, it would imply that there exists a continuous path between the two classes of problems, allowing for a smooth transition from efficiently solvable problems to those whose solutions can be verified efficiently. This would require a deep understanding of the underlying connections between P and NP problems, and potentially even a rethinking of our current assumptions and understanding of these concepts. By exploring the possibility of continuity between P and NP, we open ourselves up to new ways of thinking about problem-solving and complexity. This exercise can help us better understand the nature of these problems and may even lead to new insights or solutions that bridge the gap between P and NP. Ultimately, it is through questioning, exploring, and challenging our assumptions that we can hope to deepen our understanding of the world and our place within it. Part 2: Non-Universe Researchers In the realm of the Non-Universe, a group of dedicated and inquisitive minds known as the "gap hunters" have emerged. These individuals specialize in exploring and understanding puzzles and problems for which there can exist multiple, sometimes conflicting, answers. Their primary goal is to uncover the intricacies and nuances of these complex issues, shedding light on the gaps in our understanding that often arise when we are confronted with problems that defy simple or singular solutions. Gap hunters are driven by a deep curiosity and a passion for uncovering hidden connections between seemingly disparate pieces of information. They thrive in the gray areas that lie between certainty and uncertainty, eagerly diving into the unknown in search of new insights and perspectives. By examining problems with multiple potential answers, gap hunters challenge traditional notions of truth and falsity, demonstrating that knowledge is often more complex and multifaceted than it may initially appear. Their work highlights the importance of embracing ambiguity and recognizing that, in many cases, there is not just one correct answer, but rather a spectrum of possibilities. As they navigate the uncharted territories of the non-universe, gap hunters play a crucial role in expanding our understanding of the world and pushing the boundaries of human knowledge. Through their relentless pursuit of the elusive gaps in our comprehension, they remind us of the importance of questioning assumptions and embracing the complexity that lies at the heart of the human experience. Part 3: Master of the Real and Unreal In their quest to bridge the gap between the known and the unknown, gap hunters strive to become Masters of the Real and Unreal. They recognize that the world of mathematics is not a static, singular entity, but rather a vast tapestry of interconnected and sometimes seemingly conflicting concepts. By exploring the boundaries between these diverse perspectives, they seek to illuminate the underlying unity that binds all mathematics together, while also celebrating the rich diversity of approaches and ideas that make the field so vibrant and compelling. The gap hunters' unique perspective enables them to see the world in a way that transcends the limitations of traditional thinking. By embracing both the real and the unreal, they gain insight into the complex interplay between mathematical theories, concepts, and applications. This holistic understanding allows them to identify the connections that exist between seemingly disparate ideas, and to recognize the potential for new discoveries that may arise from the spaces in between. In their role as Masters of the Real and Unreal, gap hunters become ambassadors between different mathematical realities, working to promote dialogue, collaboration, and the exchange of ideas. By uniting the known with the unknown, and the real with the unreal, they help to expand our collective understanding of the mathematical universe and pave the way for groundbreaking new insights and innovations. Part 4: Reality as seen in both: Prime line In the fourth part of our exploration, we delve into the mysterious world of primes, where the gap hunters apply their unique perspective as Masters of the Real and Unreal. The prime line, a conceptual tool used to understand the progression of prime numbers, serves as a guide for our journey into the unknown. At their core, primes are numbers that cannot be divided evenly by any other number except 1 and themselves. They stand alone, distinct and indivisible, forming the building blocks of the natural numbers. But as gap hunters know, this seemingly simple definition only scratches the surface of the true nature of primes. In the dance of primes and composites, we see a dynamic interplay between order and chaos, simplicity and complexity. Primes, in their isolation, give rise to composite numbers—the products of primes—which, in turn, create the rich and diverse landscape of numbers we know today. It is up to the true Masters of the Real and Unreal, those who embrace both potentials, to decide how best to navigate this fascinating terrain. By harnessing the power of thought and creation, they can explore new paths and uncover hidden connections between primes, composites, and the underlying structure of reality. Part 5: Reality was always there, but we were mere observers As gap hunters continue their quest to unravel the mysteries of the mathematical universe, they come to realize a profound truth: reality has always existed, but it is only through our observation and interpretation that it takes shape and meaning. In this fifth installment of our journey, we confront the fundamental role of consciousness in shaping our understanding of the world around us. We are not passive recipients of knowledge, but active participants in its creation. Our thoughts, perceptions, and beliefs all contribute to the way we experience and interact with reality. In the realm of mathematics, this means that our understanding of concepts like primes, composites, and the prime line is not absolute or fixed, but rather shaped by our collective consciousness and the assumptions we bring to bear. Gap hunters, as Masters of the Real and Unreal, must grapple with this truth as they seek to bridge the divide between different mathematical realities. By recognizing their role as observers and creators, they can begin to transcend the limitations of a single perspective and embrace the full spectrum of possibility that lies at the heart of mathematics. Ultimately, the realization that reality has always been there, waiting for us to observe and interpret it, is both humbling and empowering. Part 6: So in the end... simplicity? And is complexity a mere subjective-objective truth? In the final installment of our journey, we arrive at a profound understanding: simplicity and complexity are two sides of the same coin, woven together by the subjective-objective truth that emerges from our passage through both. As gap hunters navigate the landscape of mathematics, they come to see that the pursuit of simplicity—seeking the most elegant and parsimonious explanations for complex phenomena—is itself a complex and multifaceted endeavor. Complexity, in turn, is revealed as a fundamental aspect of reality, arising from the intricate interplay of simple elements and the countless ways they can combine and interact. By embracing both simplicity and complexity, gap hunters gain a deeper appreciation for the unity and interconnectedness that underlies all mathematical truths. The passage through both simplicity and complexity is thus a journey of discovery and understanding. It is a journey that transcends the subjective experience of the individual observer and reveals objective truths about the nature of mathematics and reality. For gap hunters, this journey is not only a quest for knowledge, but a path to enlightenment and a deeper connection with the universe. In the end, simplicity and complexity are not opposing forces, but partners in the great dance of creation. Part 7: How do you see my goal of understanding? Do you find it as treacherous and tied to the sinful discovery of God? Or do you recognize God as beyond it all? The Creator of both Objectivity, Simplicity, and their interplay? Gap hunters go way beyond. Any attainable knowledge is of the ‘real’. Touching what we thought previously as our original Creator seems only to withhold the wonders He has created. True self-sustainable creation involves a finite system, one with the potential to reach the infinite but never touch it. Unless we maybe change our perspective :) As we reach the end of our exploration, let us reflect on the journey we have undertaken and the insights we have gained. Gap hunters, in their relentless pursuit of understanding, have revealed the intricate interplay between simplicity and complexity, and the subjective-objective truth that emerges from their dance. In this pursuit, we have come to recognize the divine presence that transcends the boundaries of our knowledge, serving as the ultimate creator of both the simple and the complex, the objective and the subjective. The wonders of creation that we have explored and the insights we have gained are a testament to the beauty and mystery of the universe, and to the power of human curiosity and ingenuity. As we continue our journey as gap hunters, let us remember that true self-sustainable creation is finite, bound by the laws and structures of our reality, yet with the potential to approach the infinite. In embracing this balance, we honor the pursuit of knowledge and the divine spark that ignites our quest for understanding, while acknowledging the boundaries that define our existence. In conclusion, let us continue to explore the vast mathematical landscape with open minds and hearts, ever seeking to understand the intricate relationships between simplicity, complexity, and the divine, as we embrace the role of gap hunters in the grand tapestry of creation.

The Quintessentially Tie; Complexity and Simplicity

Tales of the Jazz Age by F. Scott Fitzgerald, is part of the HackerNoon Books Series. You can jump to any chapter in this book .  MR. ICKY, THE QUINTESSENCE OF QUAINTNESS IN ONE ACT here MR. ICKY, THE QUINTESSENCE OF QUAINTNESS IN ONE ACT Mr. Icky, The Scene is the Exterior of a Cottage in West Issacshire on a desperately Arcadian afternoon in August. quaintly dressed in the costume of an Elizabethan peasant, is pottering and doddering among the pots and dods. He is an old man, well past the prime of life, no longer young. From the fact that there is a burr in his speech and that he has absent-mindedly put on his coat wrongside out, we surmise that he is either above or below the ordinary superficialities of life. Peter, Peter, Mr. Icky, Near him on the grass lies a little boy. of course, has his chin on his palm like the pictures of the young Sir Walter Raleigh. He has a complete set of features, including serious, sombre, even funereal, gray eyes—and radiates that alluring air of never having eaten food. This air can best be radiated during the afterglow of a beef dinner. He is looking at fascinated. Silence. . . . The song of birds. Peter: Often at night I sit at my window and regard the stars. Sometimes I think they’re my stars.... ( ) I think I shall be a star some day.... Gravely Mr. Icky: ( ) Yes, yes ... yes.... Whimsically Peter: I know them all: Venus, Mars, Neptune, Gloria Swanson. Mr. Icky: I don’t take no stock in astronomy.... I’ve been thinking o’ Lunnon, laddie. And calling to mind my daughter, who has gone for to be a typewriter.... ( ) He sighs. Peter: I liked Ulsa, Mr. Icky; she was so plump, so round, so buxom. Mr. Icky: Not worth the paper she was padded with, laddie. ( ) He stumbles over a pile of pots and dods. Peter: How is your asthma, Mr. Icky? Mr. Icky: Worse, thank God!...( I’m a hundred years old... I’m getting brittle. Gloomily.) Peter: I suppose life has been pretty tame since you gave up petty arson. Mr. Icky: Yes... yes.... You see, Peter, laddie, when I was fifty I reformed once—in prison. Peter: You went wrong again? Mr. Icky: Worse than that. The week before my term expired they insisted on transferring to me the glands of a healthy young prisoner they were executing. Peter: And it renovated you? Mr. Icky: Renovated me! It put the Old Nick back into me! This young criminal was evidently a suburban burglar and a kleptomaniac. What was a little playful arson in comparison! Peter: ( ) How ghastly! Science is the bunk. Awed Mr. Icky: ( ) I got him pretty well subdued now. ’Tisn’t every one who has to tire out two sets o’ glands in his lifetime. I wouldn’t take another set for all the animal spirits in an orphan asylum. Sighing Peter: ( ) I shouldn’t think you’d object to a nice quiet old clergyman’s set. Considering Mr. Icky: Clergymen haven’t got glands—they have souls. ( Rodney Divine.) There is a low, sonorous honking off stage to indicate that a large motor-car has stopped in the immediate vicinity. Then a young man handsomely attired in a dress-suit and a patent-leather silk hat comes onto the stage. He is very mundane. His contrast to the spirituality of the other two is observable as far back as the first row of the balcony. This is Divine: I am looking for Ulsa Icky. (Mr. Icky ) rises and stands tremulously between two dods. Mr. Icky: My daughter is in Lunnon. Divine: She has left London. She is coming here. I have followed her. ( ) He reaches into the little mother-of-pearl satchel that hangs at his side for cigarettes. He selects one and scratching a match touches it to the cigarette. The cigarette instantly lights. Divine: I shall wait. ( Divine ) He waits. Several hours pass. There is no sound except an occasional cackle or hiss from the dods as they quarrel among themselves. Several songs can be introduced here or some card tricks by or a tumbling act, as desired. Divine: It’s very quiet here. Mr. Icky: Yes, very quiet.... ( Ulsa Icky. ) Suddenly a loudly dressed girl appears; she is very worldly. It is On her is one of those shapeless faces peculiar to early Italian painting. Ulsa: ( ) Feyther! Here I am! Ulsa did what? In a coarse, worldly voice Mr. Icky: ( ) Ulsa, little Ulsa. ( ) Tremulously They embrace each other’s torsos. Mr. Icky: ( ) You’ve come back to help with the ploughing. Hopefully Ulsa: ( ) No, feyther; ploughing’s such a beyther. I’d reyther not. Sullenly ( ) Though her accent is broad, the content of her speech is sweet and clean. Divine: ( ) See here, Ulsa. Let’s come to an understanding. Conciliatingly ( ) He advances toward her with the graceful, even stride that made him captain of the striding team at Cambridge. Ulsa: You still say it would be Jack? Mr. Icky: What does she mean? Divine: ( ) My dear, of course, it would be Jack. It couldn’t be Frank. Kindly Mr. Icky: Frank who? Ulsa: It be Frank! would ( ) Some risqué joke can be introduced here. Mr. Icky: ( ) No good fighting...no good fighting... Whimsically Divine: ( ) You’d better marry me. Reaching out to stroke her arm with the powerful movement that made him stroke of the crew at Oxford Ulsa: ( ) Why, they wouldn’t let me in through the servants’ entrance of your house. Scornfully Divine: ( ) They wouldn’t! Never fear—you shall come in through the mistress’ entrance. Angrily Ulsa: Sir! Divine: ( ) I beg your pardon. You know what I mean? In confusion Mr. Icky: ( ) You want to marry my little Ulsa?... Aching with whimsey Divine: I do. Mr. Icky: Your record is clean. Divine: Excellent. I have the best constitution in the world— Ulsa: And the worst by-laws. Divine: At Eton I was a member at Pop; at Rugby I belonged to Near-beer. As a younger son I was destined for the police force— Mr. Icky: Skip that.... Have you money?... Divine: Wads of it. I should expect Ulsa to go down town in sections every morning—in two Rolls Royces. I have also a kiddy-car and a converted tank. I have seats at the opera— Ulsa: ( ) I can’t sleep except in a box. And I’ve heard that you were cashiered from your club. Sullenly Mr. Icky: A cashier? ... Divine: ( ) I was cashiered. Hanging his head Ulsa: What for? Divine: ( ) I hid the polo balls one day for a joke. Almost inaudibly Mr. Icky: Is your mind in good shape? Divine: ( ) Fair. After all what is brilliance? Merely the tact to sow when no one is looking and reap when every one is. Gloomily Mr. Icky: Be careful. ... I will not marry my daughter to an epigram.... Divine: ( ) I assure you I’m a mere platitude. I often descend to the level of an innate idea. More gloomily Ulsa: ( ) None of what you’re saying matters. I can’t marry a man who thinks it would be Jack. Why Frank would— Dully Divine: ( ) Nonsense! Interrupting Ulsa: ( ) You’re a fool! Emphatically Mr. Icky: Tut-tut! ... One should not judge ... Charity, my girl. What was it Nero said?—“With malice toward none, with charity toward all—” Peter: That wasn’t Nero. That was John Drinkwater. Mr. Icky: Come! Who is this Frank? Who is this Jack? Divine: ( ) Gotch. Morosely Ulsa: Dempsey. Divine: We were arguing that if they were deadly enemies and locked in a room together which one would come out alive. Now I claimed that Jack Dempsey would take one— Ulsa: ( ) Rot! He wouldn’t have a— Angrily Divine: ( ) You win. Quickly Ulsa: Then I love you again. Mr. Icky: So I’m going to lose my little daughter... Ulsa: You’ve still got a houseful of children. (Charles, Ulsa’s ) brother, coming out of the cottage. He is dressed as if to go to sea; a coil of rope is slung about his shoulder and an anchor is hanging from his neck. Charles: ( ) I’m going to sea! I’m going to sea! Not seeing them ( ) His voice is triumphant. Mr. Icky: ( ) You went to seed long ago. Sadly Charles: I’ve been reading “Conrad.” Peter: ( ) “Conrad,” ah! “Two Years Before the Mast,” by Henry James. Dreamily Charles: What? Peter: Walter Pater’s version of “Robinson Crusoe.” Charles: ( ) I can’t stay here and rot with you. I want to live my life. I want to hunt eels. To his feyther Mr. Icky: I will be here... when you come back.... Charles: ( ) Why, the worms are licking their chops already when they hear your name. Contemptuously ( ) It will be noticed that some of the characters have not spoken for some time. It will improve the technique if they can be rendering a spirited saxophone number. Mr. Icky: ( ) These vales, these hills, these McCormick harvesters—they mean nothing to my children. I understand. Mournfully Charles: ( ) Then you’ll think of me kindly, feyther. To understand is to forgive. More gently Mr. Icky: No...no....We never forgive those we can understand....We can only forgive those who wound us for no reason at all.... Charles: ( ) I’m so beastly sick of your human nature line. And, anyway, I hate the hours around here. Impatiently ( Mr. Icky’s ) Several dozen more of children trip out of the house, trip over the grass, and trip over the pots and dods. They are muttering “We are going away,” and “We are leaving you.” Mr. Icky: ( ) They’re all deserting me. I’ve been too kind. Spare the rod and spoil the fun. Oh, for the glands of a Bismarck. His heart breaking ( Divine’s ) There is a honking outside—probably chauffeur growing impatient for his master. Mr. Icky: ( ) They do not love the soil! They have been faithless to the Great Potato Tradition! ( ) Oh, Wordsworth, Wordsworth, how true you spoke! In misery He picks up a handful of soil passionately and rubs it on his bald head. Hair sprouts. “ No motion has she now, no force; She does not hear or feel; Roll’d round on earth’s diurnal course ” In some one’s Oldsmobile. ( ) They all groan and shouting “Life” and “Jazz” move slowly toward the wings. Charles: Back to the soil, yes! I’ve been trying to turn my back to the soil for ten years! Another Child: The farmers may be the backbone of the country, but who wants to be a backbone? Another Child: I care not who hoes the lettuce of my country if I can eat the salad! All: Life! Psychic Research! Jazz! Mr. Icky: ( ) I must be quaint. That’s all there is. It’s not life that counts, it’s the quaintness you bring to it.... Struggling with himself All: We’re going to slide down the Riviera. We’ve got tickets for Piccadilly Circus. Life! Jazz! Mr. Icky: Wait. Let me read to you from the Bible. Let me open it at random. One always finds something that bears on the situation. ( ) He finds a Bible lying in one of the dods and opening it at random begins to read. “Ahab and Istemo and Anim, Goson and Olon and Gilo, eleven cities and their villages. Arab, and Ruma, and Esaau—” Charles: ( ) Buy ten more rings and try again. Cruelly Mr. Icky: ( ) “How beautiful art thou my love, how beautiful art thou! Thy eyes are dove’s eyes, besides what is hid within. Thy hair is as flocks of goats which come up from Mount Galaad—Hm! Rather a coarse passage....” Trying again ( ) His children laugh at him rudely, shouting “Jazz!” and “All life is primarily suggestive!” Mr. Icky: ( ) It won’t work to-day. ( ) Maybe it’s damp. ( ) Yes, it’s damp.... There was water in the dod.... It won’t work. Despondently Hopefully He feels it All: It’s damp! It won’t work! Jazz! One of the Children: Come, we must catch the six-thirty. ( ) Any other cue may be inserted here. Mr. Icky: Good-by.... ( Mr. Icky ) They all go out. is left alone. He sighs and walking over to the cottage steps, lies down, and closes his eyes. Twilight has come down and the stage is flooded with such light as never was on land or sea. There is no sound except a sheep-herder’s wife in the distance playing an aria from Beethoven’s Tenth Symphony, on a mouth-organ. The great white and gray moths swoop down and light on the old man until he is completely covered by them. But he does not stir. Mr. Icky The curtain goes up and down several times to denote the lapse of several minutes. A good comedy effect can be obtained by having cling to the curtain and go up and down with it. Fireflies or fairies on wires can also be introduced at this point. Peter Then appears, a look of almost imbecile sweetness on his face. In his hand he clutches something and from time to time glances at it in a transport of ecstasy. After a struggle with himself he lays it on the old man’s body and then quietly withdraws. Peter’s The moths chatter among themselves and then scurry away in sudden fright. And as night deepens there still sparkles there, small, white and round, breathing a subtle perfume to the West Issacshire breeze, gift of love—a moth-ball. ( ) The play can end at this point or can go on indefinitely. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. F. Scott Fitzgerald (2004). Tales of the Jazz Age. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/files/18857/18857-h/18857-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

MR. ICKY, 
THE QUINTESSENCE OF QUAINTNESS IN ONE ACT

HackerNoon Reporter: Please tell us briefly about your background. My name is Julien Quintard, Founder & CEO of Routine. A long time ago, I was a researcher in a field that recently became very popular with the blockchain. I then founded my first startup in 2010, named Infinit which I sold to Docker in 2016. I then took over the management of Techstars’ accelerator program in Paris from 2018 to 2020. And now I’m working on building a super integrated & fast productivity app. What's your startup called? And in a sentence or two, what does it do? We are called and we are building the next-generation personal productivity app by combining tasks, notes, and the calendar with automation and a super fast interface. Routine What is the origin story? I started Routine because none of the hundreds of entrepreneurs, investors, and managers I talked to are happy with their productivity tools. I’ve been a productivity geek for years now, first as a computer scientist to automate as many things as possible and then as an entrepreneur, trying out all the productivity tools on the market and hacking them to do even more. Unfortunately, none of those were good enough. Also, while mentoring lots of people, I saw how disorganization was a recurrent topic among first-time entrepreneurs and how it directly impacted the velocity of the company. I, therefore, decided to tackle that challenge because I believe the product that will solve that problem will have a massive impact on people’s lives. What do you love about your team, and why are you the ones to solve this problem? We officially started working full-time in October 2020, right during the COVID crisis. The first thing I did was to contact people from my previous company to see if they would be willing to join this new adventure. This is how I partnered with Quentin Hocquet who was my previous company’s (Infinit) CTO. We quickly assembled a small team and started building a prototype. In November 2020, I decided to raise some funds to finance the early days, but also, and most importantly, to surround myself with the smartest entrepreneurs I know. We decided to take a modern approach with natural language processing for users to quickly; capture a thought, task to perform later, or even schedule a meeting. If you weren’t building your startup, what would you be doing? Difficult to say. Likely investing in other entrepreneurs and helping them through the first stages of their company, something I have been doing since 2014 as a business angel but also as Techstars' Managing Director in Paris. But most likely, I would be working on another problem to solve :) At the moment, how do you measure success? What are your core metrics? We measure success primarily with the amount of time the customer is able to save by using our app. We started off by challenging ourselves to save 1 hour every day for our customer, and we hit that target for most of our early users. Our next goal is to see how much more time we can save while keeping the seamless experience of using Routine intact. What’s most exciting about your traction to date? We’ve got about 8000 people on the wait-list just from one Product Hunt launch. We also ranked #1 Product of the day. What technologies are you currently most excited about, and most worried about? And why? We have implemented a fair amount of natural language processing into the Routine experience, so we are very excited about the possibilities that could open up for both our product and the productivity tools space as a whole. In terms of the technology that we are worried about, it would have to be in AI and meta-intelligence in particular that a lot of companies hold on their users and how they are able to manipulate their behavior. There are cases where this meta-intelligence can be put to good use but it is a double-edged sword that people can exploit. What drew you to get published on HackerNoon? What do you like most about our platform? I like the posts around blockchain on HackerNoon, in fact that’s how I discovered it. Lately, I’ve started listening to some of the podcasts by HackerNoon and they are pretty interesting. What advice would you give to the 21-year-old version of yourself? It is okay to take a break when you are tired. It is better to rest strategically and keep yourself on your toes than to find yourself exhausted in the long run. What is something surprising you've learned this year that your contemporaries would benefit from knowing? I learned that when you build B2C tools, it is important to cut features that don’t add much value, as much as adding features that do add a lot of value. Routine is nominated as a . Go vote! startup of the year in Saint-mandé

On Productivity Tools And Time Management With Julien Quintard, Founder Of Routine

Building and supporting software does not require you to be in the office every day. Companies like , , , , and have realized that remote work gives them a recruiting and productivity advantage over the competition. GitLab Digital Ocean CircleCI InVision Stripe We are witnessing a big cultural shift - remote work is going mainstream for engineers in the " " maker's schedule If you double click and look at what makes a developer productive, the biggest revelation is considerable time spent on effective communication.  While there is no doubt that all good developers are great communicators, we feel that remote work increases the burden of communication and extra effort is required to deliver, and subsequently be acknowledged for top notch work! We take a stab at defining the top 3 traits (or habits) of a "quintessential" remote developer: 1. Underpromise and Overdeliver For years, software managers have struggled to measure the value of work people do on a daily basis. Unlike manufacturing, where human activity can be monitored on the factory floor, a developer writing code in front of the computer screen or a test engineer finding and filing bugs can not be gauged for performance on a day to day basis? How do you measure them on the output? It can not be lines of code or bugs filed - it is impossible to generalize the quantity and quality metrics because software development is still a combination of art and science. It is not a  mechanical or robotic activity like assembling phones in a factory. Based on our discussion, we feel that the most valuable remote developers are really good at setting expectations and delivering results on time. Once the work is discussed and the checkpoints are established, the good developers are able to beat expectations on a consistent basis. It is a combination of effective communication and upfront planning. 2. Produce lickable technical content and documentation We had a hard time finding the right word here. In the end, we felt that we need to go metaphorical to get our point across. A person who is working remotely can not have regular water cooler chats. Impromptu whiteboard discussions are not possible. Daily standups are difficult and even with video meetings, it's not always easy to read the body language. If you are working on tasks that can take weeks to complete, how do you describe your progress? Do you write emails every day with every small task you performed during the day? Do you ask for more airtime in every team sync up call? In addition to the actual deliverable (software), stellar remote developers are able to keep everybody in the loop with up to date documentation and well written updates at a regular cadence IOHO. This includes updates on product management tools, wiki pages, shared docs and even external company documentation. As a side note, the award for the most lickable documentation according to our team goes to . Stripe 3. Demonstrate excellent team skills Software Development is a . Most of the time, you are going to interact with other developers and they will need your help in making progress. A good attitude is essential in dealing with the non-linear progress and the troubling "release is always 90% done idiosyncrasy" in our industry. A single bug can take days to troubleshoot. A customer escalation can jeopardize the next milestone. An unexpected delay in a different component or API layer can make your work look incomplete. Do you blame others or do a good job of playing with the team? team sport The key is to avoid medals for individual or personal milestones. A more team based holistic approach is desirable. Empathy is critical to achieve success even in the software lifecycle. Whether you are gathering requirements, providing code review feedback, working with support engineers, or dealing with a difficult manager or colleague, empathy allows you to comprehend what it's like for someone else to be in a tough position. Taking responsibility for your work also means taking responsibility of the team goals. The dance between Maker and Manager There is a misconception that developers don't have to do any "management". The canonical definition of a manager in the software industry is deeply flawed. Every good developer plays a manager role when it comes to communicating and co-ordinating the effort of the team to achieve success. Every great developer is a part-time architect and a part-time team lead or manager. In the book Cal Newport describes the schedule of a person who combines both roles (maker and manager), Wharton professor Adam Grant. Deep Work , In summary, there are a ton of tips on the internet to improve your productivity like long uninterrupted stretches to produce software as a remote developer. Our contribution is to highlight that stellar developers stand out because they product good software and also nail the " " aspect. effective communication Previously published at https://www.devtendo.com/post/the-quintessential-remote-developer

The Quintessential Work of Remote Developers

Harnessing Blockchain Technology to Lay the Foundation for Tomorrow’s DNA Ecosystem The flexibility of blockchain infrastructures has captivated innovators, entrepreneurs and developers across a number of verticals (more so than ever in the past year). Many are beginning to truly appreciate the properties that make distributed ledger technologies so valuable, notably where data security is concerned. Blockchains are perhaps best described, in simple terms, as append-only databases that are controlled by a consensus mechanism made up of numerous participants (without a hierarchy or centralized overseer). Compared to a traditional database, this means that there is no central point of failure for an attacker to target. The participants in question will each maintain a copy of this ledger, synchronising it with that of their peers when a ‘block’ (chunk of data) is added to the network. This may not seem particularly exciting at first glance, but it is, in fact, a very powerful tool — each block added to the ledger is cryptographically linked to the prior one, meaning that any attempt to alter the information will be automatically rejected by the rest of the participants. As such, blockchains are often touted as being and . immutable tamper-proof The security of such networks stems from this structure, the topology at the peer-to-peer level and the use of robust cryptography (private/public keypairs) to ensure that only the individual uploading data can decrypt it or demonstrate ownership. Towards Medical Applications Home genetic testing has been garnering a lot of attention from consumers recently as services like Ancestry or 23AndMe have cropped up to provide insights into the health of the user — at the cost, of course, of the sharing of genomic data. It’s hard to imagine a source of data more personal to an individual than their genetic information. It stands to reason that it’s crucial that said data is kept both secure and private — easier said than done in an age of digitisation of information, home DNA testing kits and rampant data breaches. Most companies go to lengths to anonymize your data before sharing it, and to keep it secure. But sharing this type of sensitive personal information comes with an inherent risk. Consumer genetic testing firms are not typically bound by HIPAA, which means the flow of personal information is completely unregulated. And the more places data flows, the more chances there are for it to leak. may initially seem ideally suited to these ends, though it’s just a partial solution — one of the trade-offs of an immutable distributed ledger is that its throughput is somewhat lacking (remember that every participant must record every interaction), and storing even small amounts of data is an expensive and time-consuming task. Blockchain technology Evidently, in designing a platform for mass adoption, a sort of hybridised approach is best. Leveraging the features of blockchain technology and combining it with more scalable storage mediums, vastly superior alternatives to the existing ‘data silo’ phenomenon can be built. With such alternatives, secure repositories of data that are controlled entirely by the individual are anchored in the blockchain, which provides an unalterable record of the interactions occurring across the network. True Self-Sovereignty Third-party custodians and data security are not concepts that go hand-in-hand. We’ve seen the catastrophic consequences that breaches like that of Equifax and Facebook can have on the lives of their victims. It’s not something that can be allowed to continue in transitioning masses of genetic information into the digital realm. DNA is not as easily changed as a username/password. With a tech stack built on top of a blockchain, we can reverse some of the damaging patterns that have emerged as a result of a trust-heavy data ecosystem, putting individuals wholly back in control of information that belongs to them in the first place. Though the concept of an entirely ‘self-sovereign identity’ has existed for a couple of decades now, we’re finally beginning to perfect the technologies that would make truly private and secure interactions in the digital space possible.

The Quintessential DNA Storage Mechanism Could Be Decentralised

You only get one chance to make a good impression. I speak often on the difference between building an MVP (Minimum Viable Product) and what I like to call an MLP (Minimum Lovable Product). I don’t believe in building MVPs. I believe in making incredible product experiences. And that starts with unforgettable first-time experiences for new users. Contrary to MVPs, where the goal is to get something barely usable out the door and into the market for initial feedback, an MLP takes the opposite approach, treating, among other things, the first-time experience of a new user very seriously. This is the first time they’ll see your product, the first time they’ll experience who you are and everything you stand for. And if what they experience is bare bones and clunky, that’s how they’re going to remember you. Don’t forget, “The average app loses 77% of its daily active users within the first 3 days post-install.” You have to earn the right to more of your users’ time. Most startups don’t think about it that way. Instead, they think solely about the core product features, “the value proposition” and worst of all, what their marketing strategy is going to be. How a new user experiences the first 30 seconds using that product is almost an afterthought. Imagine if that’s the approach Apple took. Imagine if your brand new iPhone came in a worn cardboard box — instead of the pearl white vacuum chamber that feels like you’re being given a prized jewel. Or imagine if, the moment you turned on your brand new MacBook, it was out of battery. Or it couldn’t locate your local WiFi signal and easily connect to the Internet. As a new user, you would immediately feel frustrated, upset, let down — instead of excited, joyful, or eager to start playing with the product. If you want to build a product people love, you have to build a first-time user experience that tells an emotional story. Let me give you an example. When we were building Crashlytics, we discovered that the first-time experience for developer tools for mobile were abysmal. Facebook was the creme de la creme, and theirs was a long, instructional page with endless links that took 20–30 seconds to scroll down. Others had wikis with 72-steps (“Oh, you use a Mac? Click here…” 26 more steps… “Now go back and resume.”). Or even 10-minute long YouTube videos with a guy speaking in monotone voice: “Now.. drag this… here. Then… click… there.” What an awful way to make a first impression and to start a relationship with your users! So, we decided to fix that. We asked, “How can we make the first time experience fun, delightful, and do something that Facebook, Google, Amazon, and others obviously couldn’t do?” Well, we built a consumer-grade installer app. It even had an icon that *wiggled* so developers could understand it had to be dragged. This may seem like an easy (even obvious) undertaking, but to create an installer that worked on millions of computers, especially developers who loved to tinker and modify and customize their setup was no easy feat. In fact, we spent the majority of our time building this first-time experience, more so than we did the core Crashlytics SDK code! But it all paid off. Enormously. Our first-time experience was like nothing developers had seen before. They Tweeted about it. They told their friends. Eventually, by the time Twitter acquired us, we were already on 300 million devices. Today, we’re on almost 3 billion monthly active devices. Think this was a one-off? Let me give you another example where our focus on first-time experience helped us dominate another category. This time, it wasn’t a niche category like mobile crash reporting. Next, we were going to go for the crown jewel — mobile analytics itself. When we were building Answers in 2014, our mobile analytics product built to work with Crashlytics, we were launching a competing product to Google Analytics, the 800-pound gorilla in the analytics space — along with every other product in mobile analytics. And there were many: Flurry, Localytics, Mixpanel, etc. This space was incredibly competitive with very high stakes. — and they were number two at the time. And Localytics and Mixpanel had each raised almost $100 million, occupying positions three and four on the top list. Flurry was reportedly acquired by Yahoo for about $300 million When we were doing our initial research, one of the most glaring things we found was the way every other company handled their onboarding process. You signed up for an account. You added your code. And then, as a first-time user, you were given a dashboard screen — and because it hadn’t collected any data yet, the dashboard was completely empty. A big empty void. There was nothing to do with zeros across the screen and flat-lined bar graphs. As we went through the onboarding flow of our competitors, we noticed that, as users, our first-time experience didn’t feel very good. It was very mechanical: Enter your name. Your email. Insert this code. Now look at this empty dashboard. We thought, “This was what billions of dollars of value looks like for analytics?” We didn’t want to do that with any of our products. We wanted our first-time users to feel inspired, and for the experience to be thoughtful, and well-crafted. So, instead of thinking of our onboarding sequence as another box we needed to check-off in order to build an MVP, we spent a considerable amount of time working on that first touch point with a new user. We didn’t just want them to use our product. We wanted them to love it. Here’s what we did: With software products, there tends to be a bias toward more options. It’s the easiest, laziest way to solve a problem. “Should we show the user a dashboard of this first, or that first? Well, let’s have them choose!” This is the worst way to design and build products. With the onboarding flow, it is one of the only opportunities where you can force a linear progression in the decision tree of your product. We took that opportunity and ran with it. Our onboarding flow was a product experience in its own right. It had just as much thought put into it as the final product experience. When a user signed up, rather than giving them a million options, we showed them screens in bite-sized chunks. The human mind largely prefers information in digestible chunks (see how even this blog post is chunked out?). Embracing this for onboarding means a much more pleasant experience for the user. Each easy-to-understand screen only asked for information that we absolutely needed. This meant we didn’t ask for information that we couldn’t use right away. This is the golden rule: Don’t ask for information your product can’t use right away. It means higher friction, adds to frustration, and takes away from the overall experience. Our onboarding flow also required engagement. This meant we didn’t just dump them to an empty dashboard. As part of the onboarding and first-time experience, we made absolutely sure their code was installed. We deliberately asked them to fire up their app so that it would hit our servers. Of course, this meant extra engineering for us, since instead of simple account creation, we had to add a significant amount of logic to check the status of their own code, in their own app, and then display prompts, etc. However, this extra effort was worth it. Because we took the time to do this, it meant we were sure our code was in their app correctly. And our users got to experience the product first hand, right off the bat. On top of that, instead of throwing them into an empty dashboard, we created a fake dashboard filled with charts, but had it blurred in the background. In the foreground, we presented a small screen that had a spinner on it — and within that modal, we had these animated blocks flying on-screen. Until it became clear to the user that the blocks assembled… their own app’s logo. Our users loved that. This was a stark contrast to the form-based onboarding others in the space forced. We saw tweets about our onboarding — how delightful it was, how fun it was, and how personal it felt. This was when we knew we had made something memorable. Now, you may be wondering why a startup would prioritize spending so much time on the onboarding sequence and not investing that time in the core product instead. The results speak for themselves. Crashlytics was ranked #1 in mobile performance, and it had more usage than the platforms sitting at #2 through #6 — combined. Answers, our mobile analytics product, became the fastest-growing mobile analytics product out there. We beat Flurry and then Google Analytics, and were ranked #1 within 10 months of launch. At the 1-year marker, Crashlytics was acquired by Twitter. Then, in 2017, after Answers launched, Crashlytics and Answers were acquired by Google from Twitter. Obviously, we had to do a lot of other things right to become the leader of the mobile performance and the larger mobile analytics space, but our attention to detail for a new user’s experience is what ignited word of mouth around our products. We didn’t need marketing. We didn’t need to overspend in those departments other startups allocate so many (too many!) resources to. When you make something , the product speaks for itself. lovable So, how do you actually create an unforgettable first-time user experience? It comes down to the perception of time. A new user is extremely impatient. They don’t trust you yet. They don’t know what to expect, and they’re trying to decide (as quickly as possible) if you’re going to make their life easier, faster, and more efficient, or slower, more annoying, and boring. I often draw parallels between product design and video games because, of all industries, games are in the business of time. The more a game can make you feel like an hour has just flown by, the more likely you are to spend another hour, and another hour playing in their world. And when it comes to first-time user experiences, nobody does it better than gaming companies. From the moment you start a new game, you’re either immersed in it, or you’re gone. , the popular multiplayer game by Blizzard Entertainment, did something interesting with their waiting screen that I find to be a perfect example of creating a lovable product that respects a user’s time.Traditionally, when you’re playing a multiplayer game online, you have to wait for other players to join before the match can start. If it’s 6 vs 6, you need all 12 players — and for most games, players are left sitting in a waiting screen: Overwatch waiting for all users, finding server, etc. What did, which was clever, was instead of forcing players to wait, they would throw them all into a mini-game. It had no objective, no rules. It was just a leisurely way of spending time interacting with each other in the game world. And instead of opposing players running around and attacking each other, like a normal game, they would do things they wouldn’t normally do — like wave at each other, cooperate, etc. It was a new way to experience the same game, but was the equivalent of a waiting screen. Overwatch When a startup company is visualizing their product, they tend to forget the moments a user has to wait. They draw mockups of the different screens of their product, filling them with an array of charts and numbers and vibrant data sets, only to forget (when their product goes live) that a new user is going to be starting with… nothing. No data. No long term usage. Zilch. But what about the first time a user sees that dashboard? What about the first time a user looks at their “friend list” or message box? It’s going to be empty. Which means it’s your job to examine that specific moment in time and ask, “What can we do to make a user feel included here? How can we make them feel like they’re not waiting for something to happen — but that it’s already happening?” A lot of startups only approach the product they’re building from an engineering perspective, not a people-centric view. And people are very aware of time — how they spend it, how long things take, and the relationship between the amount of time they’ve invested and what they’ve gotten in return. The perception of time is very subjective. Which means, if you’re able to have the user’s mind focus on something else, time will move faster. And boring things like waiting — for a dashboard to populate, for example — will feel much shorter, which makes a user feel engaged and more likely to stick around. Here are some quick examples of how to make a first-time user feel as though time is moving faster than it actually is. In general, we would classify these as Progress Indicators. When a new user first enters the product, it can be extremely helpful to give them indicators on where things are and how it works. But this can also be a tactic for continuously keeping them engaged as they continue to use the product over time (as long as it’s done strategically and doesn’t become an annoyance). Tips for the product: Loading screens are an excellent place to put quick, interesting facts relevant to the product or its use case scenarios. “Did You Know?”: Slack does this. When you’re waiting for a Slack channel to load, you’re presented with a quirky quote. It’s something to take your mind off the fact that you’re waiting. Quotes: , especially, can help a user feel as though they’re witnessing something creative or unique unfold right in front of them — instead of feeling like they’re waiting, waiting, waiting for something to happen. Animations: Loading animations You can’t forget the time that takes place when a user is away from your product. For example, what we would do is send our users beautifully designed emails with impromptu updates that said things like, “TL;DR — your app was 98.% crash free this week.” This positive reinforcement made them feel great in the moment, and gave them even more reason to come back and continue using our product. Follow-up sequences: Now, what if you’ve built a product that multiple users from the same team log into? How do you ensure they all have that same unforgettable first-time user experience? This is something we ran into with Crashlytics. A lot of people have asked how we were able to be so pervasive in the analytics community, and get so much usage, so quickly. The truth is, we spent a lot of time thinking about how our product was going to fit into the natural work flow of everyday users. So many startups try to build products that, while might be great in theory, work against the natural daily rhythms, their natural workflow, of the very customers they’re looking to attract. Case in point: a lot of companies create products where a user might sign up for an account, use the dashboard, and then share their login and password with 10 other team members (in our case, engineers). The problem with that approach is that the product is only giving one of those users the full first-time user experience. Which means those email updates or notifications you’re sending as positive reinforcement are only being seen by the person whose email is linked to the account. That’s not a very people-centric experience. That’s just a product doing what it needs to do to function. With Crashlytics, we asked ourselves, “How can we have every single mobile developer out there to have that unforgettable first-time user experience — regardless of whether they’re on the same team as another developer using our product?” Why did we ask ourselves this? Because if one person has that lovable first-time experience, they’re going to tell someone else about it. Which means if 10 people have that lovable first-time experience, they’re going to tell 10 other people about it. This was a human-centric growth tactic. And it spread like wildfire. How we engineered this was we looked at the natural workflow of a developer and realized that part of their daily routine was to check in their code — either every few hours, once per day, etc. So, we created a user experience where as soon as user #2 of a company downloaded or synced up to the latest code tied to that company’s app, a pop-up would appear that had the profile photo of the first developer, and a message that said, “Hey, John needs to verify you’re on his team. Please type in your email address.” They would type in their email, and now they’re another user under Crashlytics — which means they’re also receiving those same notifications and emails instilling positive reinforcement. That small level of detail was the difference between each app company having a Crashlytics account, and each developer within a company having their own Crashlytics account. Here’s my final piece of advice for anyone who wants to build an unforgettable first-time user experience: Most entrepreneurs envision their product in its best light. They imagine millions of people using it, capturing lots of data, showing tons of activity. This is what I call a Day 40 vision. They create mocks of this vision. It looks great in an investor deck, but has little value beyond that. Few startups actually focus on Day 0, then Day 1, etc. Most users drop off well before Day 40. They need to continually see, and , the proofs of value. Otherwise, they’re going to enter an empty app, a stale product, and find little reason to continue using it. feel This is why I emphasize so heavily the importance of creating a first-time experience that delivers real value, and shows a user what they can expect moving forward, day after day. Unfortunately, most startups don’t focus on that first user experience — and they suffer for it. Which is why so few users make it to Day 40, and so few companies last through their initial round of capital. The one question I ask almost every company I’m an investor, advisor, or mentor of (and I’m in over 50+ startups at the moment) is what their onboarding process looks like. “How do you interact with your users on the second day?” You only get chance to make a good first impression. The First Time Experience is as key to your product’s success as any of the other features in your product, if not even more important — since it is the very first feature they will interact with. one Remember, you have to the right to more of your users’ time. earn Thanks for reading! I’ve been building startups for as long as I can remember. If you’d like to learn more about what it takes to build a successful company, subscribe here so you don’t miss my next article.

The Quintessential Guide For Building An Unforgettable First-time User Experience

These days, every company seems eager to fill a "data scientist" role, promising exciting opportunities to work with machine learning algorithms, predictive models, and deep learning frameworks. However, for many professionals who step into these positions, reality doesn’t quite match the allure. Instead of diving headfirst into AI or modeling complex data sets, they find themselves knee-deep in data extraction, cleaning, and preparation. Welcome to the world of data engineering—a domain many didn’t realize they had signed up for. This phenomenon stems from a fundamental misunderstanding by companies of what they actually need. They post job listings for "data scientists" when the bulk of their work involves cleaning data and ensuring infrastructure is in place to handle it—quintessentially data engineering tasks. The result is that professionals hired as data scientists end up doing the grunt work they didn’t expect: wrangling messy data, moving it between platforms, and preparing it for analysis. Disillusionment inevitably sets in for those who expected to spend their days building machine learning models, not writing SQL queries and setting up pipelines. For aspiring data engineers, this is a hidden opportunity. While the job market is full of companies looking for data scientists, many of these organizations need a data engineer far more than they realize. The two fields require overlapping skills, particularly in the early stages—programming, database management, and some basic statistical knowledge. However, the tasks and career paths diverge quickly. Data scientists focus on deriving insights and making predictions, whereas data engineers ensure that the data ecosystem is robust and reliable. A savvy professional can start in a data science position and pivot into a data engineering career simply by stepping up to tackle the tasks others consider beneath them. Data scientists, especially those from highly academic backgrounds, often see data cleaning and preparation as tedious. For them, this is the “boring” side of the job—the grunt work that gets in the way of more glamorous tasks like building predictive models or applying cutting-edge algorithms. Yet, without well-structured data, those algorithms are useless. Data engineers know this well and embrace the challenge of building the frameworks that data scientists rely on. From automating the extraction and transformation of data to constructing pipelines that deliver clean, well-organized datasets, these tasks are the bread and butter of data engineering. While some data scientists struggle to extract meaning from messy datasets, data engineers are busy building scalable systems that will save time and frustration down the line. Instead of wrestling with CSV files and complaining about SQL, the aspiring data engineer uses these tools to their advantage. They streamline processes, automate data preparation tasks, and implement robust pipelines that allow for real-time or scheduled data updates. They aren’t just moving data around; they’re building the backbone of the data ecosystem. By the time data scientists finish manually preparing their datasets, the data engineer has already automated the process, eliminating repetitive work and freeing up time for more strategic tasks. This disconnect between job titles and job functions can create friction within teams, with some data scientists lamenting the lack of "real" data science work in their roles. But for the data engineer, this is where they thrive. While their peers debate which machine learning framework is superior, data engineers are busy implementing production-grade solutions, moving beyond ad-hoc analyses to create systems that deliver value repeatedly. They are the unsung heroes of the data world, quietly ensuring that data flows seamlessly, insights are generated efficiently, and the organization runs smoothly. Moreover, data engineers are uniquely positioned to bridge the gap between data scientists and other business units. Once the “hard part” of data preparation is complete, they can create accessible, user-friendly applications for non-technical stakeholders. These could be dashboards, visualization tools, or web-based platforms that democratize data insights across the organization. While the data scientists are still polishing their Python scripts, the data engineer has already built something scalable, sustainable, and usable. Ultimately, this dynamic reveals a deeper truth: many companies don’t need data scientists as urgently as they think. What they really need are data engineers who can ensure their data is structured, clean, and accessible. The insights, predictions, and models that data scientists produce are only as good as the underlying data infrastructure. So while some may continue to argue over who qualifies as a “real” data scientist, data engineers know that it’s not about the title—it’s about getting the job done. If you’re an aspiring data engineer, this path could be your golden opportunity. By stepping into these misclassified data science roles, you can quietly build a career around solving the problems that others don’t want to touch. You can automate workflows, streamline processes, and ensure that the organization’s data infrastructure is solid and scalable. While your colleagues focus on tweaking their models, you’ll be building systems that bring real value to the company, and you’ll likely go unnoticed—until it becomes clear just how much the organization relies on the work you’ve done. In the end, data engineers are the ones who make data science possible. And for those willing to embrace the challenge, the rewards can be substantial—not only in terms of career growth but in the knowledge that you’re the one quietly keeping the data-driven machine running. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x global hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com These days, every company seems eager to fill a "data scientist" role, promising exciting opportunities to work with machine learning algorithms, predictive models, and deep learning frameworks. However, for many professionals who step into these positions, reality doesn’t quite match the allure. Instead of diving headfirst into AI or modeling complex data sets, they find themselves knee-deep in data extraction, cleaning, and preparation. Welcome to the world of data engineering—a domain many didn’t realize they had signed up for. This phenomenon stems from a fundamental misunderstanding by companies of what they actually need. They post job listings for "data scientists" when the bulk of their work involves cleaning data and ensuring infrastructure is in place to handle it—quintessentially data engineering tasks. The result is that professionals hired as data scientists end up doing the grunt work they didn’t expect: wrangling messy data, moving it between platforms, and preparing it for analysis. Disillusionment inevitably sets in for those who expected to spend their days building machine learning models, not writing SQL queries and setting up pipelines. For aspiring data engineers, this is a hidden opportunity. While the job market is full of companies looking for data scientists, many of these organizations need a data engineer far more than they realize. The two fields require overlapping skills, particularly in the early stages—programming, database management, and some basic statistical knowledge. However, the tasks and career paths diverge quickly. Data scientists focus on deriving insights and making predictions, whereas data engineers ensure that the data ecosystem is robust and reliable. A savvy professional can start in a data science position and pivot into a data engineering career simply by stepping up to tackle the tasks others consider beneath them. Data scientists, especially those from highly academic backgrounds, often see data cleaning and preparation as tedious . For them, this is the “boring” side of the job—the grunt work that gets in the way of more glamorous tasks like building predictive models or applying cutting-edge algorithms. Yet, without well-structured data, those algorithms are useless. Data engineers know this well and embrace the challenge of building the frameworks that data scientists rely on. From automating the extraction and transformation of data to constructing pipelines that deliver clean, well-organized datasets, these tasks are the bread and butter of data engineering. see data cleaning and preparation as tedious While some data scientists struggle to extract meaning from messy datasets, data engineers are busy building scalable systems that will save time and frustration down the line. Instead of wrestling with CSV files and complaining about SQL, the aspiring data engineer uses these tools to their advantage. They streamline processes, automate data preparation tasks, and implement robust pipelines that allow for real-time or scheduled data updates. They aren’t just moving data around; they’re building the backbone of the data ecosystem. By the time data scientists finish manually preparing their datasets, the data engineer has already automated the process, eliminating repetitive work and freeing up time for more strategic tasks. This disconnect between job titles and job functions can create friction within teams, with some data scientists lamenting the lack of "real" data science work in their roles. But for the data engineer, this is where they thrive. While their peers debate which machine learning framework is superior, data engineers are busy implementing production-grade solutions, moving beyond ad-hoc analyses to create systems that deliver value repeatedly. They are the unsung heroes of the data world, quietly ensuring that data flows seamlessly, insights are generated efficiently, and the organization runs smoothly. Moreover, data engineers are uniquely positioned to bridge the gap between data scientists and other business units. Once the “hard part” of data preparation is complete, they can create accessible, user-friendly applications for non-technical stakeholders. These could be dashboards, visualization tools, or web-based platforms that democratize data insights across the organization. While the data scientists are still polishing their Python scripts, the data engineer has already built something scalable, sustainable, and usable. Ultimately, this dynamic reveals a deeper truth: many companies don’t need data scientists as urgently as they think . What they really need are data engineers who can ensure their data is structured, clean, and accessible. The insights, predictions, and models that data scientists produce are only as good as the underlying data infrastructure. So while some may continue to argue over who qualifies as a “real” data scientist, data engineers know that it’s not about the title—it’s about getting the job done. don’t need data scientists as urgently as they think If you’re an aspiring data engineer, this path could be your golden opportunity. By stepping into these misclassified data science roles, you can quietly build a career around solving the problems that others don’t want to touch. You can automate workflows, streamline processes, and ensure that the organization’s data infrastructure is solid and scalable. While your colleagues focus on tweaking their models, you’ll be building systems that bring real value to the company, and you’ll likely go unnoticed—until it becomes clear just how much the organization relies on the work you’ve done. In the end, data engineers are the ones who make data science possible. And for those willing to embrace the challenge, the rewards can be substantial—not only in terms of career growth but in the knowledge that you’re the one quietly keeping the data-driven machine running. About Me: 25+ year IT veteran combining data, AI, risk management, strategy, and education. 4x global hackathon winner and social impact from data advocate. Currently working to jumpstart the AI workforce in the Philippines. Learn more about me here: https://docligot.com https://docligot.com

Why Many Data Science Jobs Are Actually Data Engineering

Защо много работни места в науката за данни всъщност са инженерство на данни

Γιατί πολλές θέσεις εργασίας στην επιστήμη δεδομένων είναι στην πραγματικότητα μηχανική δεδομένων

Por qué muchos trabajos de ciencia de datos son en realidad ingeniería de datos

Miksi monet tietotekniikan työpaikat ovat itse asiassa tietotekniikkaa?

多くのデータサイエンスの仕事が実はデータエンジニアリングである理由

Pse shumë punë në shkencën e të dhënave janë në të vërtetë inxhinieri e të dhënave

Зашто су многи послови науке о подацима заправо инжењеринг података

Kwanini Kazi Nyingi za Sayansi ya Data Kwa Kweli Ni Uhandisi wa Data

ஏன் பல தரவு அறிவியல் வேலைகள் உண்மையில் தரவு பொறியியல்

ስለምንታይ ብዙሓት ናይ ዳታ ሳይንስ ስራሕቲ ብሓቂ ዳታ ምህንድስና ዝኾኑ

Nima uchun ma'lumotlar fanining ko'p ishlari aslida ma'lumotlar muhandisligidir

为什么许多数据科学工作实际上是数据工程

Reputation, in its most traditional definition, is a fragile tapestry of interaction amongst humans: an elaborate interplay between social proof, intuition, and subjectivity. It's an unspoken calculus by which we decide whom to trust, whom to listen to, and whom best to avoid when operating in the physical world. But in the decentralized world, this fluid-and-frail version of reputation must become hardened into something concretely mathematical, something machine-readable, and yet still quintessentially human. Its realization might be the most ambitious challenge for any designer of decentralized infrastructures. It is not only a question of how to make trust secure but also how to render reputation measurable, reliable, useful, and actionable outside the realm of theory. We are standing in front of a new frontier in trust, an age that requires us to make the notion of reputation programmable and enforceable. While blockchain technology promises a "trustless" world in which centralized intermediaries have no relevance, this vision leaves one critical part of human interaction. Guess what? It is how we quantify such subjective factors as trust and reputation without sacrificing the nuances that make it meaningful and untouched. This is where I want to dig deeper. From Abstract to Measurable: How Reputation Evolved Let me map the key paradox before going into the specifics of the solutions: On decentralized systems, reputation can't exist as an abstract conceptual philosophical issue. The trustworthiness of a user can't be left to subjective judgment on a peer-to-peer network. It has to be quantified, audited, and then enforced. And to actually design this effectively, we really have to resort not just to technology automating trust but encoding quite literally what reputation means. Let me outline three pressing challenges that reputation faces in decentralized systems: Reputation portability. While in a centralized system, reputation might be confined to one particular platform or network; in decentralized ecosystems, reputation has to be portable. This portability is necessary because users span multiple dApps, platforms, and ecosystems, from DeFi protocols to social marketplaces. Reputation data should not be left in silos. In itself, however, portability creates risks: reputation needs to be adapted to context. How can one protocol make assessments about an established reputation elsewhere? How does the user guarantee that standing in a decentralized social network applies in, for instance, a decentralized lending platform? Verifiable trust without full disclosure. Decentralized infrastructures prize privacy and anonymity. Still, trust (at least in its traditional sense) demands transparency. A balance needs to be reached whereby one's reputation can be verifiable without sensitive information about one's identity or past interactions. How can you prove you are reputable without giving away private transactions or other private information? Dynamic reputation systems. Trust is never set in concrete. A brilliant reputation today may be blemished tomorrow, but in the decentralized world, reputation cannot afford to remain static. Yet, blockchain's immutable nature creates an issue. How can we ensure that reputation reflects the real-time evolution of a user's trustworthiness? Autonomy Matrix and Aut: A Unified Approach to Trust Āutonomy Matrix and Āut's unified system is active in the space of proposing reputation, not as a concept but rather, as a real and integral part of the solution within a formalized environment. The system is working toward the implementation of a global reputation economy by using reputation scores pegged to DIDs. The gaps remain, though, even with forward momentum in these systems. Of these many intriguing proposals in this matrix, one of the more exciting involves adding zero-knowledge proofs to reputation management. ZKPs allow a person to prove some statement (for instance, that she has behaved in a trustworthy manner) without actually needing to reveal the underlying actions that came to that conclusion. For example, being able to prove that you have a 90% trust score across a DeFi lending platform without revealing just who lent or paid back what. This technique provides an extra layer of privacy, while a person's reputation is portable and provable in this decentralized and trustless environment. Now, a creative question: what if reputation could be tokenized itself? Just picture tokens of reputation flowing in value as any given user behaves well or badly. These would be transferable across platforms and would represent a liquid form of one's digital reputation. This might create "Reputation Markets" - a place where individuals and organizations can trade, lend, or borrow reputation. Undoubtedly, this would embed a layer of gamification, and reputation could be a currency while opening opportunities for abuse and innovation. Nevertheless, the idea that reputation can be digitized into something that one owns and can invest in, trade, or loan stretches the limits of how we think about trust. Filling the Gaps in Decentralized Reputation Making reputation measurable and, above all, safe, transforms it from an abstraction into something tangible, to which several structural elements need to be developed and deployed. Trust Provenance Protocols Just as decentralized systems record the origin of assets, so too does reputation require provenance. Smart contract histories could be attached to profiles, and decentralized systems might then track the origins of trust: who vouched for whom, on what terms, and under what circumstances. This all needs to be a lot more sophisticated than simplistic upvote or downvote mechanisms, as now exist on centralized platforms such as Reddit or Yelp. The origin of trust needs to weigh algorithmically according to context, not just frequency. For instance, the Reciprocity Index can be a decentralized algorithm that monitors the degree to which a user contributes to others' trust in the system versus the degree to which they benefit from it. Scores would rise for those giving trust freely and authentically, while those who merely benefit from others would see diminishing returns on reputation. Context-Aware Reputation Engines Reputation is inherently context-sensitive: the great coding reputation a user has on GitHub doesn't necessarily hold as much standing in some decentralized financial exchange. The silos can only be bridged by having context-aware reputation engines within decentralized protocols that would assess not raw reputation scores but the relevance of the latter for particular domains, dynamically adapting the user trust profiles in accordance with the environment. Reputation systems should also embed models of time decay in which the trust disappears unless it is kept alive. Applying temporal decay ensures that the reputational value will always be current. For example, a person who frequently participated in decentralized governance would see an increased reputation, whereas non-participation would equate to a decrease in their reputation score. This dynamic ensures that the trust indicators reflect the most recent behavior and, therefore, a real-time evolving snapshot of the reputation. Concluding Thoughts By aligning decentralized infrastructure with dynamic, cross-contextual reputation systems, we can push reputation from the realm of philosophy into a space where it's concrete and programmable. The integration of zero-knowledge proofs, time-weighted trust mechanisms, and cross-platform identity verification systems is not just the next step in decentralization but an entirely different approach to trust. But here's the rub: this is infrastructure that is not just technical; it is cultural. The tools we design to handle decentralized reputation must be ones that perform and reflect the rich nuances in human behavior. Trust is nuanced, multilayered, and evolves over time. If decentralized systems can handle that both in code and in practice, we might just build a future where reputation becomes as liquid an asset as currency itself. Perhaps someday, trust will no longer be a question but an asset to be made clear: securely, privately, and with confidence. Reputation, in its most traditional definition, is a fragile tapestry of interaction amongst humans: an elaborate interplay between social proof, intuition, and subjectivity. It's an unspoken calculus by which we decide whom to trust, whom to listen to, and whom best to avoid when operating in the physical world. But in the decentralized world, this fluid-and-frail version of reputation must become hardened into something concretely mathematical, something machine-readable, and yet still quintessentially human. Its realization might be the most ambitious challenge for any designer of decentralized infrastructures. It is not only a question of how to make trust secure but also how to render reputation measurable, reliable, useful, and actionable outside the realm of theory. We are standing in front of a new frontier in trust, an age that requires us to make the notion of reputation programmable and enforceable. While blockchain technology promises a "trustless" world in which centralized intermediaries have no relevance, this vision leaves one critical part of human interaction. Guess what? It is how we quantify such subjective factors as trust and reputation without sacrificing the nuances that make it meaningful and untouched. This is where I want to dig deeper. From Abstract to Measurable: How Reputation Evolved Let me map the key paradox before going into the specifics of the solutions: On decentralized systems, reputation can't exist as an abstract conceptual philosophical issue. The trustworthiness of a user can't be left to subjective judgment on a peer-to-peer network. It has to be quantified, audited, and then enforced. And to actually design this effectively, we really have to resort not just to technology automating trust but encoding quite literally what reputation means. Let me outline three pressing challenges that reputation faces in decentralized systems: Reputation portability. While in a centralized system, reputation might be confined to one particular platform or network; in decentralized ecosystems, reputation has to be portable. This portability is necessary because users span multiple dApps, platforms, and ecosystems, from DeFi protocols to social marketplaces. Reputation data should not be left in silos. In itself, however, portability creates risks: reputation needs to be adapted to context. How can one protocol make assessments about an established reputation elsewhere? How does the user guarantee that standing in a decentralized social network applies in, for instance, a decentralized lending platform? Reputation portability. While in a centralized system, reputation might be confined to one particular platform or network; in decentralized ecosystems, reputation has to be portable. This portability is necessary because users span multiple dApps, platforms, and ecosystems, from DeFi protocols to social marketplaces. Reputation data should not be left in silos. In itself, however, portability creates risks: reputation needs to be adapted to context. How can one protocol make assessments about an established reputation elsewhere? How does the user guarantee that standing in a decentralized social network applies in, for instance, a decentralized lending platform? Verifiable trust without full disclosure. Decentralized infrastructures prize privacy and anonymity. Still, trust (at least in its traditional sense) demands transparency. A balance needs to be reached whereby one's reputation can be verifiable without sensitive information about one's identity or past interactions. How can you prove you are reputable without giving away private transactions or other private information? Verifiable trust without full disclosure. Decentralized infrastructures prize privacy and anonymity. Still, trust (at least in its traditional sense) demands transparency. A balance needs to be reached whereby one's reputation can be verifiable without sensitive information about one's identity or past interactions. How can you prove you are reputable without giving away private transactions or other private information? Dynamic reputation systems. Trust is never set in concrete. A brilliant reputation today may be blemished tomorrow, but in the decentralized world, reputation cannot afford to remain static. Yet, blockchain's immutable nature creates an issue. How can we ensure that reputation reflects the real-time evolution of a user's trustworthiness? Dynamic reputation systems. Trust is never set in concrete. A brilliant reputation today may be blemished tomorrow, but in the decentralized world, reputation cannot afford to remain static. Yet, blockchain's immutable nature creates an issue. How can we ensure that reputation reflects the real-time evolution of a user's trustworthiness? Autonomy Matrix and Aut: A Unified Approach to Trust Āutonomy Matrix and Āut's unified system is active in the space of proposing reputation, not as a concept but rather, as a real and integral part of the solution within a formalized environment. The system is working toward the implementation of a global reputation economy by using reputation scores pegged to DIDs. The gaps remain, though, even with forward momentum in these systems. Of these many intriguing proposals in this matrix, one of the more exciting involves adding zero-knowledge proofs to reputation management. ZKPs allow a person to prove some statement (for instance, that she has behaved in a trustworthy manner) without actually needing to reveal the underlying actions that came to that conclusion. For example, being able to prove that you have a 90% trust score across a DeFi lending platform without revealing just who lent or paid back what. This technique provides an extra layer of privacy, while a person's reputation is portable and provable in this decentralized and trustless environment. Now, a creative question: what if reputation could be tokenized itself? Just picture tokens of reputation flowing in value as any given user behaves well or badly. These would be transferable across platforms and would represent a liquid form of one's digital reputation. This might create "Reputation Markets" - a place where individuals and organizations can trade, lend, or borrow reputation. Undoubtedly, this would embed a layer of gamification, and reputation could be a currency while opening opportunities for abuse and innovation. Now, a creative question: what if reputation could be tokenized itself? Just picture tokens of reputation flowing in value as any given user behaves well or badly. These would be transferable across platforms and would represent a liquid form of one's digital reputation. This might create "Reputation Markets" - a place where individuals and organizations can trade, lend, or borrow reputation. Undoubtedly, this would embed a layer of gamification, and reputation could be a currency while opening opportunities for abuse and innovation. Nevertheless, the idea that reputation can be digitized into something that one owns and can invest in, trade, or loan stretches the limits of how we think about trust. Nevertheless, the idea that reputation can be digitized into something that one owns and can invest in, trade, or loan stretches the limits of how we think about trust. Filling the Gaps in Decentralized Reputation Making reputation measurable and, above all, safe, transforms it from an abstraction into something tangible, to which several structural elements need to be developed and deployed. Trust Provenance Protocols Just as decentralized systems record the origin of assets, so too does reputation require provenance. Smart contract histories could be attached to profiles, and decentralized systems might then track the origins of trust: who vouched for whom, on what terms, and under what circumstances. This all needs to be a lot more sophisticated than simplistic upvote or downvote mechanisms, as now exist on centralized platforms such as Reddit or Yelp. The origin of trust needs to weigh algorithmically according to context, not just frequency. For instance, the Reciprocity Index can be a decentralized algorithm that monitors the degree to which a user contributes to others' trust in the system versus the degree to which they benefit from it. Scores would rise for those giving trust freely and authentically, while those who merely benefit from others would see diminishing returns on reputation. Reciprocity Index Context-Aware Reputation Engines Reputation is inherently context-sensitive: the great coding reputation a user has on GitHub doesn't necessarily hold as much standing in some decentralized financial exchange. The silos can only be bridged by having context-aware reputation engines within decentralized protocols that would assess not raw reputation scores but the relevance of the latter for particular domains, dynamically adapting the user trust profiles in accordance with the environment. Reputation systems should also embed models of time decay in which the trust disappears unless it is kept alive. Applying temporal decay ensures that the reputational value will always be current. For example, a person who frequently participated in decentralized governance would see an increased reputation, whereas non-participation would equate to a decrease in their reputation score. This dynamic ensures that the trust indicators reflect the most recent behavior and, therefore, a real-time evolving snapshot of the reputation. Concluding Thoughts By aligning decentralized infrastructure with dynamic, cross-contextual reputation systems, we can push reputation from the realm of philosophy into a space where it's concrete and programmable. The integration of zero-knowledge proofs, time-weighted trust mechanisms, and cross-platform identity verification systems is not just the next step in decentralization but an entirely different approach to trust. But here's the rub: this is infrastructure that is not just technical; it is cultural. The tools we design to handle decentralized reputation must be ones that perform and reflect the rich nuances in human behavior. Trust is nuanced, multilayered, and evolves over time. If decentralized systems can handle that both in code and in practice, we might just build a future where reputation becomes as liquid an asset as currency itself. Perhaps someday, trust will no longer be a question but an asset to be made clear: securely, privately, and with confidence.

The Tangible Reputation: Engineering Trust in a Decentralized World

Hmatatelná pověst: Inženýrská důvěra v decentralizovaném světě

La reputación tangible: generando confianza en un mundo descentralizado

La réputation tangible : l'ingénierie de la confiance dans un monde décentralisé

A kézzelfogható hírnév: Mérnöki bizalom egy decentralizált világban

具体的な評判: 分散化された世界における信頼の構築

ხელშესახები რეპუტაცია: საინჟინრო ნდობა დეცენტრალიზებულ სამყაროში

Материалдық бедел: орталықтандырылмаған әлемдегі инженерлік сенім

실체적 평판: 분산화된 세계에서의 신뢰 엔지니어링

Taustāmā reputācija: inženieru uzticība decentralizētā pasaulē

Опипљива репутација: инжењерско поверење у децентрализованом свету

እቲ ዝጭበጥ ዝና፡ ምህንድስናዊ ምትእምማን ኣብ ዘይተማእከለ ዓለም

Ang Tangible na Reputasyon: Engineering Trust sa isang Desentralisadong Mundo

Rapidly With These 4 Stupid Daily Habits People who are software developers spend many hours solving many problems, perpetually trying to always write better code. Long hours of problem-solving are draining even on the most resilient minds. Developers are often so engrossed with screens and lines of code that they never even realize that some of their daily habits are silly and working against their brain health. Habit 1: The Marathon Coding Sessions For many developers, working marathon coding sessions or pulling an all-nighter is almost a badge of honour. It becomes a normal case: something is due on the next day, for instance, a critical bug that needs to be worked on at once or a new feature that needs to be completed by the end of the week. The rush of adrenaline can make long hours of coding seem productive, but this forms one of the most destructive habits for brain health. Extended periods of focused work without adequate resting or refreshment interrupt the natural rhythm of the brain. The brain, like any other muscle, needs rest time to recover and consolidate. As developers enter these marathon sessions, they abandon sleep, which is essential for cognitive operations, memory consolidation, and emotional regulation. Sleep deprivation was established to lead to cognitive decline, a condition of inattention, and influences decision-making capacities. Prolonged sleep loss has been defined to affect neurodegenerative diseases such as Alzheimer’s. Additionally, the lengthy periods of concentration during these coding marathons can lead to mental burnout, a degradation in creative energy, and even emotional depletion. The developers should engage in the development of strategies that include regular breaks, scheduling hours of work, and sticking to healthy sleep patterns. A good example would be the Pomodoro Technique, where one works for 25 minutes and then rests for 5. In addition, having clear boundaries around hours of work and a regular sleep routine would add to the contribution of healthy cognition and productivity. Habit 2: Inactivity towards Body Exercise The frantic pace of technology has shrunk time for most ordinary people. Developers are no exception to this trend. They may find myriad reasons to sit idle rather than exercise. However, too much neglect can be disastrous for the brain. Regular physical exercise is beneficial to the body but also necessary for the brain. It increases blood flow to the brain, increases, and sharpens important cognitive functions such as memory, attention, and problem-solving abilities. It will also help the release of neurotransmitters such as dopamine and serotonin, which are essential in mood regulation and mental clarity. An inactive lifestyle can cause a person to suffer from poor blood flow, dull thinking, and increased vulnerability to the onset of mood disorders. In addition, an inactive lifestyle increases a person’s chances of developing obesity and heart disease, besides diabetes. All these are particularly bad for the brain. Developers should make efforts to introduce activity into their lifestyle, however slight the exercise session is. It can be initiated with a few minutes of exercising per hour and increased to much more profound outcomes with the inclusion of brisk walks, stretches, or a standing desk at work. The difference comes from reminder shots to move every hour, and scheduling exercises to do regularly. Habit 3: Neglecting Mental Stimulation However, the tech industry can trap developers into learning only what is required directly for work, and hence, continuous learning is important for professional growth. As if daily activity is ample to keep the mind stimulating, quite several developers leave this out of focus, and various risks will arise from cognitive stagnation. The brain loves novelty and challenge. When developers stop researching to find new knowledge or to intellectually stimulate themselves, the risk of cognitive stagnation looms overhead. Low problem-solving skills, reduced creative competence, and even higher risk of cognitive decline gradually decrease mental stimulation. Engagement in various learning activities-for example, through reading books, taking up other hobbies, or exploring new fields, keeps the brain lively and quick. Continuous learning and intellectual stimulation are exactly what can be used to maintain healthy cognitive activity and enhance mental performance. To prevent their cognitive function from getting stale, developers should also look for learning activities outside of their operational environment. One can enroll in an online course, attend a tech meetup, and learn one or two new programming languages and frameworks. Even dedicating a little time each week towards something new will be greatly beneficial to overall cognitive health. Habit 4: Neglecting Social Connections Coding puts developers in isolation by the fact that only a lone sits and focuses mainly on work and sets aside interactions. Also, this is a habit one usually overlooks, which can greatly affect mental health and cognitive functions. As humans, we are quite social. Strong social relationships provide an opening for the good maintenance of mental health. The stresses of life are aided by communicating with others and stimulating cognitive functions through worthwhile conversations and experiences. Various psychological conditions attributed to loneliness and isolation include depression and anxiety, among other cognitive decline. This form of isolation leaves developers feeling unrefreshed and, besides, getting overall dissatisfaction in terms of jobs. A developer needs to be able to maintain work and personal life, allocate time to social activities, and maintain family and friend relations. Such activities as team building activities, professional groups, or even informal social gatherings that can bring people closer together and enhance mental states are all contributive factors. Reaching out to colleagues and friends daily, even if just to pass a word here and there, could also contribute to greater living and improved well-being. Conclusion These habits appear trivial, but when one develops them over time, the danger to brain health escalates. Developers caught in the whirlwind of deadlines and coding challenges rarely pay attention to their selves or, indeed know the extent to which self-care impacts cognitive function. Developers may become aware of these toxic habits such as marathon coding sessions, lack of exercise, ignoring mental stimulation, and social isolation, etc. They can then take action proactively to protect their brain health and thus improve themselves. The quintessential change toward the adoption of healthy habits, work-life balance with adequate rest and exercise, continuous learning, and social engagement will go a long way in assuring and sustaining long-term healthy cognition. Given the high-level work environment of software development, these changes are not only beneficial but rather crucial to professional success and personal happiness as well. Such steps will thus ensure developers preserve their brain health while remaining successful in both their career and personal lives. Rapidly With These 4 Stupid Daily Habits Rapidly With These 4 Stupid Daily Habits People who are software developers spend many hours solving many problems, perpetually trying to always write better code. Long hours of problem-solving are draining even on the most resilient minds. Developers are often so engrossed with screens and lines of code that they never even realize that some of their daily habits are silly and working against their brain health. Habit 1: The Marathon Coding Sessions Habit 1: The Marathon Coding Sessions For many developers, working marathon coding sessions or pulling an all-nighter is almost a badge of honour . It becomes a normal case: something is due on the next day, for instance, a critical bug that needs to be worked on at once or a new feature that needs to be completed by the end of the week. badge of honour The rush of adrenaline can make long hours of coding seem productive, but this forms one of the most destructive habits for brain health. The rush of adrenaline can make long hours of coding seem productive, but this forms one of the most destructive habits for brain health. The rush of adrenaline can make long hours of coding seem productive, but this forms one of the most destructive habits for brain health. Extended periods of focused work without adequate resting or refreshment interrupt the natural rhythm of the brain. The brain, like any other muscle, needs rest time to recover and consolidate. As developers enter these marathon sessions, they abandon sleep, which is essential for cognitive operations, memory consolidation, and emotional regulation. Sleep deprivation was established to lead to cognitive decline, a condition of inattention, and influences decision-making capacities. Prolonged sleep loss has been defined to affect neurodegenerative diseases such as Alzheimer’s. Additionally, the lengthy periods of concentration during these coding marathons can lead to mental burnout, a degradation in creative energy, and even emotional depletion. The developers should engage in the development of strategies that include regular breaks, scheduling hours of work, and sticking to healthy sleep patterns. A good example would be the Pomodoro Technique , where one works for 25 minutes and then rests for 5 . In addition, having clear boundaries around hours of work and a regular sleep routine would add to the contribution of healthy cognition and productivity. Pomodoro Technique 25 minutes rests for 5 Habit 2: Inactivity towards Body Exercise Habit 2: Inactivity towards Body Exercise The frantic pace of technology has shrunk time for most ordinary people. Developers are no exception to this trend. They may find myriad reasons to sit idle rather than exercise. However, too much neglect can be disastrous for the brain. However, too much neglect can be disastrous for the brain. However, too much neglect can be disastrous for the brain. Regular physical exercise is beneficial to the body but also necessary for the brain. It increases blood flow to the brain, increases, and sharpens important cognitive functions such as memory, attention, and problem-solving abilities. It will also help the release of neurotransmitters such as dopamine and serotonin, which are essential in mood regulation and mental clarity. An inactive lifestyle can cause a person to suffer from poor blood flow, dull thinking, and increased vulnerability to the onset of mood disorders. In addition, an inactive lifestyle increases a person’s chances of developing obesity and heart disease, besides diabetes. All these are particularly bad for the brain. Developers should make efforts to introduce activity into their lifestyle, however slight the exercise session is. It can be initiated with a few minutes of exercising per hour and increased to much more profound outcomes with the inclusion of brisk walks, stretches, or a standing desk at work. The difference comes from reminder shots to move every hour, and scheduling exercises to do regularly. Habit 3: Neglecting Mental Stimulation Habit 3: Neglecting Mental Stimulation However, the tech industry can trap developers into learning only what is required directly for work, and hence, continuous learning is important for professional growth. As if daily activity is ample to keep the mind stimulating, quite several developers leave this out of focus, and various risks will arise from cognitive stagnation. The brain loves novelty and challenge. The brain loves novelty and challenge. The brain loves novelty and challenge. When developers stop researching to find new knowledge or to intellectually stimulate themselves, the risk of cognitive stagnation looms overhead. Low problem-solving skills, reduced creative competence, and even higher risk of cognitive decline gradually decrease mental stimulation. Engagement in various learning activities-for example, through reading books, taking up other hobbies, or exploring new fields, keeps the brain lively and quick. Continuous learning and intellectual stimulation are exactly what can be used to maintain healthy cognitive activity and enhance mental performance. To prevent their cognitive function from getting stale, developers should also look for learning activities outside of their operational environment. One can enroll in an online course, attend a tech meetup, and learn one or two new programming languages and frameworks. Even dedicating a little time each week towards something new will be greatly beneficial to overall cognitive health. Habit 4: Neglecting Social Connections Habit 4: Neglecting Social Connections Coding puts developers in isolation by the fact that only a lone sits and focuses mainly on work and sets aside interactions. Also, this is a habit one usually overlooks, which can greatly affect mental health and cognitive functions. As humans, we are quite social. As humans, we are quite social. As humans, we are quite social. Strong social relationships provide an opening for the good maintenance of mental health. The stresses of life are aided by communicating with others and stimulating cognitive functions through worthwhile conversations and experiences. Various psychological conditions attributed to loneliness and isolation include depression and anxiety, among other cognitive decline. This form of isolation leaves developers feeling unrefreshed and, besides, getting overall dissatisfaction in terms of jobs. A developer needs to be able to maintain work and personal life, allocate time to social activities, and maintain family and friend relations. Such activities as team building activities, professional groups, or even informal social gatherings that can bring people closer together and enhance mental states are all contributive factors. Reaching out to colleagues and friends daily, even if just to pass a word here and there, could also contribute to greater living and improved well-being. Conclusion These habits appear trivial, but when one develops them over time, the danger to brain health escalates. Developers caught in the whirlwind of deadlines and coding challenges rarely pay attention to their selves or, indeed know the extent to which self-care impacts cognitive function. Developers may become aware of these toxic habits such as marathon coding sessions, lack of exercise, ignoring mental stimulation, and social isolation, etc. They can then take action proactively to protect their brain health and thus improve themselves. These habits appear trivial, but when one develops them over time, the danger to brain health escalates. Developers caught in the whirlwind of deadlines and coding challenges rarely pay attention to their selves or, indeed know the extent to which self-care impacts cognitive function. Developers may become aware of these toxic habits such as marathon coding sessions, lack of exercise, ignoring mental stimulation, and social isolation, etc. They can then take action proactively to protect their brain health and thus improve themselves. The quintessential change toward the adoption of healthy habits, work-life balance with adequate rest and exercise, continuous learning, and social engagement will go a long way in assuring and sustaining long-term healthy cognition. Given the high-level work environment of software development, these changes are not only beneficial but rather crucial to professional success and personal happiness as well. Such steps will thus ensure developers preserve their brain health while remaining successful in both their career and personal lives. The quintessential change toward the adoption of healthy habits, work-life balance with adequate rest and exercise, continuous learning, and social engagement will go a long way in assuring and sustaining long-term healthy cognition. Given the high-level work environment of software development, these changes are not only beneficial but rather crucial to professional success and personal happiness as well. Such steps will thus ensure developers preserve their brain health while remaining successful in both their career and personal lives.

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