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(WARNING — Not for the faint-hearted.) With the advent of the Medium “Top Writer” status, everyone wants to get their hands on one. Or in some cases 5. Or maybe even more. It’s possible. There are a few tricks that you must master before reaching this elusive status. Once you do, your follower growth will accelerate like never before! These are 8 simple tricks I used to accelerate my own growth on Medium. 1. I increased my writing time. I used the Pomodoro technique to keep my energy levels continuously high. I’ve elaborated further on this in the article below. It outlines the basic cyclic timetable that I used to write my stories and how it helps replenish my ever-depleting energy bank. This is also an unknown remedy to feel continuously inspired to write. Here’s how I reached my optimal creativity as a writer. 2. I turned my responses into stories. When your follower count is low, you daily reads will obviously be low. But there’s a way around this. No matter where you write (a story or response), Medium counts it as a story. The following are all responses I wrote to other writers’ stories, which I turned into a story of my own. They all hauled in over 100+ views each (which doesn’t seem like much — but mind you these were in different reader communities, giving me a wider reach than publishing one story within a single community). Medium is all about bouncing ideas off different writers. Some ideas are fresh, some aren’t so much. Still, it counts as a story doesn’t it? I made sure to take full advantage of every loophole in the system. 5 facts about true love How writing has helped me blossom as a person. 3. I tagged appropriately. I used my tags appropriately and wisely and made sure I had a healthy output of stories for each tag. I didn’t want to limit myself to a niche. I had my roller-coaster moods as a writer— my stories were bound to fall under widely contrasting tags. So I published under a wide scope of tags which were different from each other. The results? I’m now a Top Writer of 7 categories. 4. I didn’t publish like a freak. GIPHY Not at all. I published at least 1 Op-Ed a day for the first month. These were 400–600-word essays that I meticulously edited and re-wrote. I know countless other writers who did the same. It wasn’t a tough task at all. I made sure I published in publications with at least 5k followers or more. I have my own publications which are steadily growing by the day, but I needed the well-established platforms of certain long standing publications to spread my reach. It feels a tad bit crazy now that I look back. I might bring this number down to a couple of Op-Eds a week, which doesn’t seem much at all. Other than that, I published shorter stories and responses that are less than 100 words each. These were mostly impulsive and typed fresh right at the computer. Remember, no matter the word count, a story is a story. Sometimes it’s torture for the keyboard. If my keyboard died, I would’ve gotten a new one and repeated all over again. Hello, that’s what real writers do. They write and write and write, even after they’ve forgotten why they started writing in the first place. 5. I clapped generously for others’ stories. GIPHY This made sure others would return me the favour whenever I published a story that they liked. People love to be appreciated and nothing makes them happier than the feeling of being noticed by someone else. (You can do the same for me too if you haven’t cracked yet seeing and his clapping stand-up bit.) Preacher Lawson 6. I used the Co-Schedule “ ” to trim my headlines. Headline Analyser tool This was sort of a 50–50. Not all headline scores are perfect. This tool deducts marks for lengthier headlines. But from my experience, Medium readers tend to be more responsive to longer headlines. The scores I’ve shown are for my best story so far on Medium. You can read it right below. The title has 5 unique words (26 characters total) while the tagline has 8 (35 characters). recommends 6 words for a headline and 55 characters for a tagline. Buffer Are you a ‘Born Creative’? 7. My drafts list was always full. I always kept a few drafts ready a few days ahead, scheduled to publish. This kept a steady stream of content flowing out. If I missed a day, I made sure to respond to others’ stories on Medium instead. I then tagged every response with suitable tags. 8. I used to check my grammar for me. Grammarly Who wastes time nowadays when there are apps to check your grammar for you? Duh. Please do clap and help others find this story. Connect with me on , , , and . Share your pains with me. I’m an open book. Medium Twitter Facebook Flipboard

8 simple tricks I used to become a Top Writer of 7 categories in less than a month.

The Future of Education and AI: Beyond Traditional Degrees with Marc Andreessen & Ben Horowitz

শিক্ষার ভবিষ্যত এবং এআই: মার্ক অ্যান্ড্রেসেন এবং বেন হোরোভিটজের সাথে ঐতিহ্যগত ডিগ্রির বাইরে

Die Zukunft von Bildung und KI: Jenseits traditioneller Abschlüsse mit Marc Andreessen und Ben Horowitz

El futuro de la educación y la IA: más allá de las titulaciones tradicionales con Marc Andreessen y Ben Horowitz

L'avenir de l'éducation et de l'IA : au-delà des diplômes traditionnels avec Marc Andreessen et Ben Horowitz

शिक्षा और एआई का भविष्य: मार्क आंद्रेसेन और बेन होरोविट्ज़ के साथ पारंपरिक डिग्री से परे

教育と AI の未来: マーク・アンドリーセンとベン・ホロウィッツによる従来の学位を超えて

교육과 AI의 미래: Marc Andreessen 및 Ben Horowitz와 함께하는 전통적인 학위를 넘어서

O futuro da educação e da IA: além dos diplomas tradicionais com Marc Andreessen e Ben Horowitz

Будущее образования и искусственного интеллекта: за пределами традиционных степеней с Марком Андриссеном и Беном Горовицем

Eğitimin ve Yapay Zekanın Geleceği: Marc Andreessen ve Ben Horowitz ile Geleneksel Derecelerin Ötesinde

Tương lai của Giáo dục và AI: Vượt xa các bằng cấp truyền thống với Marc Andreessen & Ben Horowitz

教育和人工智能的未来：马克·安德森 (Marc Andreessen) 和本·霍洛维茨 (Ben Horowitz) 的超越传统学位

You can jump to any section of the National Aeronautics Science & Technology Priorities here. How to Use the Resilience Grand Pathways Framework The Grand Pathways Framework is designed to point the way to science and technology innovation supporting multiple , and . For example, when considering the impacts of natural hazards and a changing climate on the safety and security of communities and the economy, the framework can help users map out the key functions and crosscutting enablers that are necessary to support those societal dimensions. Users can then explore the vulnerabilities of those key functions and cross-cutting enablers to various threats and hazards, including natural hazards. societal dimensions, key functions cross-cutting enablers For example, users could identify a surface transportation network that is critical to both the community’s economy in steady state and to safety in the event of a disaster (Figure 3). At the same time, they might identify a coastal park that creates ecotourism opportunities in steady state and that provides a buffer against storm surge during hurricanes. Framework users could then look for interdependencies across elements, such as a surface road and adjacent subsurface utility corridor that rely on the coastal park’s wetlands for protection against storm surge and scouring wave action. Such exploration helps users discover elements common across societal dimensions. With a fuller understanding of commonalities and interdependencies, framework users can then start to identify gaps where new science and technology investments would be most beneficial in building the property of resilience. In spanning multiple societal dimensions and/or cross-cutting enablers, the Grand Pathways Framework has the potential to make a large impact in strengthening a community’s resilience along multiple frontiers. Figure 3 overlays this example on the Grand Pathways Framework structure to show how a science and technology solution could investigate two cross-cutting enablers and one key function, in support of three societal dimensions. The next section explores other uses cases. This was originally published in March 2023 on It has been broken-up into bite sized sections, each with unique headlines and AI-generated lead images, in line with the provisions of whitehouse.gov. Creative Commons 3.0.

How to Use the Resilience Grand Pathways Framework

Ed Maste, the Director of Technology at the FreeBSD Foundation, discusses the rapidly-evolving interplay between hardware, cybersecurity, open source, and instruction set architectures. 1. Cybersecurity is traditionally thought of from a software mindset—but what do developers need to understand about the role of hardware security? Hardware is often the battleground where cyber attackers and security software vie for control. Because of that, there are tremendous opportunities for robust hardware security to effectively pull the rug out from under would-be attacks by simply disallowing attack mechanisms from functioning in the first place.
 
Hardware security already plays a prominent role in several key areas. For example, trusted platform modules (TPMs) and secure boot ensure that devices run only trusted software while booting, eliminating the opportunity for attack software to compromise or tamper with systems. Hardware-based encryption solutions that protect data on hard drives and networks are another common hardware security use case.
 
But more recently, emerging hardware security technologies are introducing some welcome new capability architectures for thwarting ever-more-sophisticated threats that software-based security measures have struggled to address. As these hardware capabilities and architectures grow to reshape mainstream cybersecurity practices, teams should be prepared to adapt and adopt new strategies that incorporate the combined protections of both software and hardware-based measures. 2. How has open source development impacted hardware security? I believe that the active collaboration intrinsic to developing and advancing open source projects—software or hardware—makes for a more hardened solution than just about any closed-source organization could produce. Mature open source projects have so many eyeballs on them and so many diverse, global perspectives that constant iteration is inherent. Hardware security is particularly receptive to these benefits.
 
With open source, anybody interested in contributing to a hardware security project can openly review all hardware designs and source code. That open invitation to test for vulnerabilities and introduce new creative approaches and improvements has allowed hardware security to innovate and evolve at a rapid clip. It’s reasonable to argue that many of the most exciting hardware security technologies available today would not exist or wouldn’t be what they are without the power of open source collaboration. Instruction-set architectures (ISAs) and extensions are a strong example of this, offering open source-hardened hardware foundations from which software can execute securely. 3. Digging deeper into ISAs—what is their role in hardware security? ISAs provide the specification of the instructions that a microporcessor uses to execute commands. Therefore, it’s possible to implement and enforce secure conditions and protections at the foundational level of a device’s operations.
 
ISAs are a critical part of device functionality and hardware security. For example, the x86 ISA is present on most desktops, laptops, and servers (having evolved through the 16-bit, 32-bit, and 64-bit eras). The ARM ISA is a mainstay of smartphones, tablets and other devices including servers (64-bit ARM), due to its low-power consumption attributes. The has thrived as a research platform and is earning increasing attention as a modern flexible option. A major factor in RISC-V’s success is the fact that it’s open source. The open source FreeBSD operating system offers support for x86, ARM, RISC-V, and the OpenPower Foundation’s open source Power ISA. Other ISAs are available as well to provide security and advantageous features for numerous further use cases.
 
When it comes to delivering hardware-level security, specific ISAs offer a variety of valuable features. For instance, an ISA and extensions might provide built-in data execution prevention, data encryption, and memory protection—eliminating the threats of particular attacks or security vulnerabilities within software running on that ISA-protected hardware. RISC-V ISA 4. Are there any shortcomings with ISA, or concerns that developer teams exploring them should be aware of? I think it’s important for teams to understand ISAs beyond just their lists of (compelling) features. They should assemble a logical, comprehensive, and strategic security technology stack that aligns hardware and software protections. Just as ISAs can forbid software-based attacks, they may be incompatible with particular security software. This is especially a concern if the selected ISA isn’t yet a widely supported one.
 
Also, ISAs can suffer from vulnerabilities and attack exploits, similar to how software can be affected. Therefore, organizations must keep their CPU microcode updated to prevent ISA vulnerability risks. 5. What can you tell us about the CHERI ISA, and the FreeBSD-based CheriBSD? A lot! is an open source research project being developed by the University of Cambridge and SRI International, which has gained traction as a hardware security solution via its new approach to data access control and memory protection. With the CHERI ISA, all memory access happens through a “capability” that features hardware-based bounds and permissions. With capabilities controlling access to memory regions and supported by hardware and runtime safeguards, CHERI’s promising spatial memory security offers to neutralize an entire range of memory-focused attacks—such as buffer overflows and use-after-free vulnerabilities. CHERI also shows potential in providing high-performance compartmentalization, such that attackers can’t access data without authorization.
 
While CHERI is churning through its R&D phase, ISA leaders are producing promising prototypes with the technology. is the most advanced of the prototypes; it combines CHERI with a high-performance super-scaler core on a system-on-chip demonstration platform. CheriBSD is a FreeBSD extension enabled with CHERI capabilities, capable of providing memory security and software compartmentalization. Designed for use with Arm’s Morello and CHERI-RISC-V platforms, CheriBSD offers developer teams using those platforms a fully memory-safe environment for desktop software development, and represents a leading achievement in ISA hardware-based security. CHERI Arm’s Morello platform 6. Wrapping up, how should developers feel about hardware security right now? Hardware security is the bedrock of your overall system security. Its role continues to magnify as security threats get more complex. Consider, for example, the growing concern over supply chain attacks, where the bad guys infiltrate the production process of hardware components, embedding backdoors or vulnerabilities that can be exploited later. Incidents like these continue to underscore the need for uber-rigorous hardware security practices—and fortunately there’s a lot of progress to be excited about. I’m also proud of the role FreeBSD is playing in advancing hardware security. Through collaborative efforts and the power of open source communities, the project is an active contributor to the development of secure hardware.

The Cybersecurity Battle Has Come to Hardware

I have always been very conscious about how and where I spend my time. While I paid a lot of attention to the obvious ways to be more productive—create a distraction-free focused zone, limit time on social media, divide my work into small blocks of time, and take regular breaks to revive and rejuvenate—I missed a crucial element that often gets in the way of our productivity. Our brain. The human brain has this remarkable cognitive capacity to perform at levels far beyond what we consider our natural abilities, but it’s not without its limits. The that enable the brain to prioritize and process large amounts of information quickly also get in the way of our productivity. These mental shortcuts are the brain's way to conserve energy and work more efficiently. But they also lead to many thinking errors. cognitive biases Here are the 4 cognitive biases that have the biggest impact on our productivity—how we prioritize, make decisions, manage time, and get work done. Urgency effect Zeigarnik effect Complexity bias Planning fallacy Urgency effect When an urgent task comes knocking at the door, do you push important work aside because urgent tasks demand your immediate attention while important goals are far off into the future and can wait until later? Urgency effect makes us jump at every chance to solve time-sensitive urgent matters while putting off important work. Rationally our brain knows that important tasks have a larger payoff and bigger rewards in the long run, but under the effect of this bias, we fall victim to perceiving urgent as important. Urgent tasks keep us busy and make us feel important, but they also suck into our time. Prioritizing it at the expense of more impactful work keeps us trapped in an illusion of productivity. Why we fall for the urgency effect Important tasks typically have no specific deadline. They are time-consuming and complex as they often require looking into the future and proactively identifying its needs. Giving clarity to vague ideas, making crucial decisions, or laying out a future strategy is not only time-consuming, it’s also mentally taxing. Urgent tasks have easy-to-reach, visible goals. They bring instant gratification with a big hit of dopamine. Since dopamine serves as a reinforcement for remembering and repeating pleasurable experiences, you end up dedicating more time to urgent tasks at the expense of more impactful work. Continuously pushing important tasks to the back burner keeps us locked in a never-ending cycle of unproductive choices—dedicating less time to important work inevitably creates more urgency later. Important tasks become urgent in due course of time if delayed too much, not given proper attention, or carried out without real interest. Example of urgency effect Gina is the tech manager of the CRM team. The latest releases in ChatGPT and other AI innovations is becoming a threat to her business. But instead of spending time planning how to make them a part of their future strategy, Gina ends up spending most of her time on emails, meetings, and other urgent tasks. Her busyness keeps her locked in a cycle of unproductivity and inefficiency. Urgency effect makes her pay more attention to the work right in front of her—emails, chat notifications, customer escalations—while pushing important work aside. How to avoid urgency effect A great practice to avoid urgency bias involves using The Eisenhower Matrix for prioritization. To put the Eisenhower matrix to use, go through each task one by one and separate them into four possibilities: Important and Urgent (Quadrant 1): reduce time spent here Important and Not Urgent (Quadrant 2): consciously prioritize and schedule these tasks Not Important and Urgent (Quadrant 3): delegate these tasks Not Important and Not Urgent (Quadrant 4): declutter and eliminate. Consciously scheduling dedicated hours on the calendar to do important work makes it more likely that you attend to them without interruptions. A few other practices to adopt: Set aside specific blocks of time for responding to emails, chats, or other such tasks. Reduce time spent in meetings. Utilize your peak productivity period to do your most important work. Matching your energy with the physical and mental demands of work will enable you to do your best work making it more likely for you to continue instead of giving up. Set deadlines for important tasks and hold yourself accountable for meeting them. Zeigarnik effect Thoughts of unfinished tasks keep popping up in our head right when we get down to work or are trying hard to focus. *Emails we haven’t replied to.* Pending design to compete. Meetings to schedule. … so on and on. These intrusive thoughts that take away our attention even for a split second make it hard to concentrate and get any meaningful work done. Distractions from incomplete work prevent us from entering into a state of flow—which is when we are completely immersed in a task and the time seems to stand still. Flow minimizes distractions, prevents procrastination, and lead to high performance and productivity. Named after psychologist Zeigarnik who first discovered it, the effect refers to the tendency to remember unfinished or interrupted tasks better than completed ones. Letting our brain continually remind us that we haven’t done something is quite unpleasant and it can even lead to stress, anxiety, and burnout. Why we fall for the Zeigarnik effect Zeigarnik and her professor Kurt Lewin observed that their restaurant waiters remembered everyone’s orders despite never writing anything down. But as soon as the bill was paid, they had little or no memory of who their customers were or what they had ordered. This led to a series of experiments based on which Zeigarnik concluded that human minds treat tasks that have been completed differently from those that are still left to be completed. A task that has already been started establishes a task-specific tension, which keeps it at the forefront of our memory. The tension is relieved upon completion of the task but persists if it is interrupted or not yet completed. That’s why unfinished tasks keep coming back to haunt us. Look another way, these reminders can be useful to help us finish incomplete projects only if they do not spoil our attention right in the middle of another project. Attention is like energy in that without it no work can be done, and in doing work is dissipated. We create ourselves by how we use this energy. Memories, thoughts and feelings are all shaped by how we use it. And it is an energy under control, to do with as we please; hence attention is our most important tool in the task of improving the quality of experience. ― Mihaly Csikszentmihalyi Example of Zeigarnik effect Zeigarnik effect is used in gamification: Progress trackers informing users of how close they are to completing a task. For example, when users see a message like "Your profile is 34% complete", they are more likely to spend a few minutes providing all the missing details. This technique is used by to collect user information in a super smart way. LinkedIn Checklists that provide users with a clear step-by-step flow to onboard users faster and more effectively. Interrupted commercials are more likely to be remembered than those that are not due to the Zeigarnik effect. Advertisers use it to catch the attention and memory of viewers. How to avoid the Zeigarnik effect by Florida State University shows that planning work upfront and writing it down can free your mind from distracting thoughts about unfinished work. Have daily, weekly, and monthly rituals to review, prioritize, and plan what you intend to do. When you miss something and it pops up in your head, don’t leave it hanging there, immediately write it down. Research Moving tasks from your head onto paper relaxes your brain and helps you focus on the task at hand. A few other practices to adopt: Avoid procrastination by using the Zeigarnik effect to your advantage. Instead of putting things off because they are big or complex, simply take a very small step towards it. Once you get started, your brain will kick off the Zeigarnik effect enabling you to keep going till the end. Use the Pomodoro method to divide your work into small chunks of focused time. The tactical breaks in the Pomodoro method improve memory and keep productive momentum going. Complexity bias Given a choice between two competing solutions, we are likely to choose the more complex one. Jargon catches our attention over simple explanations. Difficult-to-execute strategies impress us over straightforward ones. Sophisticated products appear more authoritative while ordinary ones appear inferior. But complexity has many problems: Knowing upfront that something is difficult can prevent us from getting started. Obstacles and challenges along the way make it hard to persist and we may give up too soon. It can delay decision-making. It’s costly as it requires more time, effort and resources to get done. It can be potentially dangerous. Not understanding something fully can lead to wrong assumptions and conclusions. It can lead to hiding mistakes and fundamental flaws. Complexity bias is the tendency to prefer complicated explanations, solutions, and arguments over easy ones. Why we fall for the complexity bias Many people mistake simple for easy. Finding simple solutions to problems may sometimes require more effort—a conscious effort to dig deeper and give way to our creative mind, avoiding biases to cut through complexity and finding solutions that do not require too much scaffolding to support. Complexity in such cases could be an excuse to label the problem as too confusing and shove it aside. We choose complexity over simplicity for another reason: it’s falsely associated with expertise, innovation and authority. The more complex or advanced the approach is, the more superior it appears. Put another way, if a solution is too simple, we assume it won’t solve the problem. This makes us inject complexity and over complicate things instead of choosing a simpler approach. \As Edsger Wybe Dijkstra, a Dutch computer scientist once said “Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.” Example of complexity bias Jim got an opportunity to prepare and present the design of a new product to his entire team. He wanted the solution to stand out and establish credibility with others. But instead of asking the question “What problem is this product required to solve and how can I solve it in the simplest way possible?” he asked, “What problem is this product required to solve and how can I make it look good?” Trying to make the solution appealing led to poor choices: Instead of choosing a simple technology he understood well, he decided to use a new technology with no experience or expertise. He made complex architectural decisions to make the product look sophisticated. He introduced features that added little to no value to a customer but sounded interesting to implement. Complexity bias in his case led to poor decisions and terrible choices. How to avoid the complexity bias To counteract complexity bias, apply Occam’s razor. It is one of the most useful mental models to solve problems. Occam’s razor advocates simplicity by focusing on key elements of the problem, eliminating improbable options, and finding solutions with fewer assumptions. Another useful mental model to reduce complexity is first principles thinking. It requires breaking down a problem into its fundamental building blocks (its essential elements), asking powerful questions, getting down to the basic truth, separating facts from assumptions, and then constructing a view from the ground up. A few other practices to adopt: Since complexity bias shields you from seeking simple solutions, asking for others' opinions may be helpful. You may ask “Is my solution too complex or confusing?” Question your intent. Reframe the end goal to align it with the outcomes you wish to achieve. Show bias for action. Instead of being stuck in analysis paralysis, take a small step towards your goal, see how it works, and slowly improve it over time. Planning fallacy When it comes to setting deadlines, most of us are highly optimistic. Even if it’s something similar to what we have done in the past, we are still likely to underestimate how much time it will take to do it in the future. It took one week to finish a design proposal last time, but if you have to do it again, you’re positive it will get done in less than a week. It took more than a month for your new hires to get onboarded last time, but while planning for the new batch coming in next week, you allocated only 2 weeks. The planning fallacy is what makes us commit to overly optimistic timelines, miss those deadlines, and then drown in guilt, anxiety, and stress. Not factoring in realistic demands of the task leads to poor planning for the future. It harms your reputation and also breaks trust because when you miss those deadlines, others assume that you don’t take your commitments seriously. Why we fall for the planning fallacy When estimating the time it will take to complete a specific task, we ignore risks and other unlikely events that may prevent us from completing the task on time. Taking the best-case scenario into account and ignoring the obstacles we might encounter along the way leads to wishful thinking. We have the best intentions to get the work done quickly and efficiently, but good intentions aren’t always enough. Good planning needs good estimation skills. Another reason why we are highly optimistic about completing a specific job is our tendency to get stuck in the nitty gritty while ignoring the big picture. Not taking the big picture into account leads to poor estimation—we make wrong assumptions and ignore the time it will take to integrate our work into the bigger picture. We are also really bad at accurately judging our skills and abilities. Our enthusiasm to meet our goals adds to the planning fallacy. \Worst part? We don’t even learn from our past mistakes. Even when we can recognize past mistakes when we are overly optimistic, we keep on making the same mistakes in the future. We focus on our goal, anchor on our plan, and neglect relevant base rates, exposing ourselves to the planning fallacy. We focus on what we want to do and can do, neglecting the plans and skills of others. Both in explaining the past and in predicting the future, we focus on the causal role of skill and neglect the role of luck. We are therefore prone to an illusion of control. We focus on what we know and neglect what we do not know, which makes us overly confident in our beliefs. ― Daniel Kahneman Example of the planning fallacy Tina is working on the estimates of a new product. She has worked on a similar product in the past. The last time she built the product, it took her 3 months to complete. The project was initially estimated for 2 months but took an additional month due to requirements changes, a longer testing cycle, and other unforeseen issues. Tina has experience from the past that she should put to use to determine how long it will take to complete the current project. However, due to the planning fallacy, she commits to a 2-month deadline again. She justifies it by assuming that her experience from the past project will help her finish the tasks sooner while completely disregarding the additional time it will take to handle unexpected issues. How to avoid planning fallacy Break down the project into small parts and estimate how long each one will take. Doing this work upfront will make your effort estimates much closer to reality than being vaguely guided by hunch. Another great strategy is the one recommended by Daniel Kahneman - He suggests taking an outside view of your estimates by consulting others—asking questions and identifying problems and mistakes they made on similar projects in the past. You can’t do this for all your tasks but definitely do it for your most crucial ones. Irrespective of how good you’re at estimation, some unlikely event can crop up and make your project fall through the cracks. It isn’t possible to take every such scenario into account and plan for it. But what’s possible is to add a little buffer to your estimates—add 20% breathing room while considering the effort it takes to do something. Finally, and this is the most important one: implement a feedback loop in your process. Track your time. Make a note of how long it takes to do something. When you miss deadlines, identify what mistakes you made and what changes you need in your planning process to do better next time. When you’re conscious of how these biases—Urgency effect, Zeigarnik effect, Complexity bias and Planning fallacy—affect your time and apply the right strategies to overcome them, you can be your most productive self. Summary Most of us struggle with getting work done efficiently because we don’t pay attention to the cognitive biases that get in the way of using time productively. Urgency effect makes us waste time attending to urgent tasks at the cost of important tasks. Not paying attention to the future needs keeps us trapped in a cycle of unproductivity. The Zeigarnik effect prevents us from giving our best to the task at hand. When our mind keeps reminding us of incomplete or interrupted tasks, it’s hard to stay focused and pay attention. Complexity bias makes us add unnecessary complexity to solutions which increases the time, effort and cost to solve even simple problems. Planning fallacy tricks our mind to give highly optimistic estimates to achieve a certain goal despite our previous experience telling us that it will be impossible to achieve it. This story was previously published . here Follow me on or here for more stories. LinkedIn

Tackling the Saboteurs Within: 4 Cognitive Biases That Affect Your Productivity

এর মধ্যে নাশকতাকারীদের মোকাবেলা করা: 4টি জ্ঞানীয় পক্ষপাত যা আপনার উত্পাদনশীলতাকে প্রভাবিত করে

Die inneren Saboteure bekämpfen: 4 kognitive Vorurteile, die sich auf Ihre Produktivität auswirken

Enfrentando a los saboteadores internos: 4 sesgos cognitivos que afectan su productividad

S'attaquer aux saboteurs intérieurs : 4 biais cognitifs qui affectent votre productivité

भीतर के तोड़फोड़ करने वालों से निपटना: 4 संज्ञानात्मक पूर्वाग्रह जो आपकी उत्पादकता को प्रभावित करते हैं

内部の妨害者に対処する: 生産性に影響を与える 4 つの認知バイアス

내부의 파괴자 대처 방법: 생산성에 영향을 미치는 4가지 인지 편향

Enfrentando os sabotadores internos: quatro preconceitos cognitivos que afetam sua produtividade

Борьба с внутренними саботажниками: 4 когнитивных искажения, которые влияют на вашу продуктивность

İçimizdeki Sabotajcılarla Mücadele Etmek: Verimliliğinizi Etkileyen 4 Bilişsel Önyargı

Giải quyết những kẻ phá hoại bên trong: 4 thành kiến nhận thức ảnh hưởng đến năng suất của bạn

解决内部破坏者：影响生产力的 4 种认知偏差

From the widely discussed Helpful Content Update (HCU) to the Search Generative Experience (SGE), 2022 was not the year for rest nor relaxation for most SEOs and content professionals. Google has seen more changes in the last year than in the last decade. I recently shared my experience of using for the first time. And how the AI overviews differ for different keywords and queries. Search Generative Experience (SGE) I have also been ringing the bells around Google’s visibly changing SERPs, and how it’s . killing organic reach A visual summary below 👀 Source Notice how ‘above the fold’ now comprises an AI overview, a couple of organic links, and a whole bunch of SERP elements (knowledge panels, People Also Ask, etc.). This is the beginning of a new Googleverse and a potential loss of your organic traffic. The antidote? I have five. 5 Ways to Stop the Potential Loss of Traffic to SGE and Grow Your Audience Like every other content professional, while I’m excited about SGE, I can’t help but wonder how SEO will change as SGE evolves. I’m sure you’re brimming with questions too. But at the moment, it will be a waste of time to worry about that. After all, SGE is still in the infancy stage. Over time, there are going to be many iterations and improvements to the model. So, what can you do? Other than creating valuable content, here are five ways your organic content can shine without SEO: Create content for native consumption Produce content with original research Build and document a distribution strategy Use executive branding for audience building Experiment with content formats (video, interactive product tours, webinars, podcasts, and more) Let’s explore each one in detail below. Build and document a distribution strategy Google has been cannibalizing clicks even before SGE was a thing. This happened in the form of a zero-click search. However, such zero-click responses were only relegated to straightforward queries like ‘ . What is content marketing?’ But with SGE in the picture, it’s different. You’re not just competing against the SERP elements like featured snippets or knowledge panels, but with the comprehensive AI overviews as well. This is why having a distribution strategy pays off. Instead of trying to optimize for SGE/SEO and waiting to be discovered, build a distribution system that lets you share and promote content in places where your target audience hangs out. Published a research report? Promote it via newsletter sponsorship. Released a new podcast episode? Share short clips on YouTube and Instagram. Wrote a new blog post? Share the juicy bits with a link on LinkedIn. You get the drift. Create content for native consumption Speaking of a distribution strategy, I have to mention the most abused content distribution and promotion practice: link dumping. Back when Facebook was in its prime, you could dump a blog post link and get a steady stream of traffic. Today? You’ll be happy to get a CTR of at least 1%. That’s because nobody likes moving away from the platform they’re engaged with. If someone is scrolling through LinkedIn, they want to read and engage with the content on LinkedIn instead of clicking away. By creating content for native consumption, you can keep your audience engaged and interested in learning more. And if you want to promote your content on social sites, be a little more creative. Rather than dumping the link as is, you should: Share the juiciest bit of information to compel the readers into clicking. Turn the key takeaways from the eBook to create a carousel. Visualize the data with graphs and charts. Ask the readers how they relate to the numbers. Pick a controversial or thought-provoking excerpt and get the conversation going in the comments. The key to a good content distribution (promotion) strategy is having a good repurposing strategy. Source original research and data When you think “Inbound Marketing”, you think HubSpot. When you think “zero-click search”, you think SparkToro. And when you think “sales intelligence”, you think of Gong. This is the power of brand recall. When you produce original, data-driven content, you get to shine in a sea of sameness (including SGE’s blandness) and build a loyal fanbase. One of my favorite examples of brands using content as a differentiating factor is Gong. Despite having roughly 1000+ sales tech solutions as competitors, they have managed to build a higher brand recall thanks to the original content. You’ll rarely find their company blog ranking high on SERPs, but ask any sales professional and they’ll tell you that Gong has the best sales content. These are a few reasons why. They use data sourced from real sales conversations to craft blog posts. You won’t find the information they provide elsewhere. Source: Gong Blog All their content is created for a clearly defined audience: sales leaders, AEs, and managers in tech companies. They write in a conversational, non-boring tone while providing actionable advice. Use executive branding for audience building Mark Schaefer, , shares in his why personal branding is essential in a post-SEO era: best-selling author and renowned marketer blog post “The ability to benefit from SEO depends on a special set of circumstances, and increasingly SEO isn’t going to create a return. The other option is to create content that establishes authority through thought leadership. In this way, you can earn attention and an audience without depending on search engines and ads.” Even great content gets buried between the many SERP folds. But if you’ve managed to build a trustworthy personal brand, you will have people waiting (eagerly) and going back to your opinions, values, and content. This is something SGE cannot replace. Here are a few ways to get started with executive branding. Build a following on social media. It costs nothing to get on platforms like LinkedIn, X, or Medium and share your entrepreneurial journey, what you’re building, or validate the idea for your next launch. Invest in digital PR to boost your digital footprint. It will also help shape your public image, and by extension, your brand’s. This could mean giving interviews, joining podcasts, guesting on webinars, or writing guest posts. The last tactic was how initially. Buffer’s Co-founder Leo Widrich grew the number of app users from 0 to 100000 Connect with journalists and content professionals through Help a B2B Writer (HaBw) and Help a Reporter Out (HARO). Share responses and quotes occasionally. This is a simple method of getting a mention on authoritative websites and scoring a backlink free of cost. Experiment with content formats Is a majority of your content efforts concentrated around blogging? Does your audience or reading the blog posts? Think about it. want like It makes sense for a company like Zapier or Scribe to publish 50+ blog posts every month. Since they sell a horizontal product catering to varying personas, Search is one of the best content marketing channels for them to target. This, however, would make zero sense for a company like Freshpaint, a healthcare data privacy platform, which sells to busy healthcare professionals and organizations. As their Head of Content, Mark Rogers, explains in the , SEO isn’t a priority for his team because their customers take advice from peers, not Google. Content, Briefly podcast Another example is Ahrefs. They created a ‘Blogging for Business’ video course to promote Ahrefs and , as Tim Soulo shares in his blog post. managed to snatch 500k+ views while bringing mid-five figures in revenue There’s no dearth of content formats to try – from podcasts, and webinars to seminars and more, you can dip your toes into a variety of’em. It gives you the benefit of meeting your audience where they hang out (perhaps on Instagram?) and provides the experience and content SGE cannot. So, find out what resonates with your audience and stick to it. Final Thoughts SEO has never been a passive strategy. While it’s too soon to conclusively say anything about the impact SGE will have on organic traffic, there are ways to win beyond SEO. As outlined above, methods like personal branding or doubling down on content distribution can ensure your content is consumed by the right people at the right time. Once we have more data about SGE and its impact, we’ll be able to devise better ways for sure.

How to Stop the Potential Loss of Traffic in the Era of AI-Powered Search

এআই-চালিত অনুসন্ধানের যুগে ট্র্যাফিকের সম্ভাব্য ক্ষতি কীভাবে থামানো যায়

So stoppen Sie den potenziellen Traffic-Verlust im Zeitalter der KI-gestützten Suche

Cómo detener la posible pérdida de tráfico en la era de la búsqueda impulsada por la IA

Comment arrêter la perte potentielle de trafic à l'ère de la recherche basée sur l'IA

एआई-संचालित खोज के युग में ट्रैफ़िक के संभावित नुकसान को कैसे रोकें

AI を活用した検索の時代に潜在的なトラフィック損失を阻止する方法

AI 기반 검색 시대에 트래픽 손실 가능성을 막는 방법

Como impedir a perda potencial de tráfego na era da pesquisa baseada em IA

Как остановить потенциальную потерю трафика в эпоху поиска на основе искусственного интеллекта

Yapay Zeka Destekli Arama Çağında Potansiyel Trafik Kaybı Nasıl Durdurulur

Cách ngăn chặn khả năng mất lưu lượng truy cập trong kỷ nguyên tìm kiếm được hỗ trợ bởi AI

如何阻止人工智能搜索时代潜在的流量损失

The chemistry of converting raw data into golden opportunities for demand generation is a mastery sought by many but perfected by few. The intersection of data and analytics with demand generation represents not merely a trend but a fundamental shift in how businesses approach market engagement and customer acquisition. With precision analytics, companies are not just passively observing market behaviors; they are actively predicting and shaping future demands. Recently, I interviewed , a Demand Gen Lead at . Steve Armenti Google Can you share a bit about yourself? I’m from New Hampshire and lived most of my life in New England. After college, I landed a sales job at an accounting software company outside of Boston. I was an SDR making 100 phone calls a day trying to book meetings with CFOs. This was 10 years ago before marketing and sales automation was as prevalent as it is today. However, I taught myself how to manually segment my territory using spreadsheets and designed my own A/B email experiments to get meetings. Eventually, I stopped making phone calls altogether and was producing the highest numbers on the team purely from emails. I didn’t know it but I was using ABM + personalization. Being in sales taught me about the human element of marketing and sales. At the end of every marketing campaign is an actual person who is trying to solve problems. In marketing, we often forget that as we sit in our office buildings (or home offices) designing campaigns. I try to remember that there are real people on the other end, just like us, and they can smell your bullsh*t from a mile away. How does data-driven decision-making impact B2B demand generation? In my opinion, it’s everything. I’ve built most of my career on using data to inform a variety of decisions: small and large about B2B demand generation and growth. Data can remove human error and opinion from the situation. For example, let’s say marketing and sales are feuding about the quality of MQLs. MQL quality can be very subjective. What matters is alignment between marketing and sales on what accounts you’re targeting, who in those accounts you’re acquiring, and what are their pain points. Who is the ideal customer profile? All of those things can be measured with data. You can pull data to show that an MQL came from a target account and that the persona is precisely the proper seniority, title, and job function. The data is used to establish a baseline of what is true and what is opinion. If you don’t have the data to prove what is true, go get it before you get into a shouting match. What specific data points are crucial for understanding B2B buyer behavior? I like to first look at a combination of demographics, firmographics, and psychographics. You can get these data points from 1P and 3P research, persona development, your website and marketing data, your CRM, surveys, and focus groups. This will give you a basic understanding of who is in your total addressable market. Second, I want to look at my data. How do customers behave? This data requires analyzing the person-level data against all of your marketing activities. The question you want to answer is “How does [persona] engage with [marketing campaign] and what is the behavior they are taking as a result” my Doing this exercise at scale will unlock a trove of insights about your customer that you can then organize and segment to fit the needs of your campaigns. What role does predictive analytics play in B2B demand generation? Predictive analytics can play a big role in any B2B demand gen program. It requires a solid data analytics infrastructure though first. Assuming there is a data warehouse and process in place to clean and ingest data, predictive analytics can help marketers do many things: Identify the highest propensity accounts, personas, and segments. Predict the timing of purchase intent helping your sellers reach out at the most opportune time Personalize messages or notifications based on user behavior Predict the effectiveness of a campaign or activity And now, with AI, this entire process is speeding up. AI will become better at collecting and processing large amounts of data to identify patterns and trends that marketers can take action on in real-time. As the prediction engine runs, and AI is feeding results back even faster than ever, marketers shift their role to the entire operation versus managing the hands-on creation process of marketing campaigns. directing How can businesses effectively leverage CRM data in demand-generation efforts? CRM data is a goldmine of information. It’s the source code to what makes your customers tick and what incentivizes them to buy. CRM data can be used to identify which accounts and personas have the highest propensity to buy. CRM data can be used to segment your audience into different groups based on their needs, interests, and purchase behavior. CRM data can be used to optimize your campaigns and improve performance. At the end of the day, all marketing should be measured on its ability to drive revenue – and your CRM is one of the most critical data sources to be able to do that. What are the common challenges in collecting and utilizing data for demand generation? Data silos. When data is stored in different systems and applications, it becomes really difficult to access and analyze. The accuracy and completeness of your data is important once you break down the silos. As they say, garbage in garbage out. So if you organized the data but it’s still crap quality, you aren’t even close. Collecting and utilizing data for demand generation can be a resource-intensive process often requiring skilled data scientists. This is a challenge in itself. Proper data infrastructure is essential to good B2B demand generation. That said, I think a big challenge the industry is facing is a lack of analytical skills for the average marketer. The marketer of the future needs to be as analytical as they are creative. How do you ensure data quality and accuracy in B2B demand generation campaigns? It starts with cleaning the data. Make sure you have a process to clean and join together the various data sources you want to use. You might find you are missing certain quality markers so you will need to look at enriching the data through other 1P sources or by licensing 3P data. Once you have a complete picture of your data (often called a data dictionary), you will want to validate that the data is accurate either through testing and QA or with an actual validation tool. Could you explain how data segmentation enhances B2B lead nurturing? Data segmentation is all about dividing your leads and contacts into groups based on certain characteristics, such as industry, company size, job title, location, or historical behavior. You want to use segmentation so you can tailor your marketing and sales messages to each group, increasing the chances they will take the action you want them to take. Using segmentation allows you to improve your targeting and make it more precise, increase the relevance and personalization of your email, and improve the efficiency of email as a channel overall. You send less messages that produce better results. What tools and technologies are indispensable for data-driven B2B demand generation? There are a million of them but you will want a demand platform, marketing automation platform, CRM, customer data platform, web/SEO/content analytics, social media software, and A/B testing software. I’m partial to , , , , , and . , , , , and are also great products. Demandbase Marketo Salesforce GrowthLoop Google Analytics SproutSocial HubSpot Kissmetrics Mailchimp Optimizely Buffer How does personalization based on data improve B2B lead conversion rates? At a high level, when you personalize your message, you show people that you understand their needs and interests. This can make them more likely to pay attention to your messages and grow an affinity toward your brand. This will likely increase the chances that people will engage with your marketing and do what you want them to do. Personalization is a game of compounding value. As your audience continues to feel like you understand them and can meet their needs, they go deeper into the funnel evaluating your product or service. Marketing continues to personalize until the person raises their hand and takes action or wants to talk to sales. The personalization doesn’t stop here. Onboarding, sales enablement, and product discovery all need to continue the experience the person felt during the evaluation process. How do you bridge the gap between data analytics and actionable demand-generation strategies? In my opinion, it’s a linear process that goes like this: Get your house (data warehouse) in order. Collect, clean, and ingest all the data you want into one source of truth Build the proper data pipelines to fuel your teams. Data needs to flow from the warehouse into dashboards, CDPs, reporting, etc. so teams can review that data in real-time Automate insights and reporting. Most of the regular, day-to-day reporting you need to do is simply looking at the same KPIs weekly and/or monthly. Standardize those KPIs and the reports. Set calendar invites for when you want your team to look at it. Pull your top insights and develop commentary about what changed from the last reporting period and why. Run optimization sprints. After you’ve collected insights, rank the top ones using some priority method [e.g. Reach, Interact, Convert, and Engage (RICE)] and go and A/B optimizations. Do this in a sprint fashion so you get quick feedback and quick data. That feedback and data flows back into your pipelines and the cycle becomes a perfect loop. What emerging trends in data and analytics are shaping the future of B2B demand generation? AI, of course. I’m stoked about what AI is going to do for B2B demand generation. On the data side, I’m personally exploring how AI can automate the collection and analysis of data, improve insights and decision-making, and identify patterns and trends in data that go unseen by humans to better understand customers and prospects. On the creative side, I’m excited about personalizing our marketing to each person. Right now I use a framework that identifies target accounts, ICP (personas), and then segments. The next level of this is down to the actual person. I’m also really interested in AI for the use of predictive performance and analysis in demand generation. Launching campaigns is a time-consuming process and when it fails, a lot of resources, budget, and time are wasted. With AI, predicting the success rate of campaigns is possible. Additionally, prediction around which accounts, personas, and people are most likely to buy is incredible. This plus the personalization is like Michael Jordan and Scottie Pippen in the 90s – unstoppable. Also published . here

What Google Can Teach Us About Effective B2B Demand Generation

Daniel Roe — Core team member at Nuxt.js Hello, dear readers! I’m back with another insightful piece, this time focusing on the developer experience in Nuxt 3, as presented by Daniel Roe, a core team member of Nuxt. Daniel also did a live coding session which covered all the following topics in action. If you want to watch that, or the entire talk, you can find it on . YouTube Intro Daniel Roe, with his background as a CTO of a SaaS startup and experience with a creative agency, emphasizes the significance of the developer experience. Having been a user of Nuxt, he understands the challenges developers face and believes that enhancing this experience is beneficial for both developers and companies. He believes that improving the developer experience is beneficial for everyone. It aids the developer in implementing their ideas faster and more efficiently, and it’s also advantageous for companies as it leads to quicker and better results. The vision is to be as minimal as possible, as lightweight as possible, and to reduce context switching Typescript in Nuxt 3 One of the significant changes in Nuxt 3 is the full integration of Typescript. This doesn’t mean developers have to use Typescript, but it offers full control of the IDE, generating a file that sets paths and provides type hinting. tsconfig.json Nuxt 3 takes full control of the developer’s IDE. This is achieved by generating a file. This configuration file is the heart of any Typescript project, and by controlling it, Nuxt 3 can introduce a plethora of features. tsconfig.json For instance, it sets paths for every alias defined in the Nuxt project, whether it's by Nuxt itself, some other module, or an additional library. This ensures that developers have a smooth experience with imports, type hinting, and other IDE features. Documentation at Fingertips One of the significant advantages of using Typescript is the ability to provide inline documentation. Nuxt 3 leverages this by moving as much documentation as possible into the editor. This includes detailed descriptions of functions, their parameters, expected return types, code examples, and even links to further reading. This approach ensures that developers have immediate access to crucial information without having to switch contexts or browse external documentation. Reducing Boilerplate in Nuxt 3 One of the standout features of Nuxt 3 is its commitment to reducing boilerplate code, making the developer experience smoother and more intuitive. Here’s a deeper dive into how Nuxt 3 achieves this: Auto-imported Functions In Nuxt 3, developers no longer need to manually import commonly used functions. For instance, when using Vue 3, functions like , , and are frequently utilized. In Nuxt 3, these are auto-imported, eliminating the need for repetitive import statements. ref onMounted reactive This not only reduces the noise in the code but also streamlines the coding process. <script setup>
const props = defineProps ({ name: String })
const greeting = computed(() => 'Hi ${props. name]')
</script>

<template>{{ greeting }}</template> Minimal Initial Setup A fresh Nuxt 3 project comes with a minimal set of files. This includes: : The starting point of the application. app.vue : While this configuration file is present, it's initially empty and can often remain so, thanks to Nuxt's convention-over-configuration approach. nuxt.config : Contains just one dependency - Nuxt. package.json : A configuration file generated by Nuxt to take full control of the IDE, enabling features like path aliases and type hinting. tsconfig.json Smart Data Fetching Nuxt 3 introduces an isomorphic fetch function, , which smartly handles response headers. This function can determine whether the response is text, JSON, an array buffer, or another type, and processes it accordingly. $fetch This eliminates the need for developers to manually parse responses, making data fetching more intuitive. export default defineEventHandler (event => {
  const { id } = useQuery(event) // /api/user?id-1 => 1
  const user = await $fetch( https: //api.dev/users/${id}*)
  return {
    id,
    user,
  }
}) Server Functions In Nuxt 3, server functions can directly return objects, such as JSON. This means developers no longer need to set headers or stringify responses manually. This approach not only simplifies server-side code but also powers type inference, providing developers with accurate type hints when fetching from these endpoints. Conclusion I hope you enjoyed this part and that it was as valuable to you as it was to me. Over the next few days, I’ll share the rest of the talks with you. Stay tuned… Shout out to my friend , who made me excited to write the next part. Shahrokh Also published here

The Developer Experience With nuxt 3: Here's What You Need to Know

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