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In the TED Talk below, Dr. Daniel Kahneman, Inventor of Behavioral Economics, explains how our happiness is determined and sometimes distorted by what he describes as our two selves. Dr. Daniel Kahneman, two selves The Way a Story Ends The Way a Story Ends The Way a Story Ends We must be conscious of the way a story ends in our memories. A bad ending can make our Remembering Self permanently unhappy about an otherwise very happy experience. Therefore, it's essential to recognize and compartmentalize a negative ending in what's going to be a memory narrative. We must be conscious of the way a story ends in our memories Remembering Self it's essential to recognize and compartmentalize a negative ending in what's going to be a memory narrative. Storytime Storytime In between Panama and Colombia, there are 300 islands that are strangely omitted on Google Maps — or any of the other maps I’ve seen of the southern Caribbean. A personal experience:In 2012, I took one of the coolest vacations of my life. While traveling from Central to South America, I spent four days in the surreal San Blas Islands (between Panama and Colombia). It was a time of relaxation on sunny beaches, meeting the locals of the islands (and even learning a little of their language), eating great food, drinking fine wine and rum by bonfires, making new friends, and snorkeling in clear waters. However, it ended with two fairly disastrous events: 1) At the border crossing, my passport was almost ruined by water damage, and 2) On our first night in Colombia, we got robbed. In 2012, I took one of the coolest vacations of my life. While traveling from Central to South America, I spent four days in the surreal San Blas Islands (between Panama and Colombia). It was a time of relaxation on sunny beaches, meeting the locals of the islands (and even learning a little of their language), eating great food, drinking fine wine and rum by bonfires, making new friends, and snorkeling in clear waters. However, it ended with two fairly disastrous events: 1) At the border crossing, my passport was almost ruined by water damage, and 2) On our first night in Colombia, we got robbed. When these two negative events happened, I made a conscious decision to categorize them as simply part of the risks of travel and not include them in my mental narrative of the San Blas Islands vacation. When these two negative events happened, I made a conscious decision to categorize them as simply part of the risks of travel and not include them in my mental narrative of the San Blas Islands vacation. When these two negative events happened, I made a conscious decision to categorize them as simply part of the risks of travel and not include them in my mental narrative of the San Blas Islands vacation. Memory anticipation feedback loops - Our remembering self is in charge of making decisions based on future anticipated memories. We derive a lot of happiness from these self-fulfilling prophecies, so if there's a decision you need to make, imagine yourself being happy in the future, reflecting on the decision. Memory anticipation feedback loops remembering self based on future anticipated memories self-fulfilling prophecies Spend time with people you like - and who make you feel good about yourself. It's the most significant measurable factor of happiness. Spend time with people you like the most significant measurable factor of happiness Make it to $60,000 - It turns out money does buy happiness, but the happiness-to-income correlation flattens out at $60,000 a year for Americans and other comparable countries. So, do whatever it takes to get your income to $60,000/yearly, but after that, focus on other areas of your life to maximize happiness. Make it to $60,000 the happiness-to-income correlation flattens out at $60,000 a year Thought Experiment Thought Experiment At the end of a vacation, all your pictures are going to be destroyed, and you will receive a drug that gives you amnesia. All your memories of the vacation are going to be destroyed. Would you choose the same activities? At the end of a vacation, all your pictures are going to be destroyed, and you will receive a drug that gives you amnesia. All your memories of the vacation are going to be destroyed. Would you choose the same activities? If so, then it illustrates a significant difference between the way your Remembering Self and your Experiencing Self perceive happiness. Remembering Self Experiencing Self My question for Dr. Kahneman is, do biological happiness and healthiness correlate more to the Experiencing Self or the Remembering Self? Should we, as biohackers, be more focused on maximizing Experiential Happiness or creating Happy Memories? biological happiness and healthiness correlate more to the Experiencing Self or the Remembering Self? biological happiness and healthiness correlate more to the Experiencing Self or the Remembering Self? Should we, as biohackers, be more focused on maximizing Experiential Happiness or creating Happy Memories? https://www.ted.com/talks/daniel_kahneman_the_riddle_of_experience_vs_memory?embedable=true https://www.ted.com/talks/daniel_kahneman_the_riddle_of_experience_vs_memory?embedable=true 0:30 - Over 40 books published in the last 5 years with happinessin the title; happiness is researched thoroughly1:07 - 1st Trap of Happiness is a reluctance to admit complexity; the wordhappinessis too general, and we need to adopt a more complex view1:30 - 2nd Trap Confusion Between Experience and Memory, being happy in your life and being happy about your life1:50 - 3rd Trap Focusing Illusion, we cannot think about any factor of well-being without distorting its significance.2:55 - The two selves; theExperiencing Self  (in the present), the Remembering Self(keeps score of our life). They are very different.3:45 - The notion of happiness gets confused between the two selves.5:30 - Example from medical operations: when the story or memory that ended in pain is negatively colored, the entire dialog6:50 - The ending of the story makes the biggest difference.7:20 - The psychological present is about 3 seconds long.7:40 - TheRemembering Selfonly focuses on very few of these8:08 - The biggest difference between the two selves is the handling of time.9:00 - TheRemembering Self is the one that makes decisions, the Experiencing Selfhas very little to do with the decision making process.9:40 - We think of our future as anticipated memories. We live at the tyranny of theRemembering Self.11:15 - Thought Experiment: At the end of vacation, all your pictures are going to be destroyed, and you will receive an amnesiac drug. All your memories of the vacation are going to be destroyed. Would you choose the same activities?13:56 - A person's moment-to-moment happiness (theExperiencing Self) can vary drastically from the happiness they feel when they think about their life (the Remembering Self).14:50 - The biggest factor of happiness is spending time with people we like.15:00 - We should not think of happiness as a substitute for well-being.17:17 - Happiness of theExperiencing Self for Americans, below $60,000/Yearly people are unhappy, above $60,000/Yearly money does not buy you happiness - the Experiencing Self's happiness graph goes flat. happiness happiness Experiencing Self Remembering Self Remembering Self Remembering Self Experiencing Self Remembering Self Experiencing Self Remembering Self Experiencing Self Experiencing Self The paradox of happiness is that the more you pursue and worry about happiness, the less happy you'll be. I explain why here... I explain why here

The Remembering Self and the Experiencing Self: A Paradox to Happiness Hackers

Authors:
(1) SIMONE CASALE-BRUNET, École Polytechnique Fédérale de Lausanne, Switzerland;
(2) MIRKO ZICHICHI, Universidad Politécnica de Madrid, Spain;
(3) LEE HUTCHINSON, WhaleAnalytica.com, Switzerland;
(4) MARCO MATTAVELLI, École Polytechnique Fédérale de Lausanne, Switzerland;
(5) STEFANO FERRETTI, University of Urbino “Carlo Bo”, Italy. Authors: Authors: (1) SIMONE CASALE-BRUNET, École Polytechnique Fédérale de Lausanne, Switzerland; (2) MIRKO ZICHICHI, Universidad Politécnica de Madrid, Spain; (3) LEE HUTCHINSON, WhaleAnalytica.com, Switzerland; (4) MARCO MATTAVELLI, École Polytechnique Fédérale de Lausanne, Switzerland; (5) STEFANO FERRETTI, University of Urbino “Carlo Bo”, Italy. Table of Links 1 Introduction 1 Introduction 2 State of Art 2 State of Art 3 Projects Selection and Data Collection 3 Projects Selection and Data Collection 3.1 Blockchain data 3.1 Blockchain data 3.2 Twitter data 3.2 Twitter data 4 Data Analysis and Results 4.1 Ethereum wallets and Twitter users and 4.2 The communities 4.1 Ethereum wallets and Twitter users and 4.2 The communities 4.3 Hashtags 4.3 Hashtags 4.4 The role of the social network community 4.4 The role of the social network community 5 Conclusions and References 5 Conclusions and References This paper presents an analysis of the role of social media, specially Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early projects such as "CryptoPunks" and since early 2021, has received an increasing interest by a community of people creating, buying, selling NFTs and by the media reporting to the general public. In this work it is shown how the landscape of one class of projects, specially those used as social media profile pictures, has become mainstream with leading projects such as "Bored Ape Yacht Club", "Cool Cats" and "Doodles". This work illustrates how heterogeneous data was collected from the Ethereum blockchain and Twitter and then analysed using algorithms and state-of-art metrics related to graphs. The initial results show that from a social network perspective, the collections of most popular NFTs can be considered as a single community around NFTs. Thus, while each project has its own value and volume of exchange, on a social level all of them are primarily influenced by the evolution of values and trades of "Bored Ape Yacht Club" collection. 1 INTRODUCTION Non Fungible Tokens (NFTs) are a booming technology, with a trading volume that - in just one year - has increased from $150 million to over $5 billion (recorded in January 2022 by considering only the transactions that took place on the Ethereum blockchain [2] through the main exchange platform OpenSea) [19]. Public attention towards NFTs has exploded since the beginning of 2021, when the NFT market experienced record sales and exchange volumes, up to the present day where individual pieces for some projects have reached prices of millions of dollars and have been purchased by a number of celebrities. However, little is known about the overall structure and evolution of the NFT ecosystem, or how this phenomenon has also grown thanks to the communities that have formed in social networks, such as Twitter. In a simplistic way, we can define an NFT as a unique digital asset whose information (such as features, traits and ownership) is certified and managed using blockchain technology. In other words, we can think of a NFT project as a set of football player cards. Each card of the set is di#erent from the others because of some specific traits (e.g., a player can be more or less wanted), the circulation of each card is fixed, and the owner of each card is known and traceable. The set of cards is managed on the blockchain by means of a smart contract, while each card represents an indivisible token. More specifically, NFTs are an example of a Distributed Ledger Technology (DLT) application that renders trustworthy intermediaries such as banks and notary firms obsolete [24]. In fact, cryptographic tokens based on DLTs, through guaranteed enforcement of encoded obligations (e.g., through smart contracts), can combine both concepts of (i) access rights to an underlying economic value (property) [5, 13], and (ii) a permission to access someone else’s property or services or a collective good. NFTs and their technology are already being used in a number of varied fields. Some examples include: the certification of digital generative artworks, the representation and management of land and objects ownership in the metaverse, and the certification of ownership of a profile image in social networks, such as Twitter. It is this latter use case of profile picture images (PFPs) that has been one of the largest contributors to the popularity of NFT technology during the past year. There have been digital figurine projects whose cards were previously trading for a few hundred dollars in early 2021 and whose average price today is in the hundreds of thousands of dollars. Leaving aside the purely economic aspect, this phenomenon of using NFTs as profile pictures has both social and technological interest that, in our opinion, are worth researching deeper. In fact, the use of profile pictures belonging to a digital collection with a limited circulation (typically 10,000 different figurines) and whose ownership is certified by a distributed ledger, introduces some entirely new and disruptive concepts. First of all, those who use a profile picture, with no apparent relation to their own photo, seek to eliminate stereotypes and preconceptions by hiding themselves in a sort of anonymity typical of the crypto world; moreover, it allows the user the ability to create a digital persona (that may or may not have any relation to their real identity from which their subconscious may wish to escape) [26]. Second, the fact of having a limited number of cards (a limit forced by construction by the smart contract written on blockchain) provides the possession of some of them (such as the CryptoPunks and Bored Ape Yacht Club) with real digital status symbols that allow the owner to highlight the fact that she or he has been a person in the crypto world for a long time or economically successful. Third, the owner of a figurine in a particular project can sometimes enjoy digital or real benefits: such as being able to access restricted discussion rooms in social networks like Discord or take part real world or metaverse special events and parties. This allows a union of real and digital worlds where the concept of ownership is easily transportable and usable, without requiring going through intermediaries. From the personal experience of the authors of this work, Twitter and Discord represent the two most representative and used social networks for people interested in NFTs of the PFPs type, where real communities have been created. This work, the first of its kind, aims to analyze the activity of the most PFPs in the Twitter ecosystem: which turns out to be both the main communication channel of these communities and the one most easily analyzed thanks to its content query API. In this paper we wanted to apply state of art social network analysis (SNA) techniques to analyze these communities and verify how they interact and drive the NFTs market and how they are interconnected. SNA techniques are in fact widely used in application areas such as community and topic detection [6]. In this paper we took 18 most significant NFT profile pictures projects and collected all their blockhain transactions and all their related tweets starting from the date of creation to April 15th, 2022. Next, we analyzed the data obtained from Twitter by creating two different kind of graphs: one related to tweets with commonalities between each project pair and a second related to tweets having common hashtags. We then analyzed which communities are the most influential in this ecosystem and how they interact with each other. The paper is structured as follows: Section 2 presents an overview of SNA techniques available in literature. Next, Section 3 discusses which projects have been selected for this work, the rationale for choosing them among others and how the data were collected from Twitter and the Ethereum blockchain. Next, Section 4 presents which SNA analyses have been conducted and the results obtained. Finally, Section Section 5 concludes this paper by providing future research insights. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Remember When NFTs Were All the Rave on Twitter?

**BOSTON, USA, March 11th, 2025/CyberNewsWire/--**GitGuardian, the security leader behind GitHub's most installed application, today released its comprehensive "2025 State of Secrets Sprawl Report," revealing a widespread and persistent security crisis that threatens organizations of all sizes. The report exposes a 25% increase in leaked secrets year-over-year, with 23.8 million new credentials detected on public GitHub in 2024 alone. Most concerning for enterprise security leaders: 70% of secrets leaked in 2022 remain active today, creating an expanding attack surface that grows more dangerous with each passing day. "The explosion of leaked secrets represents one of the most significant yet underestimated threats in cybersecurity," said Eric Fourrier, CEO of GitGuardian. "Unlike sophisticated zero-day exploits, attackers don't need advanced skills to exploit these vulnerabilities—just one exposed credential can provide unrestricted access to critical systems and sensitive data."Eric Fourrier points to the 2024 U.S. Treasury Department breach as a warning: "A single leaked API key from BeyondTrust allowed attackers to infiltrate government systems. This wasn't a sophisticated attack—it was a simple case of an exposed credential that bypassed millions in security investments." "The explosion of leaked secrets represents one of the most significant yet underestimated threats in cybersecurity," said Eric Fourrier, CEO of GitGuardian. "Unlike sophisticated zero-day exploits, attackers don't need advanced skills to exploit these vulnerabilities—just one exposed credential can provide unrestricted access to critical systems and sensitive data."Eric Fourrier points to the 2024 U.S. Treasury Department breach as a warning: "A single leaked API key from BeyondTrust allowed attackers to infiltrate government systems. This wasn't a sophisticated attack—it was a simple case of an exposed credential that bypassed millions in security investments." Key Findings for Security Leaders The report identifies several critical trends that demand immediate attention: The Blind Spot: Generic Secrets Despite GitHub's Push Protection helping developers detect known secret patterns, generic secrets—including hardcoded passwords, database credentials, and custom authentication tokens—now represent more than half of all detected leaks. These credentials lack standardized patterns, making them nearly impossible to detect with conventional tools. Private Repositories: A False Sense of Security The analysis reveals a startling truth: a full 35% of all private repositories scanned contained at least one plaintext secret, shattering the common assumption that private repositories are secure: AWS IAM keys appeared in plaintext in 8.17% of private repositories—over 5× more frequently than in public ones (1.45%)
Generic passwords appeared nearly 3× more often in private repositories (24.1%) compared to public ones (8.94%)
MongoDB credentials were the most frequently leaked secret type in public repositories (18.84%) AWS IAM keys appeared in plaintext in 8.17% of private repositories—over 5× more frequently than in public ones (1.45%) Generic passwords appeared nearly 3× more often in private repositories (24.1%) compared to public ones (8.94%) MongoDB credentials were the most frequently leaked secret type in public repositories (18.84%) "Leaked secrets in private code repositories must be treated as compromised," emphasized Eric Fourrier. "Security teams must recognize that secrets should be treated as sensitive data regardless of where they reside." "Leaked secrets in private code repositories must be treated as compromised," emphasized Eric Fourrier. "Security teams must recognize that secrets should be treated as sensitive data regardless of where they reside." Beyond Code: Secrets Sprawl Across the SDLC Hardcoded secrets are everywhere, but especially in security blind spots like collaboration platforms and containers environments where security controls are typically weaker: Slack: 2.4% of channels within analyzed workspaces contained leaked secrets
Jira: 6.1% of tickets exposed credentials, making it the most vulnerable collaboration tool
DockerHub: 98% of detected secrets were embedded exclusively in image layers, with over 7,000 valid AWS keys currently exposed Slack: 2.4% of channels within analyzed workspaces contained leaked secrets Jira: 6.1% of tickets exposed credentials, making it the most vulnerable collaboration tool DockerHub: 98% of detected secrets were embedded exclusively in image layers, with over 7,000 valid AWS keys currently exposed The Non-Human Identity Crisis Non-human identities (NHIs)—including API keys, service accounts, and automation tokens—now vastly outnumber human identities in most organizations. However, these credentials often lack proper lifecycle management and rotation, creating persistent vulnerabilities. A security leader at a Fortune 500 company acknowledged this challenge: "We aim to rotate secrets annually, but enforcement is difficult across our environment. Some credentials have remained unchanged for years." A security leader at a Fortune 500 company acknowledged this challenge: "We aim to rotate secrets annually, but enforcement is difficult across our environment. Some credentials have remained unchanged for years." Secrets Managers: Not a Complete Answer Even organizations using secrets management solutions remain vulnerable. A study of 2,584 repositories leveraging secrets managers revealed a 5.1% secret leakage rate —far from the near-zero we anticipate. This surpasses the overall GitHub average of 4.6%. Common issues include: Secrets extracted from secrets managers and hardcoded elsewhere
Insecure authentication to secrets managers exposing access credentials
Fragmented governance due to secrets sprawl across multiple secrets managers Secrets extracted from secrets managers and hardcoded elsewhere Insecure authentication to secrets managers exposing access credentials Fragmented governance due to secrets sprawl across multiple secrets managers The Path Forward: Comprehensive Secrets Security As AI-generated code, automation, and cloud-native development accelerate, the report forecasts that secrets sprawl will only intensify. While GitHub's Push Protection has reduced some leaks, it leaves significant gaps—particularly with generic secrets, private repositories, and collaboration tools. "For CISOs and security leaders, the goal isn't just detection—it's the remediation of these vulnerabilities before they're exploited," said Eric Fourrier. "This requires a comprehensive approach that includes automated discovery, detection, remediation, and stronger secrets governance across all enterprise platforms." "For CISOs and security leaders, the goal isn't just detection—it's the remediation of these vulnerabilities before they're exploited," said Eric Fourrier. "This requires a comprehensive approach that includes automated discovery, detection, remediation, and stronger secrets governance across all enterprise platforms." The report concludes with a strategic framework for organizations to address secrets sprawl through: Deploying monitoring for exposed credentials across all environments
Implementing centralized secrets detection and remediation
Establishing semi-automated rotation policies for all credentials
Creating clear developer guidelines for secure vault usage Deploying monitoring for exposed credentials across all environments Implementing centralized secrets detection and remediation Establishing semi-automated rotation policies for all credentials Creating clear developer guidelines for secure vault usage To read the full 2025 State of Secrets Sprawl Report, users can visit GitGuardian.com. GitGuardian.com GitGuardian.com Additional resources GitGuardian - Website GitGuardian - Website GitGuardian - Website The State of Secrets Sprawl 2025 The State of Secrets Sprawl 2025 The State of Secrets Sprawl 2025 About GitGuardian GitGuardian is an end-to-end NHI security platform that empowers software-driven organizations to enhance their Non-Human Identity (NHI) security and comply with industry standards. With attackers increasingly targeting NHIs, such as service accounts and applications, GitGuardian integrates Secrets Security and NHI Governance. GitGuardian GitGuardian This dual approach enables the detection of compromised secrets across your dev environments while also managing non-human identities and their secrets' lifecycles. The platform is the world's most installed GitHub application and supports over 450+ types of secrets, offers public monitoring for leaked data, and deploys honeytokens for added defense. Trusted by over 600,000 developers, GitGuardian is the choice of leading organizations like Snowflake, ING, BASF, and Bouygues Telecom for robust secrets protection. Contact Media Contact Holly Hagerman Connect Marketing hollyh@connectmarketing.com +1(801) 373-7888 This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

GitGuardian Report: 70% Of Leaked Secrets Remain Active For Two Years, Urging Immediate Remediation

Доклад на GitGuardian: 70% от изтеклите тайни остават активни в продължение на две години, настоявайки за незабавно отстраняване

Informe de GitGuardian: El 70 % de los secretos filtrados permanecen activos durante dos años, lo que insta a una solución inmediata.

דוח GitGuardian: 70% מהסודות שדלפו נשארים פעילים במשך שנתיים, ודוחקים לתיקון מיידי

GitGuardian jelentés: A kiszivárgott titkok 70%-a két évig aktív marad, azonnali orvoslást sürget

GitGuardian レポート: 漏洩した機密情報の 70% が 2 年間有効のまま、即時の修復が必要

GitGuardian Willakuy: 70% Pakakuna filtrado kaqmanta Iskay Watakama llamk'achkan, chaylla allichayta kallpachaspa

Raport GitGuardian: 70% dintre secretele scurse rămân active timp de doi ani, solicitând remedierea imediată

GitGuardian Chirevo: 70% Yezvakavanzika Zvakaburitswa Zvirambe Zvichishanda KweMakore Maviri, Kukurudzira Kugadziriswa Kwekare

Извештај ГитГуардиана: 70% процурелих тајни остаје активно две године, позивајући се на хитну санацију

Ripoti ya GitGuardian: Asilimia 70 ya Siri Zilizovuja Husalia Hai kwa Miaka Miwili, Ikihimiza Marekebisho ya Haraka

GitGuardian Raporu: Sızdırılan Sırların %70'i İki Yıl Aktif Kalıyor, Acil Düzeltme Çağrısı Yapılıyor

Звіт GitGuardian: 70% витоку секретів залишаються активними протягом двох років, закликаючи до негайного виправлення

I almost quit my Web3 career due to struggles and challenges but then I learnt of these secrets and now I am very successful in the space… Web 3 is very vast and you can get lost without the right background to help you get cope and get onboarded. I was unlucky to have learnt about these secrets after nearly five months in the web3 space and this affected me greatly. it slowed my progress in the space, caused me to miss out on lots of opportunities and always doing the wrong things. I struggled for five months and I almost quit my Web3 career but then I started asking questions, meeting new and valuable people in the space and through my experiences I have decided to give out these secrets to help any newbie to be easily integrated in the space and help them adapt well so they do not have the same experience I had. K-R-E-A-N-M K- stands for knowledge. There is this stereotype that you can just make money easily by engaging in projects and tasks shilled and marketed by influencers but the truth is, without knowledge you will only be a mediocre. R- stands for research. This is basically the flour on the pizza of Web3. Everything starts with research and that enriches you with the knowledge you need to navigate the space. E- stands for engagement. While researching, it is essential you engage in solid projects and fellow colleagues in the space this helps to diversify your interactions and creates connections for you. A- stands for active. This is super essential, just like every other career, this is another one of those high paying careers and you have to be active. It is not your regular visit to social media platforms, this is your job and not a fun visit, take it seriously! N- stands for Niche. Web3 is vast and embodies a lot of niche. You have to know what you want and your goal and stay focus don’t just surf around the surface and be clicking every link. Choose a niche and be one of the best in it that’s how you get to the top. M - stands for money. Everyone on this space is here to make profit(money). Nobody is here to give you handouts or help you become a millionaire overnight. Put in the work and take profit! Lastly, remember to stay LOCKED IN! I almost quit my Web3 career due to struggles and challenges but then I learnt of these secrets and now I am very successful in the space… Web 3 is very vast and you can get lost without the right background to help you get cope and get onboarded. I was unlucky to have learnt about these secrets after nearly five months in the web3 space and this affected me greatly. it slowed my progress in the space, caused me to miss out on lots of opportunities and always doing the wrong things. I struggled for five months and I almost quit my Web3 career but then I started asking questions, meeting new and valuable people in the space and through my experiences I have decided to give out these secrets to help any newbie to be easily integrated in the space and help them adapt well so they do not have the same experience I had. Web 3 is very vast and you can get lost without the right background to help you get cope and get onboarded. I was unlucky to have learnt about these secrets after nearly five months in the web3 space and this affected me greatly. it slowed my progress in the space, caused me to miss out on lots of opportunities and always doing the wrong things. I struggled for five months and I almost quit my Web3 career but then I started asking questions, meeting new and valuable people in the space and through my experiences I have decided to give out these secrets to help any newbie to be easily integrated in the space and help them adapt well so they do not have the same experience I had. K-R-E-A-N-M K-R-E-A-N-M K - stands for knowledge. There is this stereotype that you can just make money easily by engaging in projects and tasks shilled and marketed by influencers but the truth is, without knowledge you will only be a mediocre. K R - stands for research. This is basically the flour on the pizza of Web3. Everything starts with research and that enriches you with the knowledge you need to navigate the space. R E - stands for engagement. While researching, it is essential you engage in solid projects and fellow colleagues in the space this helps to diversify your interactions and creates connections for you. E A - stands for active. This is super essential, just like every other career, this is another one of those high paying careers and you have to be active. It is not your regular visit to social media platforms, this is your job and not a fun visit, take it seriously! A N - stands for Niche. Web3 is vast and embodies a lot of niche. You have to know what you want and your goal and stay focus don’t just surf around the surface and be clicking every link. Choose a niche and be one of the best in it that’s how you get to the top. N M - stands for money. Everyone on this space is here to make profit(money). Nobody is here to give you handouts or help you become a millionaire overnight. Put in the work and take profit! M Lastly, remember to stay LOCKED IN! LOCKED IN!

Next Time You're Struggling in Web3, Remember the K-R-E-A-N-M Framework

How Mamba and Hyena Are Changing the Way AI Learns and Remembers

AI That Remembers

Much faster than the dollar or the yuan, the currency of knowledge is being devalued. When it hits zero, those betting on questions will prosper. The Answer to Everything In Douglas Adams’s book The Hitchhiker’s Guide to the Galaxy, a group of hyper-intelligent beings builds a supercomputer named Deep Thought to calculate “the Answer to the Ultimate Question of Life, the Universe, and Everything”. After seven and a half million years of computing, Deep Thought finally replies: The Hitchhiker’s Guide to the Galaxy Deep Thought “The Answer to the Great Question of Life, the Universe and Everything… is… forty-two.” “The Answer to the Great Question of Life, the Universe and Everything… is… forty-two.” forty-two This did not go well with the programmers, who expressed their disappointment to the computer. “It would have been simpler had I just computed the Ultimate Question itself. But I can’t.”, replied Deep Thought.
“Can’t?” the programmers cried in astonishment.“No,” said Deep Thought. “I speak with all the authority that 7.5 million years of computation can confer. But I do not know the Question. To understand the Answer, you must understand the Question.”“So what do we do?” asked the programmers.Deep Thought replied, “I shall design for you a computer. A computer so complex that organic life itself will form part of its operational matrix. And you yourselves shall take on new forms and go down into it, to operate its system as part of its programming team. And this computer will be called…” — he paused — “the Earth.” “It would have been simpler had I just computed the Ultimate Question itself. But I can’t.”, replied Deep Thought. Question “Can’t?” the programmers cried in astonishment. “No,” said Deep Thought. “I speak with all the authority that 7.5 million years of computation can confer. But I do not know the Question. To understand the Answer, you must understand the Question.” you “So what do we do?” asked the programmers. Deep Thought replied, “I shall design for you a computer. A computer so complex that organic life itself will form part of its operational matrix. And you yourselves shall take on new forms and go down into it, to operate its system as part of its programming team. And this computer will be called…” — he paused — “the Earth.” the Earth. So, what is more important? The answer or the question? is Don’t panic. Read on. Don’t panic The Knowledge Era: Greeks, Renaissance, Modernism, Turing When Alan Turing proposed his famous Imitation Game (we now call it The Turing Test), he specifically stated “…I believe it to be too meaningless to deserve discussion” whether “machines can think”. But by then — after over 2500 years of indoctrination — being able to answer — to know like a human — has become the hallmark of intelligence. Imitation Game Plato, Aristotle, Leonardo, Galileo, Copernicus, Newton, Voltaire, Locke, Kant. “Sapere aude” — “Dare to know” — became not just a noble ideal but a moral imperative. We built our society around this ideal. We taught and measured our youth by how much they know. We invest to become experts, value and pay for their opinions, and argue about which knowledge is correct and which is not. According to this ideal, we built better tools and machines until we reached the ultimate goal. An all-knowing oracle. It will soon pass the Turing Test (if it hasn’t already), but does that mean we can lie back and let it take us to Utopia? If “knowledge is power,” do we now have the power to do anything? Far from it. if it hasn’t already Now that knowledge has become abundant, we need to acknowledge that it is completely useless by itself. We need to change our mental direction (and perception of value) from “knowing” to “asking”. Two things that have been at opposing ends of where one needs to strive. Now that knowledge has become abundant, we need to acknowledge that it is completely useless by itself. We need to change our mental direction (and perception of value) from “knowing” to “asking”. Two things that have been at opposing ends of where one needs to strive. The Subtle Art of Not Knowing Being able to ask questions is much harder than one might expect. It does come naturally to us as kids (to the extent of driving parents mad), but we are taught to value knowing, not questions, and lose or inhibit this ability. Here’s the list of things science and philosophers consider the pillars of being question-oriented. Test to see how good you are at any of them. No pressure. It is only your prosperity and that of humanity that is at stake. It is only your prosperity and that of humanity that is at stake Metacognition – Knowledge about the limits of knowledge. Being able to scan your inner self, identify gaps, and form questions that target those gaps.


Domain Knowledge – Asking meaningful questions requires prior knowledge. Familiarity with a domain helps recognize what’s missing, frame your questions with precision, and interpret responses.


Executive Function – Formulating a strong question involves holding information in mind, focusing attention, and resisting easy answers.


Theory of Mind – Effective questions are shaped by the ability to understand what others know, believe, or need.


Curiosity and Disposition – Beyond ability, question-asking depends on mindset and drive. It takes openness to uncertainty and a desire to find out.


Epistemic Humility – The willingness to admit not knowing without defensiveness. This is a big deal. It is also a cultural thing. Keep an eye out for societies that tolerate and even encourage this trait.


Question Typing – Skilled questioners know that not all questions are the same. They choose intentionally between clarifying, exploratory, hypothetical, or evaluative questions depending on context and purpose.


Conversational Intelligence and Contextual Sensitivity – These include reading the room, adapting tone, and framing the inquiry in a way that invites engagement rather than defensiveness or confusion. Since we are talking about the age of AI, this might sound absurd. But remember, we will soon work in hybrid teams, and in that context — knowing who/what and when to ask — will be crucial.


Emotional Regulation – In situations that are high-stakes, uncertain, or emotionally charged, the ability to stay composed — counts. It allows for listening, reflection, and persistence.


Imaginative Capacity – Some of the most powerful questions come not from gaps in information, but from creative insight — seeing possibilities others don’t. Metacognition – Knowledge about the limits of knowledge. Being able to scan your inner self, identify gaps, and form questions that target those gaps. Metacognition – Knowledge about the limits of knowledge. Being able to scan your inner self, identify gaps, and form questions that target those gaps. Metacognition Domain Knowledge – Asking meaningful questions requires prior knowledge. Familiarity with a domain helps recognize what’s missing, frame your questions with precision, and interpret responses. Domain Knowledge – Asking meaningful questions requires prior knowledge. Familiarity with a domain helps recognize what’s missing, frame your questions with precision, and interpret responses. Domain Knowledge Executive Function – Formulating a strong question involves holding information in mind, focusing attention, and resisting easy answers. Executive Function – Formulating a strong question involves holding information in mind, focusing attention, and resisting easy answers. Executive Function Theory of Mind – Effective questions are shaped by the ability to understand what others know, believe, or need. Theory of Mind – Effective questions are shaped by the ability to understand what others know, believe, or need. Theory of Mind Curiosity and Disposition – Beyond ability, question-asking depends on mindset and drive. It takes openness to uncertainty and a desire to find out. Curiosity and Disposition – Beyond ability, question-asking depends on mindset and drive. It takes openness to uncertainty and a desire to find out. Curiosity and Disposition Epistemic Humility – The willingness to admit not knowing without defensiveness. This is a big deal. It is also a cultural thing. Keep an eye out for societies that tolerate and even encourage this trait. Epistemic Humility – The willingness to admit not knowing without defensiveness. This is a big deal. It is also a cultural thing. Keep an eye out for societies that tolerate and even encourage this trait. Epistemic Humility Question Typing – Skilled questioners know that not all questions are the same. They choose intentionally between clarifying, exploratory, hypothetical, or evaluative questions depending on context and purpose. Question Typing – Skilled questioners know that not all questions are the same. They choose intentionally between clarifying, exploratory, hypothetical, or evaluative questions depending on context and purpose. Question Typing Conversational Intelligence and Contextual Sensitivity – These include reading the room, adapting tone, and framing the inquiry in a way that invites engagement rather than defensiveness or confusion. Since we are talking about the age of AI, this might sound absurd. But remember, we will soon work in hybrid teams, and in that context — knowing who/what and when to ask — will be crucial. Conversational Intelligence and Contextual Sensitivity – These include reading the room, adapting tone, and framing the inquiry in a way that invites engagement rather than defensiveness or confusion. Since we are talking about the age of AI, this might sound absurd. But remember, we will soon work in hybrid teams, and in that context — knowing who/what and when to ask — will be crucial. Conversational Intelligence Contextual Sensitivity Emotional Regulation – In situations that are high-stakes, uncertain, or emotionally charged, the ability to stay composed — counts. It allows for listening, reflection, and persistence. Emotional Regulation – In situations that are high-stakes, uncertain, or emotionally charged, the ability to stay composed — counts. It allows for listening, reflection, and persistence. Emotional Regulation Imaginative Capacity – Some of the most powerful questions come not from gaps in information, but from creative insight — seeing possibilities others don’t. Imaginative Capacity – Some of the most powerful questions come not from gaps in information, but from creative insight — seeing possibilities others don’t. Imaginative Capacity Difficult terms — more difficult to implement. Feel the tension of saying “I do not know” to any of the following “knowledge” provoking statements: “Are the Trump Tariffs a good or bad idea?” “Are the Trump Tariffs a good or bad idea?” “Rushing your kids to bed on a school night is the right thing to do?” “Rushing your kids to bed on a school night is the right thing to do?” “Should you take a loan to invest in the stock exchange?” “Should you take a loan to invest in the stock exchange?” “Are fluoride toothpastes good for you?” “Are fluoride toothpastes good for you?” “Should you quit your job and start a business?” “Should you quit your job and start a business?” “Are GMOs a thing we should ban or encourage?” “Are GMOs a thing we should ban or encourage?” “Should the marketing department you lead change its focus?” “Should the marketing department you lead change its focus?” The Knowledge Paradox What’s more, we’ve hit a paradox. To be effective at questioning — one needs to know. But to know is not to question. Down goes the rabbit hole. The solution lies — I’m treading softly on speculative ground here — at implicit vs explicit knowledge. We discussed it briefly in a previous post. Fact recollection, calculations, and even strong theory replication will not be required. Intuitive understanding, inter- and cross-domain inference, and the ability to move from implicit to explicit and fuzzy-explicit (the machine will fill the blanks) will be the winner. previous post How to train for that kind of thinking? I predict that by encouraging what is already natural for our brain. Not fact recollection and preciseness, but broad associations and non-linear and stacked pattern recognition. But honestly, I do not know. It is an open question. An Economic Incentive. With an Asterisk Remember the “It is only your prosperity and that of humanity that is at stake” statement from above? It was no joke. In every era, when there is an increase in the productivity gained from capital (i.e., technological progress) — the labor (people’s work) associated with that increase — also grows in value (when the labor is contributing. Not replaced). It is only your prosperity and that of humanity that is at stake contributing replaced And vice versa. If labor does not contribute to the yield increase — or is replaced — the result is growing social inequality, which usually ends badly. (Read this book for details — it’s amazing.) Two groups will “run off” — the one with capital (through the increased returns) and the one contributing to the capital yield — surfing their growing salaries away from the rest (for a rather recent study on the subject see here, though what is claimed there about college education is becoming obsolete very fast). this book here The most valued labor will shift — from experts with answers to doubters with better questions. These are the people we need to train through the education system, and these are the people we need to become. There is just one little dark asterisk to add here. AI Agents. It is easy to imagine how they do the “replacing” trick in the above capital-techno-yield scheme. There is no need for an inquisitive human if the machine can do both the questioning and the answering. True, but the machine needs to have motivation in order to question. Even setting goals and letting the Agent reach them autonomously requires motivation. And we are still very far from a motivated Siri. No motivation — no unemployment. If we become humble enough to stop knowing. The Cognitive Shift To finish with a bit of optimism, here’s my take on how we are going to trust knowledge in the near future. We are not. No facts given on any medium by any person will have any weight. The good news is there’s no fake news. Not because we can’t trust anything due to deepfakes, but because of the first law of economics. For something to have value — it needs to be scarce. When knowledge requires no effort to retrieve — it loses its value. Value will be in the motivations that produce the best results. Which motivations are these, and what results should they aim for? Easy. 42.

Not Knowing: The Secret, Coveted Art 

Facing the AIpocalypse With Eyes Open, and a Plan to Win Facing the AIpocalypse With Eyes Open, and a Plan to Win It’s a divisive issue. Every time I write about AI affecting engineers’ livelihoods, jobs, or AI business automation, I get two much-repeated responses: “Don’t be stupid, AI will never.” One guy even told me, ‘Your intelligence is artificial!’
“Yeah, bro, it’s wild. It’s a lot to deal with.” “Don’t be stupid, AI will never.” One guy even told me, ‘Your intelligence is artificial!’ “Yeah, bro, it’s wild. It’s a lot to deal with.” I’m not here to worry you. I prefer optimism, but let’s be real, change is here. It’s already hitting, and those who stay open-minded and aware will adapt and thrive through this massive transition. I’m keeping my eyes open and aiming to evolve with AI. Burying your head in the sand like an ostrich and convincing yourself this isn’t happening is not a strategy. is not a strategy Prepping FTW. So, what’s my advice for software people amidst the biggest upheaval we’ve ever seen? Learn AI—No Matter Where You Sit Junior dev? Learn AI.
Senior engineer? Learn AI.
Software product lead, team lead, CTO? Learn AI. Junior dev? Learn AI. Senior engineer? Learn AI. Software product lead, team lead, CTO? Learn AI. This is tech, which we love anyway. Being late to react to this shift is going to hurt. How to Learn AI as a Dev The more I share my AI automation experiments, the more I see this as one of the wildest times of opportunity ever. Here’s the truth: many, many software folks are ignoring AI. Lots of us are revelling in it and just trying stuff out, but we’re still the minority. One thing is for sure: you’re going to need more than an hour or two with ChatGPT. Learn the Landscape AI is more than just ChatGPT. It’s LLMs, agents, workflows, memory, and many divergent approaches to modelling. It may be fundamentally a lookup tool, but almost every day, a new team is leveraging it to do something new. My advice: My advice: Read Hacker News, HackerNoon, X, and ProfitSwarm.ai Read Hacker News, HackerNoon, X, and ProfitSwarm.ai Learn to Think in AI Prompt engineering is a mindset. If you’re good at writing PRDs or sales copy, you already have an advantage. The quality of your AI outputs depends entirely on the quality of your input (prompts). My advice: My advice: Get used to calling AI APIs with diverse, dynamic prompts
Play with AI image gen tools
Practice framing outputs in concrete ways
Learn model quirks & master system prompts
Learn automation tooling (Gumloop, Lindy, n8n, etc.) Get used to calling AI APIs with diverse, dynamic prompts Play with AI image gen tools Practice framing outputs in concrete ways Learn model quirks & master system prompts Learn automation tooling (Gumloop, Lindy, n8n, etc.) Gumloop Gumloop Vibe Shift My last two posts on HackerNoon blew up. Vibe coding exploded, then became an interesting niche drama in AI the past month. …But I think those dramatic takes often miss the point. Vibe coding is legit for good developers. Vibe coding is legit for good developers. For others, it’s still fun and great for prototyping. But don’t expect it to produce production-ready, secure, scalable code yet. For those engineers who embrace vibe coding, it’s a multiplier. So, as of April 2025, Vibe Coding Smart is: Non-technical folks: Use AI to prototype and learn. Just don’t assume it outputs production-ready code
Junior devs: Use it to learn and speed up your logic writing, but check, check, check
Senior engineers/full-stack devs: AI is excellent at:

Quick prototyping
Fast (if bland) UI work
Writing boilerplate code (e.g., CRUD / DAL basics) Non-technical folks: Use AI to prototype and learn. Just don’t assume it outputs production-ready code Junior devs: Use it to learn and speed up your logic writing, but check, check, check Senior engineers/full-stack devs: AI is excellent at:

Quick prototyping
Fast (if bland) UI work
Writing boilerplate code (e.g., CRUD / DAL basics) Quick prototyping
Fast (if bland) UI work
Writing boilerplate code (e.g., CRUD / DAL basics) Quick prototyping Fast (if bland) UI work Writing boilerplate code (e.g., CRUD / DAL basics) But to my mind, AI still needs guidance on: still needs guidance Security
Authentication
Formatting
Nomenclature
Framework dependencies Security Authentication Formatting Nomenclature Framework dependencies By being good engineers and feeding it PRDs, robust specs, and napkin layouts, then hardening the code, we can achieve pretty amazing results. Employed as a Software Engineer? Lead AI in your organization. It’s awesome being an engineer; it can be a rewarding craft. But honestly, you should be leading AI adoption in your org, or at least be part of the transition. If not, you risk being left behind by 2026. Propose a project for yourself to test out tools and feed back to your company
Write internal updates on what’s working in AI
Be aware of market-affecting AI changes
Be forward-thinking about automation
Always remember to be human; people need their jobs, and change often creates anxiety. This may come up as escalation/conflict; tread carefully Propose a project for yourself to test out tools and feed back to your company Propose a project Write internal updates on what’s working in AI Write internal updates Be aware of market-affecting AI changes Be aware Be forward-thinking about automation automation Always remember to be human; people need their jobs, and change often creates anxiety. This may come up as escalation/conflict; tread carefully Always remember to be human (Note: Certain industries and regulated software might be harder to adopt AI in; think healthcare, finance, etc. But don’t let it block you totally, think of ways AI can be applied without antagonising people or effacing regulatory restrictions.) Note: Decide Your Line, Exit Strategies & CRAFT AI is revolutionizing our profession. To what extent humans will engineer software in the future is unclear. Have an honest talk with yourself ahead of time. If your job pivots to managing AI employees, do you still want to do it?


Is software engineering your craft? Do you want to compete in a market rife with AI clone factories?


Will you enjoy a day-to-day work life with far fewer humans in it? If your job pivots to managing AI employees, do you still want to do it? If your job pivots to managing AI employees, do you still want to do it? Is software engineering your craft? Do you want to compete in a market rife with AI clone factories? Is software engineering your craft? Do you want to compete in a market rife with AI clone factories? Will you enjoy a day-to-day work life with far fewer humans in it? Will you enjoy a day-to-day work life with far fewer humans in it? We all have a line. A range of environmental variables that are nourishing, or even just acceptable. There may be opportunities to pivot, retrain, accept, or reject AI as part of our workflows. Define your line before you are made to cross it. Strategy Examples: Strategy Examples: Some software entrepreneurs might thrive by always retaining the human dev craft
Others might get great at automating and be happy wrangling bots
Perhaps you could pivot to consulting or a totally different career Some software entrepreneurs might thrive by always retaining the human dev craft Others might get great at automating and be happy wrangling bots Perhaps you could pivot to consulting or a totally different career (Please don’t take this as life advice. I just want to get you thinking!) Pivoting to IRL One pull I feel (and believe will be massive by 2026) is the pivot of knowledge workers into IRL businesses. Maybe you’ve always wanted to: Captain a boat
Make giant sculptures
Run a smallholding
Make bespoke furniture Captain a boat Make giant sculptures Run a smallholding Make bespoke furniture ..or maybe that’s just me 😅. Software and logic are comfy, but IRL ‘work’ may be healthier, present new challenges, and represent a ripe opportunity. Tech might squeeze the joy out of hand-crafting apps. It will likely make copycats 1,000 times more prolific, making it a race to the bottom. In my opinion, there’s a lot of upside for many of us in the IRL business over the next few years. Certainly, I’m going to hedge my digital businesses with some analog ventures. My AIpocalypse Prep I’m generally optimistic. I believe AI will create good outcomes for many of us. But I love this quote: “Invert, always invert.” - algebraist Carl Jacobi, via Charlie Munger “Invert, always invert.” - algebraist Carl Jacobi, via Charlie Munger I always try to see the alchemical opportunity in everything I do. The flip side. AI has huge potential for mass career changes, but also great opportunities for us as craft system makers. What I’m Doing to Evolve With AI: Leaning into AI hard (doing a challenge to make a 100% AI business this year - ProfitSwarm.ai)
Making learning to use AI a core part of my life
I experiment constantly, while trying to stay grounded in my values and humanity. (AI is super experimental right now)
Balancing digital living with IRL living
Hedging by looking for local biz opportunities Leaning into AI hard (doing a challenge to make a 100% AI business this year - ProfitSwarm.ai) Making learning to use AI a core part of my life I experiment constantly, while trying to stay grounded in my values and humanity. (AI is super experimental right now) Balancing digital living with IRL living Hedging by looking for local biz opportunities AI could be a philosopher’s stone or a management consultant’s axe. You decide. Let’s See Where AI Takes Us If you want to follow along with my AI business automation experiments, you can subscribe at ProfitSwarm.ai. ProfitSwarm.ai I’m going to make AI my philosopher's stone, or explode fantastically. Let’s see where it takes us.

Escape the AIpocalypse: Essential Strategies for Developers

Избягване на AIpocalypse: Основни стратегии за разработчиците

Escapar del AIpocalypse: estrategias esenciales para los desarrolladores

Escape the AIpocalypse: estratexias esenciais para desenvolvedores

הימנעות מ-AIpocalypse: אסטרטגיות חיוניות למפתחים

Pobjeći AIpocalypse: bitne strategije za programere

Escape the AIpocalypse: Essential Strategies for Developers(AIポカリプスの脱出:開発者にとって不可欠な戦略)

도망 AIpocalypse : 개발자를위한 필수 전략

यो बर्ष महानगरको अभियान — सम्पदा संरक्षण तथा सम्बर्धन, पर्यटन प्रवर्धनका लागि पूर्वाधार Next Post

Escape the AIpocalypse: Základné stratégie pre vývojárov

Escape the AIpocalypse: Developers க்கு தேவையான அம்சங்கள்

Escape the AIpocalypse: กลยุทธ์ที่จําเป็นสําหรับนักพัฒนา

AIpocalypse: Developer's Essential strategiyalar

San Francisco, United States, April 29th, 2025/CyberNewsWire/--SecAI, an AI-enriched threat intelligence company, made its official debut today at RSA Conference 2025 in San Francisco, marking the company’s first public appearance on the global cybersecurity stage. At the event, the SecAI team is showcasing the latest version of its platform to security professionals from around the world. San Francisco, United States, April 29th, 2025/CyberNewsWire/--SecAI, The updated SecAI Investigator platform is purpose-built to solve one of cybersecurity’s most stubborn challenges: efficient threat investigation. It tackles this by combining two key innovations. First, it delivers curated, high-fidelity threat intelligence, which includes clear verdicts, multi-dimensional labels, and rich context like historical attack behavior through a unified interface. Second, it’s designed from the ground up with an AI-native architecture. The platform leverages advanced AI techniques not only for natural language interaction, but for deep information integration, contextual security reasoning, and suggest remediation options. SecAI Booth At RSA Conference 2025, N-6570 “We believe the future of cybersecurity lies in intelligent systems that can think and adapt like seasoned analysts,” said Chase Lee, Managing Director at SecAI. “We believe the future of cybersecurity lies in intelligent systems that can think and adapt like seasoned analysts,” said Chase Lee, Managing Director at SecAI. “Threat investigation has remained one of the most human-intensive parts of the SOC, but it doesn't have to be. By combining deep threat intelligence with agentic AI, we’re not just accelerating investigations—we’re reshaping what’s possible in cyber defense. This is about giving security teams superhuman capabilities to meet the scale and speed of modern threats.” “Threat investigation has remained one of the most human-intensive parts of the SOC, but it doesn't have to be. By combining deep threat intelligence with agentic AI, we’re not just accelerating investigations—we’re reshaping what’s possible in cyber defense. This is about giving security teams superhuman capabilities to meet the scale and speed of modern threats.” In the security operations lifecycle—typically divided into detection, investigation, and response—automation has advanced detection and response dramatically over the past decade. But investigation remains a critical bottlenecks, often consuming over 70% of analysts’ time. SecAI believes that effective investigation depends on two essential capabilities: accurately gathering and organizing relevant information, and making sound, timely judgments. The main blockers today are: A lack of timely, comprehensive threat intelligence
Ineffective methods for connecting data points to practical workflows A lack of timely, comprehensive threat intelligence Ineffective methods for connecting data points to practical workflows SecAI Investigator addresses both. By streamlining the investigation process, the platform enables analysts to rapidly evaluate the nature and relevance of IPs, domains, and threat actors, dive deep into logs and alerts, and make faster, more confident decisions. Looking ahead, SecAI plans to roll out API and threat intelligence feed integrations, allowing customers to embed SecAI’s contextual threat intelligence directly into their existing systems and workflows. This will enable real-time enrichment, faster responses, and more scalable intelligence-driven operations across teams. Users can visit SecAI Investigator to explore the platform or connect with the SecAI team at RSA Conference 2025 at Booth 6570 for live demos and early access. SecAI Investigator SecAI Investigator About SecAI SecAI is an AI-native cybersecurity company specializing in threat detection, investigation, and response. By deeply analyzing adversary tactics, techniques, and procedures (TTPs) and fusing advanced generative AI with rich, contextual threat intelligence, SecAI delivers smarter, faster, and more effective solutions for modern security teams. SecAI SecAI The team's mission is to transform cybersecurity operations by empowering analysts with intelligent systems that scale expertise and accelerate decision-making. Contact PR Manager Nicholas Tan SecAI nicholas@secai.ai This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

SecAI Debuts At RSA 2025, Redefining Threat Investigation With AI

SecAI RSA 2025-এ ডেবিট, AI-এর মাধ্যমে হুমকি তদন্ত পুনর্নির্ধারণ

SecAI debitira na RSA 2025, redefinirajući istragu o prijetnjama pomoću AI-a

SecAI debuta en RSA 2025, redefiniendo la investigación de amenazas con IA

SecAI- ը RSA 2025- ում debuts, վերլուծելով սխալների հետազոտությունը AI- ի հետ

SecAI、RSA 2025でデビュー、AIで脅威調査を再定義

SecAI는 RSA 2025에서 AI로 위협 조사를 재정의합니다.

SecAI debitē RSA 2025, pārdefinējot apdraudējumu izmeklēšanu ar AI

SecAI RSA 2025-д анхдагч байна, AI-ийг ашиглан хязгаарлалт судалгааг шинэчлэх

SecAI debutează la RSA 2025, redefinind cercetarea amenințărilor cu AI

SecAI Debut sa RSA 2025, Redefining Threat Investigation sa pamamagitan ng AI

SecAI, RSA 2025, AI-ga qorxud bilan qaytaradi

SecAI在RSA 2025上首次亮相,用AI重新定义威胁调查

Dear ChatGPT, I'm Alone and Depressed—Can You Help?

প্রিয় ChatGPT, আমি একা এবং বিষণ্ন - আপনি কি সাহায্য করতে পারেন?

Estimat ChatGPT, estic sol i deprimit - Pots ajudar?

Querido ChatGPT, estoy solo y deprimido - ¿Puedes ayudar?

Cher ChatGPT, Je suis seul et déprimé – Pouvez-vous m’aider ?

Querido ChatGPT, estou só e deprimido - Podes axudar?

Dear ChatGPT, I'm Alone and Depressed - Can You Help? あなたは私を助けることができますか?

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