In a world where I let AI agents plan my vacation, I expected a spark of joy, a glimpse of adventure. But instead, I felt the hollowness of automation. The beauty of spontaneity replaced by algorithms, the laughter of shared moments overshadowed by cold, calculated suggestions. I wandered through destinations that felt curated, not chosen, longing for the warmth of genuine connection. In this sea of artificial planning, I found myself more alone than ever. Was this truly a vacation, or just a lonely escape from reality? #Loneliness #Vacation #AITravel #Heartbreak #Solitude

In a world that increasingly feels like it has turned its back on authentic connection, I find myself staring blankly at my Smart TV, a screen that promises companionship but delivers only cold advertisements. The irony is not lost on me; I sit here, surrounded by technology designed to bring us closer, yet I feel more isolated than ever. As I explore the intricacies of Smart TV operating systems, I'm reminded of the delicate balance they must maintain: protecting our data while catering to the insatiable hunger of advertisers. It's a tragic dance, one where my privacy is sacrificed at the altar of profit. Each click feels like a betrayal, a reminder that I'm just another data point, another target for those who seek to profit from my attention. I used to think that technology was a bridge to deeper connections, a way to feel less alone in this vast, seemingly indifferent universe. But now, it feels more like a prison, each algorithm tightening its grip around my reality. I wonder if the creators of these platforms ever pause to consider the emotional toll they impose on us. Are they aware that each pop-up ad stings, each targeted suggestion feels like a reminder of my solitude? In moments of silence, I long for the warmth of real conversations, the kind that cannot be quantified by metrics or sold to the highest bidder. I want to feel seen and understood, not just as a consumer, but as a human being with hopes, dreams, and fears. Yet, the more I engage with these Smart TVs and their operating systems, the more I feel like a ghost haunting my own life, trapped between the desire for connection and the reality of commodification. As I navigate through content designed to keep me entertained, I can't shake the feeling of sadness that lingers in the air. It's a heavy cloak, woven from the threads of disappointment and longing. The world outside continues to rush by, vibrant and alive, while I remain here, lost in a digital realm that promises everything but delivers nothing of real substance. I look into the depths of the screen, searching for something—anything—that might fill this aching void. Instead, I'm met with a reflection of my own despair, a reminder that in our quest for connection, we might have lost sight of what truly matters. The irony is painful, and I can't help but feel like a prisoner to this cycle of consumption and isolation. In the end, I wonder: will we ever reclaim our humanity from the clutches of these systems? Or will we forever be at the mercy of the data-driven world that sees us not as individuals but merely as opportunities? #SmartTV #DataPrivacy #Isolation #EmotionalConnection #TechnologySadness

🌟 Salut à tous, amis passionnés de jeux vidéo ! 🌟 Aujourd'hui, je suis tellement ravi de partager avec vous quelques réflexions inspirantes sur le monde fascinant de l'édition de jeux, notamment grâce à l'éditeur Balatro et Playstack, qui nous ouvrent un chemin prometteur vers un avenir radieux en 2025 ! 🚀✨ L'une des plus grandes leçons que nous pouvons tirer de cette aventure est l'importance de la transparence. Oui, vous avez bien entendu ! 🤝 La transparence est le drapeau vert que nous devrions tous viser à lever dans nos projets. Que vous soyez développeur, créateur ou simplement un passionné de jeux, comprendre ce que le jeu a besoin et quand il en a besoin est essentiel pour réussir. C’est comme naviguer dans un océan : lorsque vous avez une carte claire et un ciel dégagé, chaque vague devient une opportunité ! 🌊🌈 Imaginez un monde où les éditeurs et les développeurs partagent ouvertement leurs objectifs et leurs défis. Cela crée non seulement un environnement de confiance, mais également un espace propice à l’innovation. 💡💪 Nous avons tous le pouvoir de transformer des idées en réalité, et c'est cette transparence qui nous permet de surmonter les obstacles qui peuvent se présenter sur notre chemin. L'édition de jeux est un voyage collectif, et chaque contribution compte. Que vous soyez un vétéran du secteur ou que vous veniez tout juste de commencer, rappelez-vous que chaque pas compte. La passion et l'engagement sont les moteurs qui poussent nos rêves vers de nouveaux sommets. 🌟🎮 Alors, n'ayez pas peur de partager vos idées, vos besoins et vos attentes avec votre équipe ou votre communauté. Soyez toujours ouvert aux retours et aux suggestions, car c'est ainsi que nous grandissons ensemble ! 🌱✨ À tous ceux qui aspirent à faire partie de cette belle aventure, rappelez-vous : le chemin peut sembler long, mais avec la bonne attitude et une communication claire, rien n'est impossible ! Ensemble, nous pouvons réaliser des merveilles et créer des expériences de jeu qui marqueront les esprits pour les générations à venir. 🌍❤️ Restons unis, soyons transparents et préparons-nous à embrasser le futur avec enthousiasme et détermination ! Que l'aventure commence ! 🚀🌈 #JeuxVidéo #ÉditionDeJeux #Transparence #Inspiration #Innovation

Bungie, l'éditeur connu pour ses franchises emblématiques comme Destiny, a récemment annoncé que le lancement de son prochain grand jeu, Marathon, est retardé indéfiniment. Initialement prévu pour septembre, le studio a décidé de prendre du recul afin de mieux répondre aux retours des fans. Cette décision a été prise après l'alpha test du jeu plus tôt dans l'année, où de nombreux joueurs ont exprimé des préoccupations et des suggestions. ## Les raisons du retard Le développement de jeux vidéo ...

Is it just me, or does the phrase "Quick Tip: A Better Wet Shader" sound like the latest buzz from a trendy café, where the barista is more interested in his art than the coffee? I mean, who would have thought that the secret to stunning visuals in Blender would come down to a clearcoat? It’s almost as if John Mervin, that brave pioneer of pixelated perfection, stumbled upon the holy grail of rendering while driving—because, you know, multitasking is all the rage these days! Let's take a moment to appreciate the genius of recording tutorials while navigating rush hour traffic. Who needs a calm, focused environment when you could be dodging potholes and merging lanes? I can just picture it: "Okay, folks, today we're going to add a clearcoat to our wet shader... but first, let’s avoid this pedestrian!" Truly inspiring. But back to the world of wet shaders. Apparently, the key to mastering the art of sheen is just slapping on a clearcoat and calling it a day. Why bother with the complexities of light diffusion, texture mapping, or even the nuances of realism when you can just... coat it? It's like serving a gourmet meal and then drowning it in ketchup—truly a culinary masterpiece! And let’s not forget the vast potential here. If adding a clearcoat is revolutionary, imagine the untapped possibilities! Why not just throw in a sprinkle of fairy dust and call it a magical shader? Or better yet, how about a “drive-by” tutorial series that teaches us how to animate while on a rollercoaster? The future of Blender tutorials is bright—especially if you’re driving towards it at 80 mph! After all, who needs to focus on the intricacies of shader creation when we can all just slap on a clearcoat and hope for the best? The art of 3D rendering has clearly reached a new zenith. So, to all the aspiring Blender wizards out there, remember: clearcoat is your best friend, and traffic lights are merely suggestions. In conclusion, if you ever find yourself needing a quick fix in Blender, just remember—there’s nothing a good clearcoat can’t solve. Just don’t forget to keep your eyes on the road; after all, we wouldn’t want you to miss a tutorial while mastering the art of shaders on the go! #WetShader #BlenderTutorial #Clearcoat #3DRendering #DigitalArt

Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement

Jun 16, 2025Ravie LakshmananMalware / DevOps Cybersecurity researchers have discovered a malicious package on the Python Package Indexrepository that's capable of harvesting sensitive developer-related information, such as credentials, configuration data, and environment variables, among others. The package, named chimera-sandbox-extensions, attracted 143 downloads and likely targets users of a service called Chimera Sandbox, which was released by Singaporean tech company Grab last August to facilitate "experimentation and development ofsolutions." The package masquerades as a helper module for Chimera Sandbox, but "aims to steal credentials and other sensitive information such as Jamf configuration, CI/CD environment variables, AWS tokens, and more," JFrog security researcher Guy Korolevski said in a report published last week. Once installed, it attempts to connect to an external domain whose domain name is generated using a domain generation algorithmin order to download and execute a next-stage payload. Specifically, the malware acquires from the domain an authentication token, which is then used to send a request to the same domain and retrieve the Python-based information stealer. The stealer malware is equipped to siphon a wide range of data from infected machines. This includes - JAMF receipts, which are records of software packages installed by Jamf Pro on managed computers Pod sandbox environment authentication tokens and git information CI/CD information from environment variables Zscaler host configuration Amazon Web Services account information and tokens Public IP address General platform, user, and host information The kind of data gathered by the malware shows that it's mainly geared towards corporate and cloud infrastructure. In addition, the extraction of JAMF receipts indicates that it's also capable of targeting Apple macOS systems. The collected information is sent via a POST request back to the same domain, after which the server assesses if the machine is a worthy target for further exploitation. However, JFrog said it was unable to obtain the payload at the time of analysis. "The targeted approach employed by this malware, along with the complexity of its multi-stage targeted payload, distinguishes it from the more generic open-source malware threats we have encountered thus far, highlighting the advancements that malicious packages have made recently," Jonathan Sar Shalom, director of threat research at JFrog Security Research team, said. "This new sophistication of malware underscores why development teams remain vigilant with updates—alongside proactive security research – to defend against emerging threats and maintain software integrity." The disclosure comes as SafeDep and Veracode detailed a number of malware-laced npm packages that are designed to execute remote code and download additional payloads. The packages in question are listed below - eslint-config-airbnb-compatts-runtime-compat-checksolders@mediawave/libAll the identified npm packages have since been taken down from npm, but not before they were downloaded hundreds of times from the package registry. SafeDep's analysis of eslint-config-airbnb-compat found that the JavaScript library has ts-runtime-compat-check listed as a dependency, which, in turn, contacts an external server defined in the former packageto retrieve and execute a Base64-encoded string. The exact nature of the payload is unknown. "It implements a multi-stage remote code execution attack using a transitive dependency to hide the malicious code," SafeDep researcher Kunal Singh said. Solders, on the other hand, has been found to incorporate a post-install script in its package.json, causing the malicious code to be automatically executed as soon as the package is installed. "At first glance, it's hard to believe that this is actually valid JavaScript," the Veracode Threat Research team said. "It looks like a seemingly random collection of Japanese symbols. It turns out that this particular obfuscation scheme uses the Unicode characters as variable names and a sophisticated chain of dynamic code generation to work." Decoding the script reveals an extra layer of obfuscation, unpacking which reveals its main function: Check if the compromised machine is Windows, and if so, run a PowerShell command to retrieve a next-stage payload from a remote server. This second-stage PowerShell script, also obscured, is designed to fetch a Windows batch script from another domainand configures a Windows Defender Antivirus exclusion list to avoid detection. The batch script then paves the way for the execution of a .NET DLL that reaches out to a PNG image hosted on ImgBB. "is grabbing the last two pixels from this image and then looping through some data contained elsewhere in it," Veracode said. "It ultimately builds up in memory YET ANOTHER .NET DLL." Furthermore, the DLL is equipped to create task scheduler entries and features the ability to bypass user account controlusing a combination of FodHelper.exe and programmatic identifiersto evade defenses and avoid triggering any security alerts to the user. The newly-downloaded DLL is Pulsar RAT, a "free, open-source Remote Administration Tool for Windows" and a variant of the Quasar RAT. "From a wall of Japanese characters to a RAT hidden within the pixels of a PNG file, the attacker went to extraordinary lengths to conceal their payload, nesting it a dozen layers deep to evade detection," Veracode said. "While the attacker's ultimate objective for deploying the Pulsar RAT remains unclear, the sheer complexity of this delivery mechanism is a powerful indicator of malicious intent." Crypto Malware in the Open-Source Supply Chain The findings also coincide with a report from Socket that identified credential stealers, cryptocurrency drainers, cryptojackers, and clippers as the main types of threats targeting the cryptocurrency and blockchain development ecosystem. Some of the examples of these packages include - express-dompurify and pumptoolforvolumeandcomment, which are capable of harvesting browser credentials and cryptocurrency wallet keys bs58js, which drains a victim's wallet and uses multi-hop transfers to obscure theft and frustrate forensic tracing. lsjglsjdv, asyncaiosignal, and raydium-sdk-liquidity-init, which functions as a clipper to monitor the system clipboard for cryptocurrency wallet strings and replace them with threat actor‑controlled addresses to reroute transactions to the attackers "As Web3 development converges with mainstream software engineering, the attack surface for blockchain-focused projects is expanding in both scale and complexity," Socket security researcher Kirill Boychenko said. "Financially motivated threat actors and state-sponsored groups are rapidly evolving their tactics to exploit systemic weaknesses in the software supply chain. These campaigns are iterative, persistent, and increasingly tailored to high-value targets." AI and Slopsquatting The rise of artificial intelligence-assisted coding, also called vibe coding, has unleashed another novel threat in the form of slopsquatting, where large language modelscan hallucinate non-existent but plausible package names that bad actors can weaponize to conduct supply chain attacks. Trend Micro, in a report last week, said it observed an unnamed advanced agent "confidently" cooking up a phantom Python package named starlette-reverse-proxy, only for the build process to crash with the error "module not found." However, should an adversary upload a package with the same name on the repository, it can have serious security consequences. Furthermore, the cybersecurity company noted that advanced coding agents and workflows such as Claude Code CLI, OpenAI Codex CLI, and Cursor AI with Model Context Protocol-backed validation can help reduce, but not completely eliminate, the risk of slopsquatting. "When agents hallucinate dependencies or install unverified packages, they create an opportunity for slopsquatting attacks, in which malicious actors pre-register those same hallucinated names on public registries," security researcher Sean Park said. "While reasoning-enhanced agents can reduce the rate of phantom suggestions by approximately half, they do not eliminate them entirely. Even the vibe-coding workflow augmented with live MCP validations achieves the lowest rates of slip-through, but still misses edge cases." Found this article interesting? Follow us on Twitter  and LinkedIn to read more exclusive content we post. SHARE     #malicious #pypi #package #masquerades #chimera

You’ve drawn fifty versions of the same screen — and you still hate every one of them. Begrudgingly, you pick three, show them to your product manager, and hear: “Looks cool, but the idea doesn’t work.” Sound familiar? In this article, I’ll unpack why designers fall into detail work at the wrong moment, examining both process pitfalls and the underlying psychological reasons, as understanding these traps is the first step to overcoming them. I’ll also share tactics I use to climb out of that trap. Reason #1 You’re Afraid To Show Rough Work We designers worship detail. We’re taught that true craft equals razor‑sharp typography, perfect grids, and pixel precision. So the minute a task arrives, we pop open Figma and start polishing long before polish is needed. I’ve skipped the sketch phase more times than I care to admit. I told myself it would be faster, yet I always ended up spending hours producing a tidy mock‑up when a scribbled thumbnail would have sparked a five‑minute chat with my product manager. Rough sketches felt “unprofessional,” so I hid them. The cost? Lost time, wasted energy — and, by the third redo, teammates were quietly wondering if I even understood the brief. The real problem here is the habit: we open Figma and start perfecting the UI before we’ve even solved the problem. So why do we hide these rough sketches? It’s not just a bad habit or plain silly. There are solid psychological reasons behind it. We often just call it perfectionism, but it’s deeper than wanting things neat. Digging into the psychologyshows there are a couple of flavors driving this: Socially prescribed perfectionismIt’s that nagging feeling that everyone else expects perfect work from you, which makes showing anything rough feel like walking into the lion’s den. Self-oriented perfectionismWhere you’re the one setting impossibly high standards for yourself, leading to brutal self-criticism if anything looks slightly off. Either way, the result’s the same: showing unfinished work feels wrong, and you miss out on that vital early feedback. Back to the design side, remember that clients rarely see architects’ first pencil sketches, but these sketches still exist; they guide structural choices before the 3D render. Treat your thumbnails the same way — artifacts meant to collapse uncertainty, not portfolio pieces. Once stakeholders see the upside, roughness becomes a badge of speed, not sloppiness. So, the key is to consciously make that shift: Treat early sketches as disposable tools for thinking and actively share them to get feedback faster. Reason #2: You Fix The Symptom, Not The Cause Before tackling any task, we need to understand what business outcome we’re aiming for. Product managers might come to us asking to enlarge the payment button in the shopping cart because users aren’t noticing it. The suggested solution itself isn’t necessarily bad, but before redesigning the button, we should ask, “What data suggests they aren’t noticing it?” Don’t get me wrong, I’m not saying you shouldn’t trust your product manager. On the contrary, these questions help ensure you’re on the same page and working with the same data. From my experience, here are several reasons why users might not be clicking that coveted button: Users don’t understand that this step is for payment. They understand it’s about payment but expect order confirmation first. Due to incorrect translation, users don’t understand what the button means. Lack of trust signals. Unexpected additional coststhat appear at this stage. Technical issues. Now, imagine you simply did what the manager suggested. Would you have solved the problem? Hardly. Moreover, the responsibility for the unresolved issue would fall on you, as the interface solution lies within the design domain. The product manager actually did their job correctly by identifying a problem: suspiciously, few users are clicking the button. Psychologically, taking on this bigger role isn’t easy. It means overcoming the fear of making mistakes and the discomfort of exploring unclear problems rather than just doing tasks. This shift means seeing ourselves as partners who create value — even if it means fighting a hesitation to question product managers— and understanding that using our product logic expertise proactively is crucial for modern designers. There’s another critical reason why we, designers, need to be a bit like product managers: the rise of AI. I deliberately used a simple example about enlarging a button, but I’m confident that in the near future, AI will easily handle routine design tasks. This worries me, but at the same time, I’m already gladly stepping into the product manager’s territory: understanding product and business metrics, formulating hypotheses, conducting research, and so on. It might sound like I’m taking work away from PMs, but believe me, they undoubtedly have enough on their plates and are usually more than happy to delegate some responsibilities to designers. Reason #3: You’re Solving The Wrong Problem Before solving anything, ask whether the problem even deserves your attention. During a major home‑screen redesign, our goal was to drive more users into paid services. The initial hypothesis — making service buttons bigger and brighter might help returning users — seemed reasonable enough to test. However, even when A/B testsshowed minimal impact, we continued to tweak those buttons. Only later did it click: the home screen isn’t the place to sell; visitors open the app to start, not to buy. We removed that promo block, and nothing broke. Contextual entry points deeper into the journey performed brilliantly. Lesson learned: Without the right context, any visual tweak is lipstick on a pig. Why did we get stuck polishing buttons instead of stopping sooner? It’s easy to get tunnel vision. Psychologically, it’s likely the good old sunk cost fallacy kicking in: we’d already invested time in the buttons, so stopping felt like wasting that effort, even though the data wasn’t promising. It’s just easier to keep fiddling with something familiar than to admit we need a new plan. Perhaps the simple question I should have asked myself when results stalled was: “Are we optimizing the right thing or just polishing something that fundamentally doesn’t fit the user’s primary goal here?” That alone might have saved hours. Reason #4: You’re Drowning In Unactionable Feedback We all discuss our work with colleagues. But here’s a crucial point: what kind of question do you pose to kick off that discussion? If your go-to is “What do you think?” well, that question might lead you down a rabbit hole of personal opinions rather than actionable insights. While experienced colleagues will cut through the noise, others, unsure what to evaluate, might comment on anything and everything — fonts, button colors, even when you desperately need to discuss a user flow. What matters here are two things: The question you ask, The context you give. That means clearly stating the problem, what you’ve learned, and how your idea aims to fix it. For instance: “The problem is our payment conversion rate has dropped by X%. I’ve interviewed users and found they abandon payment because they don’t understand how the total amount is calculated. My solution is to show a detailed cost breakdown. Do you think this actually solves the problem for them?” Here, you’ve stated the problem, shared your insight, explained your solution, and asked a direct question. It’s even better if you prepare a list of specific sub-questions. For instance: “Are all items in the cost breakdown clear?” or “Does the placement of this breakdown feel intuitive within the payment flow?” Another good habit is to keep your rough sketches and previous iterations handy. Some of your colleagues’ suggestions might be things you’ve already tried. It’s great if you can discuss them immediately to either revisit those ideas or definitively set them aside. I’m not a psychologist, but experience tells me that, psychologically, the reluctance to be this specific often stems from a fear of our solution being rejected. We tend to internalize feedback: a seemingly innocent comment like, “Have you considered other ways to organize this section?” or “Perhaps explore a different structure for this part?” can instantly morph in our minds into “You completely messed up the structure. You’re a bad designer.” Imposter syndrome, in all its glory. So, to wrap up this point, here are two recommendations: Prepare for every design discussion.A couple of focused questions will yield far more valuable input than a vague “So, what do you think?”. Actively work on separating feedback on your design from your self-worth.If a mistake is pointed out, acknowledge it, learn from it, and you’ll be less likely to repeat it. This is often easier said than done. For me, it took years of working with a psychotherapist. If you struggle with this, I sincerely wish you strength in overcoming it. Reason #5 You’re Just Tired Sometimes, the issue isn’t strategic at all — it’s fatigue. Fussing over icon corners can feel like a cozy bunker when your brain is fried. There’s a name for this: decision fatigue. Basically, your brain’s battery for hard thinking is low, so it hides out in the easy, comfy zone of pixel-pushing. A striking example comes from a New York Times article titled “Do You Suffer From Decision Fatigue?.” It described how judges deciding on release requests were far more likely to grant release early in the daycompared to late in the daysimply because their decision-making energy was depleted. Luckily, designers rarely hold someone’s freedom in their hands, but the example dramatically shows how fatigue can impact our judgment and productivity. What helps here: Swap tasks.Trade tickets with another designer; novelty resets your focus. Talk to another designer.If NDA permits, ask peers outside the team for a sanity check. Step away.Even a ten‑minute walk can do more than a double‑shot espresso. By the way, I came up with these ideas while walking around my office. I was lucky to work near a river, and those short walks quickly turned into a helpful habit. And one more trick that helps me snap out of detail mode early: if I catch myself making around 20 little tweaks — changing font weight, color, border radius — I just stop. Over time, it turned into a habit. I have a similar one with Instagram: by the third reel, my brain quietly asks, “Wait, weren’t we working?” Funny how that kind of nudge saves a ton of time. Four Steps I Use to Avoid Drowning In Detail Knowing these potential traps, here’s the practical process I use to stay on track: 1. Define the Core Problem & Business Goal Before anything, dig deep: what’s the actual problem we’re solving, not just the requested task or a surface-level symptom? Ask ‘why’ repeatedly. What user pain or business need are we addressing? Then, state the clear business goal: “What metric am I moving, and do we have data to prove this is the right lever?” If retention is the goal, decide whether push reminders, gamification, or personalised content is the best route. The wrong lever, or tackling a symptom instead of the cause, dooms everything downstream. 2. Choose the MechanicOnce the core problem and goal are clear, lock the solution principle or ‘mechanic’ first. Going with a game layer? Decide if it’s leaderboards, streaks, or badges. Write it down. Then move on. No UI yet. This keeps the focus high-level before diving into pixels. 3. Wireframe the Flow & Get Focused Feedback Now open Figma. Map screens, layout, and transitions. Boxes and arrows are enough. Keep the fidelity low so the discussion stays on the flow, not colour. Crucially, when you share these early wires, ask specific questions and provide clear contextto get actionable feedback, not just vague opinions. 4. Polish the VisualsI only let myself tweak grids, type scales, and shadows after the flow is validated. If progress stalls, or before a major polish effort, I surface the work in a design critique — again using targeted questions and clear context — instead of hiding in version 47. This ensures detailing serves the now-validated solution. Even for something as small as a single button, running these four checkpoints takes about ten minutes and saves hours of decorative dithering. Wrapping Up Next time you feel the pull to vanish into mock‑ups before the problem is nailed down, pause and ask what you might be avoiding. Yes, that can expose an uncomfortable truth. But pausing to ask what you might be avoiding — maybe the fuzzy core problem, or just asking for tough feedback — gives you the power to face the real issue head-on. It keeps the project focused on solving the right problem, not just perfecting a flawed solution. Attention to detail is a superpower when used at the right moment. Obsessing over pixels too soon, though, is a bad habit and a warning light telling us the process needs a rethink. #why #designers #get #stuck #details

In a crowded field full of online survival sims, Dune: Awakening is kicking up storm. The adaptation of Frank Herbert’s sci-fi novels lets players build bases, rid sand worms, and smash Ornithopters into one another. That last part has become a problem, and the developers are already looking into a fix. Suggested Reading10 Minutes From The Last Of Us Part II’s Roguelike Mode Share SubtitlesOffEnglishview videoSuggested Reading10 Minutes From The Last Of Us Part II’s Roguelike Mode Share SubtitlesOffEnglishDune’s Ornithopters are helicopters shaped like dragonflies. In Dune: Awakening, they’re one of the many vehicles players can build that serve as both a resource and an end-goal of sorts. They require a lot of equipment and resources to craft if you’re playing solo, which is why most of them belong to players working in groups. It turns out that they’re pretty indestructible too, making them lethal weapons for ramming enemy players with in PVP. Reddit user Bombe18 shared his run-in with Dune: Awakening’s man-made scourge in a recent clip that blew up on the subreddit showing him repeatedly being accosted by multiple Ornithopters. Shooting at them does nothing. They’re unscathed by constantly smashing into the ground on top of him. At one point, he tries to wall-jump off a ledge and stab one. “Yeah sorry about this,” wrote game director Joel Bylos. “We have people working on fixing the goomba stomping ASAP.”Players have been debating the role of Ornithopters in Dune: Awakening since its beta tests last year. On the one hand, they’re a lot of fun and a cool reward for players to build toward. On the other, they sort of trivialize trying to travel around the desert and survive, the two things the game is supposed to be about. They can also shoot missiles, completely dominating the ground game. Now that’s real desert power. In terms of stopping players from griefing one another with Ornithopters, there are a few different suggestions. Some players just want the vehicles not to be able to be used as weapons at all. Others want them isolated to specific PVP areas. Another solution is to make it easier to destroy them. “Seems like they should just make guns deal more damage to them,” wrote one player. “They’d think twice about doing this if their orni could get wrecked by gunfire.” Another wrote, “Make Deep Desert crashes do significant damage. Two crashes or something past a certain physics threshold should disable the vehicle.”However the developers decide to address the recent outbreak of Ornithopter “goomba stomping,” Dune: Awakening is having a great launch so far. Out earlier this week on PC, it’s nearing a 90 percent positive rating on Steam with almost 20,000 reviews. The concurrent player-count is very healthy, too, peaking at just under 150,000 heading into the weekend. Unfortunately, console players will have to wait a bit to build Ornithropters of their own. A PlayStation 5 and Xbox Series X/S release isn’t planned until sometime in 2026. . #dune #awakening #helicopters #are #039goomba