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Our frontend builds crossed 20 minutes. The obvious move was to rip out Webpack for something faster. We didn't. Before touching a single line of config, we profiled the entire pipeline. Webpack's ProgressPlugin turned up something we didn't expect — one plugin, Terser, was eating 13+ minutes of every build. Webpack wasn't the bottleneck. JavaScript minification was. 🔍 That one number changed the whole plan. We kept Webpack. Replaced Babel with SWC. Swapped Terser for esbuild. Moved CSS optimisation to LightningCSS. Parallelised compilation across cores with thread-loader. ⚙️ Fixed a hidden bottleneck too — AWS CodeArtifact tokens were re-authenticating every 12 hours and quietly busting our Docker cache. Restructured the Dockerfile into layers that actually cache. 🐳 20 minutes to 2 minutes. Cold build ~90% faster. Incremental ~95% faster. Across 20 production apps, 600+ PRs a month, 5,000+ CI runs. ⚡ No migration. No four-week rewrite. No new bundler to debug for the next year. The real lesson wasn't about tooling. It was that we almost skipped measurement and went straight to migration — the industry default. Glad we didn't. 💡 Full breakdown — the Speed Measure Plugin data, the pnpm switch, the exact Dockerfile changes — link in the first comment. 👇 Really proud of what our engineering team pulled off here. Worth the read. 🫡 Zepto Zepto Tech #ZeptoTechXPress #ZeptoEngineering

𝗡𝗮𝗶𝘃𝗲 𝗥𝗔𝗚 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻 𝗮 𝗱𝗲𝗺𝗼. 𝗜𝘁 𝗳𝗮𝗶𝗹𝘀 𝘁𝗵𝗲 𝗺𝗼𝗺𝗲𝗻𝘁 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲𝗿𝘀 𝘀𝗵𝗼𝘄 𝘂𝗽. Embed → retrieve → generate looks clean in a notebook. Real requirements break it: → Questions whose answer is spread across many documents → Industry terms that embeddings get wrong → Bad chunks the pipeline never catches → Answers that live in how things connect, not in any single chunk → PDFs full of tables and images a text-only index cannot read These 5 architectures are how serious teams stay ahead in the agentic AI era: 𝟬𝟭 𝗛𝘆𝗯𝗿𝗶𝗱 𝗥𝗔𝗚 → Dense vectors find meaning. BM25 finds exact words. → Reciprocal Rank Fusion combines both ranked lists. → A safe baseline for almost every team. 𝟬𝟮 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚 → Pull entities and their relationships into a knowledge graph. → Retrieve subgraphs and community summaries, not chunks. → Best when the answer lives in how things connect. 𝟬𝟯 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 → A planner agent picks the right tool: vector, web, or SQL. → A reasoner agent keeps trying until the answer is solid. → Retrieval becomes a plan, not a single step. 𝟬𝟰 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝘃𝗲 𝗥𝗔𝗚 (𝗖𝗥𝗔𝗚) → Grade every retrieval before you trust it. → Correct → answer. Unclear → rewrite the query. Wrong → search the web. → This is what production RAG actually looks like. 𝟬𝟱 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗥𝗔𝗚 → One embedding model (CLIP, ColPali) for text, images, and tables. → One vector index. One multimodal LLM. → No more separate pipelines for PDFs with charts. I built a runnable example for each of the five patterns. GitHub link in the first comment. The best teams in 2026 do not pick one. They combine them — hybrid retrieval inside an agentic loop, with a corrective grader, over a multimodal index. Naive RAG is a starting point, not a finish line. That is why most enterprise GenAI projects stall at the demo. Which of these five becomes the default RAG stack in the next 18 months — and which stays a specialized tool?

Only 25% of wealthy families successfully preserve wealth into the second generation. Roughly 10% make it to the third generation, and just 5% sustain that wealth into the fourth. Those numbers help explain why many Family Offices are being forced to rethink their structure, priorities, and long term purpose. The traditional image of the Family Office has long been tied to scale, exclusivity, and large internal operations. Dedicated investment teams, private legal counsel, concierge services, and layered governance structures became markers of sophistication for ultra wealthy families seeking greater control over their financial lives. Now, many Family Offices are moving in a different direction. Despite continued growth in global wealth, a rising number of Family Offices are downsizing, consolidating operations, or shutting down entirely. The shift has less to do with declining wealth and more to do with rising complexity, operational costs, and changing generational priorities. Maintaining a fully staffed Family Office today requires significant expense across talent, compliance, cybersecurity, technology, and administration. For many families, especially those below the ultra large institutional level, the structure no longer delivers the efficiency it once promised. The issue is rarely investment performance alone. More often, wealth disappears because of weak governance, lack of communication, succession failures, entitlement, and growing family fragmentation over time. Generational transition is also reshaping the Family Office itself. Second and third generation family members often bring different investment philosophies, levels of involvement, and long term priorities. As families spread across multiple regions and jurisdictions, alignment becomes more difficult and governance grows more complicated. In response, many families are adopting leaner structures focused on oversight and strategy while outsourcing specialized functions to external partners. Investment management, estate planning, reporting, cybersecurity, and administrative services can now be handled externally with institutional quality support. Technology has accelerated this shift, allowing smaller teams to operate with greater efficiency and visibility than ever before. The conversation is also becoming more intentional. Many families are no longer measuring success by the size of their operation. Instead, the focus has shifted toward governance, communication, succession planning, and long term family cohesion. In many cases, a smaller and more focused Family Office structure may be better suited for preserving wealth across generations than a large internal organization weighed down by complexity. The Family Office industry is still growing globally, but the model itself is changing. The future Family Office will likely be defined less by size and more by adaptability, clarity, and strategic coordination.

2026 will be an unprecedented year for consumer electronics, and the smartphone industry in particular. For fifteen years, the smartphone industry relied on a single, reliable assumption: components would inevitably get cheaper. While short-term volatility existed, the long-term downward trend in memory and display costs allowed for annual spec bumps without price hikes. In 2026, that model has finally broken, driven by a sharp and unprecedented surge in memory costs. AI has fundamentally reshaped demand. The same memory used in smartphones is now critical for AI data centers, as hyperscalers lock in silicon wafer capacity years in advance to fuel the AI boom. For the first time, smartphones are competing directly with AI infrastructure and memory prices are rising sharply as a result. In some cases, memory costs have already increased by up to 3x, with further rises expected as unprecedented demand continues to swallow available supply. Memory is fast becoming one of the most expensive smartphone components and potentially the single largest cost driver in the bill of materials by year-end, with estimates suggesting that memory modules which cost less than $20 a year ago could exceed $100 by year-end for top-tier models. The result is a structural shift. This is a reversal of everything we’ve come to expect from this industry. When something that used to get cheaper every year suddenly becomes a lot more expensive, the economics of building a smartphone fundamentally change. Brands now face a simple choice: raise prices, by 30% or more in some cases, or downgrade specs. The “more specs for less money” model that many value brands were built on is no longer sustainable in 2026. As a result, some markets, particularly entry and mid-tier segments, are likely to shrink by 20% or more, and brands that have historically dominated these segments will struggle. Pricing will inevitably also increase across our smartphone portfolio, particularly as we will upgrade some products launching this Q1 to UFS 3.1. However, for Nothing, the current situation represents a great opportunity. Operating without the cost advantages of industry giants forced us to innovate differently. We learned early on that we couldn’t win on spec sheets alone; instead, we focused on perfecting the user experience, proving that how a phone looks and feels matters far more than its raw numbers. That’s where our focus has always been. 2026 is the year the "specs race" ends. As the industry resets, experience becomes the only real differentiator. That is exactly what Nothing was built for. The era of cheap silicon is over. The era of intentional design is just beginning.

ceo: where’s the buyer in the funnel? cmo: yes. ceo: top? middle? bottom? cmo: …all. none. depends on when you look. ceo: be serious. cmo: okay. they liked our post in March, opened an email in May, toured a model in July, vanished, then showed up yesterday ready to buy. ceo: that’s not how the funnel works. cmo: correct. because the funnel doesn’t exist anymore. ceo: then what does exist? cmo: chaos. beautiful, behavior-driven chaos. ceo: renames slide “embracing the chaos: our modern marketing strategy” Buyers have been rewriting their journeys. And they are non-linear. Sporadic. Platform-hopping. Emotion-led. And timeline-flexible. Which means the real competitive advantage isn’t the funnel. It’s the ecosystem. The brand, the content, the digital experience, the trust you’ve built over time. That’s what catches them whenever they resurface.

I once lived at distributor’s home in a small town because I had no choice... When Marico Limited was nascent, Bombay Oil Industries was still the family’s backbone. In those early days, I wanted our business to transform from a commodity trade into a branded consumer company. To do that, I had to understand the ground truth. There were no fancy hotels in the towns we visited. I stayed in dusty and small guest rooms. I sat with distributors over chai and samosas. I watched how coconut oil was stored, how shopkeepers priced it, how packaging changed hands. One day, a retailer told me matter-of-factly: “You always sell big tins. When people come back to buy, they carry a few kilos. If your packet is small, they will pick your brand at convenience.” That simple insight was a turning point. It nudged us to expand SKU ranges, introduce smaller packs, and think about how to become a “grab-and-go” brand, rather than just a bulk commodity supplier. If you ask me where innovation begins, it begins in the least glamorous places. In the musty shelves of neighbourhood stores, in conversations that feel insignificant, in paying attention to what people don’t say aloud. Takeaway for entrepreneurs: Your real research lab isn’t spreadsheets or agencies. It’s the ground. If you go build empathy for your customer at the shelf level, the brand strategy almost builds itself. #entrepreneurship #business #resilience #mindset #growth

Rick Rubin went on stage in Helsinki the day after my talk. Someone asked how he resolves creative differences with artists. His answer was simple: change the conversation from "I disagree" to "let's build it." Then he shared a story: An artist played him a song. The transition didn't work. Rubin told him so. The artist said, "We'll just cut that part in half." Rubin thought to himself: What a dumb idea. But he didn't say that. He said, "Let's try it." The artist played it. It worked. Rubin is a legend. He's produced everyone from Johnny Cash to Jay-Z. Instead, he bit his tongue and let the artist prove him wrong. The principle: when you make an idea tangible, it stops being the person's idea. It becomes something you can both look at objectively and improve together. Once you build it, the truth is obvious. Here's what this looks like in practice: Your designer wants to change the entire homepage layout. You think it's too risky. Instead of three meetings debating it, you say: "Let's build a prototype and test it with 50 users this week." Your sales team wants to restructure the pricing page. Instead of blocking it because you're worried about conversions, you say: "Let's run it as an A/B test on 20% of traffic for two weeks." Your engineer wants to rebuild a core feature from scratch. You think it's overengineered. But instead of killing it in the planning phase, you say: "Spike it out in three days and show me if the performance gain is real." You're not saying yes to everything. You're saying, "Let's find out." Rubin also said something that stuck with me: "If there's disagreement, I always side with the artist's vision. Because to them, it's their career. To me, it's just one piece of my portfolio." Most leaders think backing down makes them look weak. Rubin knows that siding with the person who has the most at stake makes better work happen. Your job isn't to be right. It's to create the conditions where the best idea wins. Stop debating. Start building. P.S. This insight is from this week's newsletter where I break down why Yamaha dominates while Steinway got sold to private equity: https://lnkd.in/efSqP_9K P.P.S. Access additional research links, the podcast, and the full archive in the first comment 👇 Thank you to Nordic Business Forum!

Vitamin D3 supplementation: largely accepted nowadays. Creatine: starting to break through. Next: Magnesium (Threonate or Bisglycinate). Why? Well, for starters, Mg can protect against hearing loss. There is solid data on reducing migraines, and it can improve sleep. 30–60 minutes before bed. I have an episode of the podcast with an MD, PhD and chair of a major medical school department who explains why Mg is beneficial for many people. The old guard that dismisses supplements is dissolving away. And of course Rx meds still matter, but the landscape is not the same anymore. And as always—and I’ve stated this in pretty much every podcast and every venue I possibly can—you have to get your behaviors right. Supplements are not a replacement. It’s obvious, but people overlook it nonetheless.

In the race to AI dominance, only a fraction of companies are truly future-ready, while the rest scramble to catch up! How about CPG & FMCG companies? We're building on MIT CISR (MIT Center for Information Systems Research) research into the Four Stages of Enterprise AI Maturity. In the matrix below, we categorized leading #CPG brands across four progressive stages: 1. Experiment & Prepare 2. Build Pilots & Capabilities 3. Develop AI Ways of Working 4. Become AI Future-Ready It's clear that while many brands are still in early experimentation (e.g., adidas, Diageo, The Estée Lauder Companies Inc.), a select few like Nestlé, The Coca-Cola Company, L'Oréal, LVMH, Procter & Gamble, and Unilever are pioneering Stage 4, embedding AI into decision-making, creating AI-augmented services, and combining traditional, generative, agentic, and robotic AI for continuous innovation and new revenue. ++ 𝗞𝗲𝘆 𝗵𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 ++ - Stage 1 (Experiment & Prepare): Dominated by 21 brands (e.g., BAT, Carlsberg Group, Henkel, Kimberly-Clark), focusing on workforce education, policy-setting, data accessibility, and human-in-the-loop identification. - Stage 2 (Build Pilots & Capabilities): 7 brands (e.g., 3M, Danone, The HEINEKEN Company, Kraft Heinz, Mondelēz International, Tyson Foods) are automating processes, creating use cases, sharing data via APIs, and leveraging coach-and-communicate styles with LLMs and generative AI models. - Stage 3 (Develop AI Ways of Working): Just 3 brands (AB InBev, Nike, PepsiCo) are scaling automation, adopting test-and-learn cultures, architecting for reuse, incorporating pretrained models, and exploring agents. - Stage 4 (Become AI Future-Ready): This elite group is future-proofing with AI-embedded decisions, proprietary models, and hybrid AI types—driving above-average growth in SC, marketing, and #eCommerce. AI is projected to generate $500 billion in value for global CPG by 2025, with investments exceeding $2.5 billion in AI/ML, boosting profitability by 2-5% via pricing and reducing supply chain errors by 50%. ++ 𝟯 𝗧𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗖𝗣𝗚 & 𝗙𝗠𝗖𝗚𝘀 ++ 1. Start with Education and Pilots (Stages 1-2): Invest in #AI literacy programs for your workforce and launch targeted pilots. 2. Scale with Reusable Architectures (Stage 3): Build scalable AI platforms with pretrained models and dashboards for real-time insights; focus on test-and-learn cultures to automate processes and explore #AgenticAI for autonomous operations. 3. Embed AI Enterprise-Wide (Stage 4): Combine generative and robotic AI for decision-making, such as AI-augmented product innovation or sustainable services—target new revenue streams like personalized nutrition apps. The analysis focuses on AI mentions (derived from search result volumes and unique initiatives), maturity stages (aligned with MIT CISR's 4-stage model, sources (web citations from searches), and detailed AI technologies where available.

Psychology behind building objects of DESIRE. Lets talk about LIFESTYLE beauty, a territory beyond functionality. Think on aspirations, symbology, luxury, identity, and status. In lifestyle, desire is cultivated not just through product performance, but through emotional branding, scarcity, and curated experiences. you are looking for deep understanding of what your customers truly value, and what frustrations your brand can solve. The global premium cosmetics market is experiencing growth, with a market value of USD 153.68 Billion in 2024, and is projected to reach USD 353.93 Billion by 2034, growing at a CAGR of 8.70% >> PSYCHOLOGY OF DESIRE << Desire-driven purchases tap deeply into the brain’s EMOTIONAL and reward systems. When we encounter luxury or exclusive products, our brains release dopamine in anticipation of the reward, sparking motivation and craving. +72% consumers make purchase based on emotional connection with a brand or product. This anticipation is often stronger than the actual satisfaction of owning the item. Scarcity and limited availability trigger the amygdala, activating fear of missing out (FOMO) and increasing the product’s perceived VALUE. +332% conversion rates by Limited-time offers or “only 2 left” messages. +48% of online shoppers have purchased something due to FOMO. At the same time, mirror neurons make us subconsciously IMITATE influencers or aspirational figures who use these products, reinforcing the desire to buy. +84% Gen Z and Millennials are influenced by social media before making purchases. >>DESIRE BUILDING<< →Emotional triggers ⇒ Emotional design drives deep connection & impulse. →Dopamine surge ⇒ Reward anticipation, not the reward, excites the brain. →Scarcity ⇒ Limited triggers urgency & fear of missing out. →Mirror neurons ⇒ Aspirational figures builds subconscious imitation. →Exclusivity ⇒ Luxury signals status, elevating perceived self-worth. →Desire ⇒ Controlled access makes products feel more valuable. →Impulse buy ⇒ Emotional + social triggers pull quick decisions. >>RATIONALIZE MEMORIES ⇒ LOYALTY<< Emotional connection also plays a major role. The prefrontal cortex helps us RATIONALIZE emotionally-driven decisions, while the hippocampus links products to MEMORIES, making them more meaningful. Oxytocin fosters trust and LOYALTY when a brand aligns with personal values or tells a compelling story. In essence, we don’t just buy products, we buy identity, emotion, and experience. Final thoughts. In lifestyle beauty, products are desired, not just bought. It's about sparking emotion, not just solving problems. Build aspiration, connection, and identity by tapping into what truly drives your audience. Here’s my curated search of examples, get inspired for your next HIT! Featured Brands: Carolina Herrera Chanel Beautycrop Benefit Bubble Glossier Glow to Go Gucci Miu miu Rhode Some by me Tocobo #beautybusiness #luxurbusiness #beautyprofessionals #luxuryprofessionals