Innovation

Agrivoltaics – combining land for solar and agriculture – is a genuine win-win. It allows a single piece of land to produce both food and clean energy at the same time. Around the world, farmers are finding that solar infrastructure creates microhabitats that boost resilience, improve yields and reduce water stress. For the agriculture: ✅ Shade from the panels lower ground temperatures and reduces evaporation. In arid areas, this has doubled or even tripled crop yields while cutting irrigation needs by half. ✅ Shade-tolerant crops like lettuce, kale, berries and broccoli thrive under reduced heat stress, especially during extreme weather. ✅ Higher soil moisture also promotes healthier pasture, leading to more nutritious forage for grazing animals. For solar operators: ✅ Sheep naturally keep vegetation under control, reducing mowing and maintenance costs and lowering fire risk. They also prevent plants from shading the panels. ✅ Crops underneath the panels help to cool the modules, improving performance on hot days. And the animals benefit too. A 3-year study of 1,700 sheep at the Wellington Solar Farm in NSW found the sheep produced higher quality wool and more of it. The arrays offer shade in summer, shelter during storms and cooler microclimates throughout the day. Economically it's a strong proposition: - Landowners gain a stable income stream while keeping land productive. - Developers access more viable sites with fewer permitting hurdles. - Communities retain agricultural land and benefit from local investment and tax revenue. And in the US, a significant "solar grazing" industry is emerging, where farmers become vegetation managers. They rent out flocks of sheep to solar farm owners and the sheep trim the vegetation. Agrivoltaics is showing that solar and agriculture don’t have to compete for land. They can thrive together – and create more value in the process. Image credit: Enel Green Power #energy #renewables #energytransition

Grid bottlenecks are a feature — not a bug — of the energy transition. For years, we viewed economics as the main hurdle to scaling clean energy. High costs for wind, solar, heat pumps, and storage dominated the conversation. But the world has changed. Thanks to extraordinary innovation and dramatic cost reductions in renewables and electrification technologies, the bottlenecks we face today are different. They’re no longer about whether clean energy is affordable — it is. Instead, the challenge is whether our energy systems can evolve quickly enough to integrate it. A recent Financial Times piece highlights this clearly: across Europe, the rapid build-out of renewable generation now outpaces the ability of grids to move electricity to where it’s needed. Curtailment, congestion, and long queues for grid connections already cost billions annually — and without decisive action, these costs will grow. This isn’t a sign of failure. It’s a sign of success. It means the transition is happening faster than the infrastructure built for the fossil era can handle. The rise of decentralised, variable renewables and electrified heating and transport requires a fundamentally different approach to planning — one that anticipates growth rather than reacts to it. The EU’s move toward more coordinated, top-down scenario building and cross-border grid planning recognises exactly this. Better alignment between countries and system operators, faster permitting, and prioritisation of critical projects are essential steps to unlock the full value of cheap clean energy. Because every euro lost to bottlenecks is not a cost of climate action — it’s a cost of not modernising our grids fast enough. The more successful we are in deploying renewables and electrification, the more urgently we must upgrade and expand our grids. Grid constraints are not a reason to slow down. They’re a reason to speed up the transformation of an energy system that was never designed for the technologies now powering our transition.

A new 20-year analysis of satellite data shows that the Old Continent’s freshwater reserves are shrinking, silently and steadily. Satellites that weigh the Earth by tracking gravitational changes reveal 👉 Northern Europe is getting wetter. 👉 Southern and central Europe are drying fast. And what’s disappearing fastest is the water we don’t see — groundwater, the strategic reserve that keeps our taps running, our crops alive, and our economies functioning. This is #climatechange in real time. No models, no projections — observations from space. Researchers warn that Europe is barreling toward a 2°C world, and the consequences are already here: • Heavier downpours but longer, harsher dry spells • Winter recharge seasons shrinking • More runoff, less infiltration • Deep aquifers declining across the EU • Increasing pressure on public water supply and agriculture Groundwater is the backbone of Europe’s resilience. In 2022 alone: 🔹 62% of all public water supply came from groundwater 🔹 33% of agricultural demand relied on it 🔹 Groundwater abstractions increased by 6% despite lower overall water use Farmers across southern Europe are watching reservoirs drop while fruit and vegetable yields continue to fall. These are the same dynamics long documented across the Global South, now hitting Europe with unprecedented force. The old assumptions no longer hold. Europe is not water-secure. Infrastructure alone will not save us. New reservoirs arriving in 20 years are not a solution for a crisis happening today. We need: ✅ Radical efficiency — cutting leakage, modernising networks, accelerating water-smart design ✅ Water reuse at scale — separating drinking water systems from non-potable recycled streams ✅ Nature-based solutions — restoring wetlands, aquifers, and natural recharge ✅ Smarter climate-informed water governance — using the best science to guide every decision ✅ A mindset shift — rainwater harvesting, circular water systems, and demand-side management must become standard, not exceptional read the article in The Guardian 👇 https://lnkd.in/eeTsyMve

Empathy Isn’t Missing — It’s Misframed I’ve watched this video countless times. Every time, I don’t see generosity. I see design. I used to believe people ignore the truth because they don’t care. Now I realize it’s because they don’t see what I see. Empathy isn’t a lack of compassion — it’s a lack of perspective. And perspective can be designed. The words didn’t change the man’s story — they changed our frame of perception. When language shifts from description to contrast, it activates awareness. That’s the mechanism behind empathy — it’s not emotional contagion, it’s cognitive reframing. → We respond to difference, not repetition. → We act when a message bridges our world with someone else’s. → We feel when language turns distance into proximity. Here’s how I try to apply that lesson in my own work: ✅ Reveal contrast, not condition. Don’t describe pain — expose the gap between what is and what could be. ✅ Design for awareness before emotion. Help people notice first; feeling follows naturally. ✅ Make others participants, not observers. Use framing that transfers perspective, not pity. ✅ Use silence strategically. Leave room for the reader to complete the meaning. Because empathy doesn’t start with emotion — it starts with architecture. The right words don’t tell people what to feel. They help them feel what was already true. 💭 The Question 👉 When you communicate — are you trying to make people care, or helping them notice what they’ve been blind to all along? #LeadershipDesign #FramingEffect #CommunicationStrategy #CognitiveEmpathy #BehavioralPsychology #PerceptionDesign Video credits: Dr. Marcell Vollmer

Real consumer insight does not sit in market reports. It lives in everyday behaviour. I have always believed that if you want to understand the Indian consumer, you must walk the aisles, visit the kirana stores, and spend time in homes. The questions are simple: why did they choose this brand, what made them switch, what are their latest unsatisfied needs, what habit stopped them from trying something new. The answers are rarely written down. They are observed in the pauses, the hesitations, the way a hand reaches for one pack over another. India is a mosaic of markets. What sells in Chennai might fail in Chandigarh. A message that resonates in Delhi could fall flat in a tier-three town. Income, culture, and even climate shape choices. Unless you immerse yourself in these realities, your strategy risks being built on assumptions. The sharper your consumer insight, the stronger your competitive edge. Do not delegate consumer understanding to agencies or reports. Make it a personal discipline. Sit with retailers, shadow buyers, watch the trade. The real breakthroughs are found not in a meeting agenda, but in how people actually live, shop, and decide. #leadership #entrepreneurship #consumer #mindset

🚨 Introducing the AI Apps 50: Startup Edition Ever wondered how startups are spending their money when it comes to AI? Our team at Andreessen Horowitz worked with Mercury to crunch the numbers and rank the top applications by spend. The list + what we learned from it ⬇️ - Horizontal apps have a slight lead over vertical (60% of the list). This includes general assistants (ex. Perplexity) and SIX different meeting support tools (ex. Fyxer AI). But, it also encompasses creative tools and vibe coding tools that are used in roles across orgs. - Vertical apps can augment human labor...or replace it. We're mostly seeing the former - but five companies on the list allow customers to "hire AI" (ex. Crosby Legal, Cognition, 11x). Labor augmenters mostly assist with customer service, sales, and recruiting. - Vibe coding has landed in enterprises. It's not just a prosumer trend! Number three on the list, below OpenAI and Anthropic? Replit. Other listmakers in the category include Lovable and Emergent, while Cursor made the ranks for more technical users. - Products are making the consumer -> enterprise jump. 12 cos also appeared in our most recent Consumer AI Top 100 - almost all of which started out B2C and have migrated B2B over time. In fact, 70% of listmakers are available for individual use (no enterprise license needed)! Check out the full report: https://lnkd.in/gmMvfvSv

🔮 UX Metrics and KPIs Cheatsheet (Figma) (https://lnkd.in/en9MK4MD), a helpful reference sheet for UX metrics, with formulas and examples — for brand score, desirability, loyalty, satisfaction, sentiment, success, usefulness and many others. Neatly put together in one single place by fine folks at Helio Glare. To me personally, measuring UX success is focused around just a few key attributes — how successful users are in completing their key tasks, how many errors users experience along the way and how quickly users get through onboarding to first meaningful success. The context of the project will of course request specific, custom metrics — e.g. search quality score, or brand score, or engagement score or loyalty — but UX metrics are all around delivering value to users through their successes. Here are some examples: 1. Top tasks success > 80% (for critical tasks) 2. Time to complete top tasks < Xs (for critical tasks) 3. Time to first success < 90s (for onboarding) 4. Time to candidates < 120s (nav + filtering in eCommerce) 5. Time to top candidate < 120s (for feature comparison) 6. Time to hit the limit of a free tier < 7d (for upgrades) 7. Presets/templates usage > 80% per user (to boost efficiency) 8. Filters used per session > 5 per user (quality of filtering) 9. Feature adoption rate > 30% (usage of a new feature per user) 10. Feature retention rate > 40% (after 90 days) 11. Time to pricing quote < 2 weeks (for B2B systems) 12. Application processing time < 2 weeks (online banking) 13. Default settings correction < 10% (quality of defaults) 14. Relevance of top 100 search queries > 80% (for top 5 results) 15. Service desk inquiries < 35/week (poor design → more inquiries) 16. Form input accuracy ≈ 100% (user input in forms) 17. Frequency of errors < 3/visit (mistaps, double-clicks) 18. Password recovery frequency < 5% per user (for auth) 19. Fake email addresses < 5% (newsletters) 20. Helpdesk follow-up rate < 4% (quality of service desk replies) 21. “Turn-around” score < 1 week (frustrated users -> happy users) 22. Environmental impact < 0.3g/page request (sustainability) 23. Frustration score < 10% (AUS + SUS/SUPR-Q) 24. System Usability Scale > 75 (usability) 25. Accessible Usability Scale (AUS) > 75 (accessibility) Each team works with 3–4 design KPIs that reflect the impact of their work. Search team works with search quality score, onboarding team works with time to success, authentication team works with password recovery rate. What gets measured, gets better. And it gives you the data you need to monitor and visualize the impact of your design work. Once it becomes a second nature of your process, not only will you have an easier time for getting buy-in, but also build enough trust to boost UX in a company with low UX maturity. [continues in comments ↓] #ux #design

Something VERY cool just happened in California and… it could be the future of energy.   On July 29, just as the sun was setting, California’s electric grid was reaching peak demand.   However, instead of ramping up fossil fuel resources, the California Independent System Operator (CAISO) and local utilities decided to lean on a network of thousands of home batteries.   More than 100,000 residential battery systems (made up primarily by Sunrun and Tesla customers) delivered about 535 megawatts of power to California’s grid right as demand peaked, visibly reducing net load (as shown in the graphic).   Now, this may not seem like a lot but 535 megawatts is enough to power more than half of the city of San Francisco and that can make all the difference when a grid is under stress.   This is what’s called a Virtual Power Plant or VPP. It’s a network of distributed energy resources that grid operators can call on in an emergency to provide greater resilience to our energy systems. Homeowners are compensated for the dispatch, grid operators are given another tool for reliability, and ratepayers are saved from instability. It’s a win-win-win.   Now, this was just a test to prepare for other need-based dispatches during heat waves in August and September. But it’ historic.   As homeowners add more solar and storage resources, the impact of these dispatch events will become even more profound and even more necessary. This was the second time this summer that VPPs have been dispatched in California and I expect to see even more as this technology improves.   Shout out to Sunrun, Tesla, and all companies who participated. Keep up the great work.

Meta just hit Command + Zuck on its AI strategy - shredding the open-source playbook and replacing it with one that reads: Compute. Talent. Secrecy. The vibe is no longer “open source for all.” It’s “closed doors, infinite compute, elite team, existential stakes.” Let's break it down: (1) Compute: Zuck’s Manhattan Project Meta is building gigascale AI clusters. Prometheus comes online with 1 GW in 2026; Hyperion scales to 5 GW soon after. For context, Iceland’s total electricity consumption is ~2.4 GW, Cambodia is at ~4 GW. Meta’s Hyperion cluster alone could out-consume entire nations. These clusters are for training frontier models - GPT-4-class and beyond. In this new regime, FLOPS per researcher is the KPI, and Meta is going from GPU-starved to GPU-dripping. Each researcher now has more compute to play with than entire labs elsewhere. That’s not just good for performance, it's a hell of a recruiting pitch. (2) Secrecy: From Open Arms to Closed Labs Meta won developer love by open-sourcing its LLaMA models. But it also accidentally became the free R&D department for its own competitors. DeepSeek AI, for example, built on Meta's models and vaulted ahead. Now Meta is reportedly shelving its most powerful open model, Behemoth, due to both internal underperformance and external regret and shifting toward a closed frontier model, aligning more with OpenAI and Google. This is a massive philosophical reversal from “open wins” (as Yann LeCun would say) to “closed dominates.” (3) Talent: Just Buy Everyone Comp packages reportedly range from $200 million to $1 billion for AI leads. All AI efforts are now housed under a new unit, Superintelligence Labs, run by Alexandr Wang (ex-Scale AI). This elite team is small, only ~12 engineers, working in a separate, high-security building next to Zuckerberg himself. Forget beanbags and 10xers. This is a DARPA-style moonshot with a trillion-dollar company behind it. Zuckerberg has said, basically, “Look, we make a lot of money. We don’t need to ask anyone’s permission to spend it.” He’s not wrong. While OpenAI, Anthropic, and xAI rely on outside capital to fund their ambitions, Meta runs on a $165B/year ad engine. And unlike Google and Microsoft - who have boards, activist investors, and share classes that allow for dissent - Zuckerberg controls Meta, structurally and operationally. Meta’s unique dual-class share structure gives Zuckerberg over 50% of the voting power, even though he owns less than 15% of the company. He doesn’t need anyone’s approval, he can build whatever he wants. This makes Meta less like a public company and more like a founder-led sovereign AI lab - with Big Tech cash and startup flexibility. That governance structure is a strategic weapon, letting them place bold, long-term bets at breathtaking speed. Meta’s open-source era is over. This is the closed, compute-soaked, capital-fueled empire play. Less GitHub, more Los Alamos.

Invisible UX is coming 🔥 And it’s going to change how we design products, forever. For decades, UX design has been about guiding users through an experience. We’ve done that with visible interfaces: Menus. Buttons. Cards. Sliders. We’ve obsessed over layouts, states, and transitions. But with AI, a new kind of interface is emerging: One that’s invisible. One that’s driven by intent, not interaction. Think about it: You used to: → Open Spotify → Scroll through genres → Click into “Focus” → Pick a playlist Now you just say: “Play deep focus music.” No menus. No tapping. No UI. Just intent → output. You used to: → Search on Airbnb → Pick dates, guests, filters → Scroll through 50+ listings Now we’re entering a world where you guide with words: “Find me a cabin near Oslo with a sauna, available next weekend.” So the best UX becomes barely visible. Why does this matter? Because traditional UX gives users options. AI-native UX gives users outcomes. Old UX: “Here are 12 ways to get what you want.” New UX: “Just tell me what you want & we’ll handle the rest.” And this goes way beyond voice or chat. It’s about reducing friction. Designing systems that understand intent. Respond instantly. And get out of the way. The UI isn’t disappearing. It’s mainly dissolving into the background. So what should designers do? Rethink your role. Going forward you’ll not just lay out screens. You’ll design interactions without interfaces. That means: → Understanding how people express goals → Guiding model behavior through prompt architecture → Creating invisible guardrails for trust, speed, and clarity You are basically designing for understanding. The future of UX won’t be seen. It will be felt. Welcome to the age of invisible UX. Ready for it?