Business Strategy

Renewables avoided $480 billion in fossil fuel costs last year. And those savings will continue year after year. This is one of the standout findings from IRENA's latest Renewable Power Generation Costs report. Unlike coal and gas power plants, wind turbines and solar panels don't need a continuous supply of fuel. Once they're built, they continue generating electricity without the ongoing cost of buying coal, gas or oil. And this has three important consequences: ✅ Every unit of renewable electricity generated reduces the need to purchase fossil fuels for power generation. ✅ Those avoided fuel costs accumulate year after year over the lifetime of the asset. ✅ They also reduce exposure to volatile fossil fuel prices and improve energy security. IRENA quantified these savings by comparing actual renewable generation in 2025 with an alternative scenario in which the same electricity was instead generated by each country's existing fossil fuel mix. The result was an estimated $480 billion in avoided fuel costs – and this is just a single year. The economics of renewable energy are often discussed in terms of the cost of building it, but one of its biggest economic advantages comes afterwards. Unlike a one-off saving, avoided fuel costs repeat every year a wind farm or solar farm remains in service.

The Anatomy of a new Claude 'Fable 5' Prompt: 1. Task Start with why, NOT what.  Claude 5 connects the dots. 'I'm working on [goal] for [who it's for]. They need [what the output enables]. With that in mind: [task].' 2. Context Files Upload your expertise. Stop explaining in prompts. "Read these files completely before responding: [filename .md] - [what it contains]." The file is the brain. This part never changes. 3. Reference Show Claude 5 what good looks like. "Reference for what I want to achieve: [paste]." One example beats ten instructions. 4. Effort The new change, a few people are talking about. "This is a [routine / hard / hardest-unsolved] problem. Scope it like it's at the top of your range." Teams testing Claude 5 on easy tasks undersell it.  Give it your hardest problem. 5. Act "AskUserQuestion" is still the king. Add "When you have enough information to act, act. Don't re-litigate my decisions. While weighing a choice, give a recommendation." 6. Scope Claude 5 over-delivers by default. Control it. "Do the simplest thing that works well. No extra features, refactors, or abstractions. If I'm describing a problem, the deliverable is your assessment." The old one did too little. This one does too much. 7. Delegate One Claude is no longer the limit. "Split independent subtasks across subagents & keep working while they run. Verify with a fresh-context subagent." It's not a chatbot anymore. It's a team lead. 8. Evidence The line that removes fake progress reports. "Before reporting progress, audit every claim against a tool result. If it's unverified, say so. Tests failed? Show the output." Anthropic tested this.  It nearly eliminated fabricated status updates. 9. Memory Claude 5 gets smarter every run. If you let it. "Record learnings in [notes .md] — one per file. Update, no duplicate. Delete what turns out wrong." Your prompts expire. Your learning file compounds. 10. Checkpoint It can run for hours. Decide when it stops. "Pause only for: destructive actions, scope changes, or input only I can provide. Never end your turn on a promise." The old fear was Claude stopping too late.  The new fear is stopping too early. 11. Report The last block. The first thing you read. "Open with the outcome - the TLDR I'd ask for. Complete sentences. Clear beats short." It worked for hours. You read for ten seconds. Copy the full prompt template + download my personal md. files for Claude here: Step 1. Go to how-to-ai.guide. Step 2. Subscribe for free. Don't pay anything. Step 3. Open my welcome email. Step 4. Hit the automatic reply button inside. Step 5. Download my .md files. Ready to upload.

Saudi Arabia built the world's largest virtual hospital, and we haven't even heard of it. It connects 224 hospitals and treats 400,000 patients a year without a single physical bed. It's called Seha Virtual Hospital in Riyadh, and it just earned a Guinness World Record for being the largest virtual healthcare provider in the world. But how can a hospital be “virtual”? How does it work? → Imagine you live in a small town with only a basic local hospital. → It has doctors and equipment. But if you need a cardiologist or neurologist, you travel 6+ to a bigger city. In urgent situations, people lose lives. → With Seha, specialists treat you remotely through your local hospital - reviewing scans, diagnosing conditions, prescribing treatment - while local staff execute it. That's the model. Specialist expertise delivered through existing hospitals. And here's what makes it work: ▶️ AI prioritizes urgent cases - analyzes CT scans and imaging to rank who needs immediate intervention ▶️ IoT monitors patients remotely - heart failure patients wear devices that alert doctors before hospitalization is needed ▶️ Integrated health records - manages prescriptions and reports across all 224 hospitals in real-time The results? - ICU patients now stay an average of 4 days instead of weeks.  - Stroke patients get CT scans within 25 minutes of arrival. - Treatment starts in 28 minutes.  - Radiology reports in 2 hours. This isn't telemedicine where you video-call a doctor from home. This is expertise delivered through your local hospital without the specialist being physically there. It proves you don't need cardiologists and neurologists in every town. You just need good internet and hospitals willing to collaborate. Do you think virtual hospitals could solve specialist shortages in rural areas? #Entrepreneurship #healthtech #innovation

Gartner just surveyed 350 large enterprises deploying AI. 80% cut jobs. Some by as much as 20%. The result? The companies that cut the most showed nearly identical financial returns to the ones that cut the least. In several cases, the ones that cut less performed better. No correlation between AI-driven layoffs and improved ROI. None. Gartner's Helen Poitevin was direct: "Workforce reductions may create budget room, but they do not create return." Cutting people frees up cash. It does not generate value. Most leadership teams are conflating the two. So what actually works? Upskilling staff to work alongside AI. Redesigning roles around what humans do well vs. what AI does well. Building operating models where people guide autonomous systems instead of getting replaced by them. There's a real difference between using AI to do the same work with fewer people and using AI to unlock work that was previously impossible. The first saves money on paper. The second compounds over time. We've already seen the pattern. Klarna cut 700 CS roles, watched quality decline, and started rehiring. IBM automated HR functions and reversed course. The Commonwealth Bank of Australia reversed 45 AI-driven layoffs after realizing those roles were never redundant. Gartner predicts half of companies that attributed headcount cuts to AI will rehire under new titles by 2027. If someone in your org is building an AI business case around headcount reduction, share this data. The assumption that fewer people equals better margins equals better returns is not supported by the evidence. AI is not leading to a jobs apocalypse. It's changing the shape of what people do. The companies that understand that difference will be the ones worth working for, and buying from, three years from now. Read the full piece on State of Brand here: https://lnkd.in/ggH-NXyM

A Brooklyn developer just leased 25% faster than 7 competing projects in a 3-block radius. Rents 10-20% above market. With 18 more lease-ups in the pipeline, many backed by institutional developers with bigger budgets and stronger brands. The edge wasn't location or capital, but a design-oriented focus on the drivers of real rent premiums. Fve lessons from Charney Companies' development at Union Channel in Brooklyn, New York: 1/ Unit mix. Pulled architectural plans for every competing project in the market. 3-bedrooms were 3% of supply but demand pointed to 14%. Union Channel tripled the market average. They were the first unit type to fully lease. 2/ Studios. Market average was 500 sqft at $3,500/month. Too much space, too much rent. Union Channel built 400 sqft studios — 20% smaller, 10% cheaper. Leased 50% faster than the rest of the building. 3/ Living rooms. Of every layout variable tested across hundreds of units, living room width was the single strongest predictor of rent per sqft. Every other layout decision was calibrated to protect it. 4/ Amenities. Conventional wisdom says more amenities = more value. The data says the opposite. Quality of select amenities beats breadth. Fitness center quality had the strongest correlation with rent per sqft. They hired a gym consultant instead of designing in-house. 5/ Marketing. 20% of leases came directly from social media — 4x the rate on prior projects. Strategy built around the neighborhood, not the building. Murals on construction fencing. 3,000 organic Instagram followers before opening. These five decisions account for 73% of the value created at Union Channel. All made before the building opened. The data exists in every market. Most developers just aren't looking. Full case study from Andrew Steiker-Epstein in this week's Thesis Driven newsletter. Link in comments.

The UK is brilliant at starting businesses. We are terrible at scaling them because we ignore these signs. I see this frequently working with founders running businesses between £3m and £100m. They have ambition, and the hard work is there. But a handful of things are holding them back from making that step-change to a large company. Take it from me. I made most of these mistakes myself at HomeServe. Here are the 8 warning signs your business is not ready to scale: (And how to fix them to ensure it is...) 1️⃣ You haven't proved the model ↳ Scaling costs before you have a working model does not create economies of scale. Stay small and keep testing until the cash comes in consistently. 2️⃣ You are still doing the CEO's job ↳ If every decision runs through you, the business cannot grow beyond you. Hire your replacement. Find someone better than you to run the day-to-day. Then work on the business, not in it. 3️⃣ You cannot explain your strategy in a sentence ↳ If your team cannot tell you what the business does and why in one sentence, it is not clear enough to execute. Answer three questions: what are you passionate about, what can you be the best at, and how will you make money. Write it in 20 words or fewer. 4️⃣ You are chasing too many ideas ↳ The history of HomeServe is littered with mistakes brought on by my instinct for grabbing every shiny new idea. Build a not-to-do list. If it does not fit your 20-word strategy, it goes on the list. 5️⃣ Your culture hasn't kept pace with your headcount  ↳ Scaling too fast without defined values nearly cost us the culture that made HomeServe successful. Define three to five core values. Every employee should know what the business stands for and why it matters. 6️⃣ You cannot predict cash flow ↳ If your cash flow is unstable or unpredictable, you are not ready to focus on revenue and profit yet. Look at cash flow every week without fail. Only when it is stable and consistent can you shift your attention to scaling revenue and improving margins. 7️⃣ You are still trying to reinvent the wheel, instead of evolving  ↳ When HomeServe strayed into furniture warranties, we lost money and had to sell it off to refocus on what was working. Ask yourself honestly: Are you clear on your product market fit and what your core is ? If not, you will run into problems scaling. 8️⃣ You have no one to challenge your thinking ↳ When I was building HomeServe, I had no peer group of fellow founders to learn from. You will scale faster with fewer wrong turns when you find the right counsel. That's precisely why I've begun sending out my weekly newsletter, How to Make a Billion.  Subscribe here to start reading: https://lnkd.in/ergDQtiK

The European Central Bank is now making the economic case for decarbonisation. Not as climate policy. As monetary policy. Frank Elderson, ECB board member, argues in the Financial Times that Europe's dependence on imported fossil fuels is a structural threat to price stability (👉 https://lnkd.in/eKWWjKbh). The data is damning: energy price shocks pushed euro area inflation to 10.6% in October 2022. Every geopolitical tremor in the Middle East shows up in European energy bills. And the ECB is caught in an impossible bind: tighten to fight inflation and deepen the slowdown, ease to support growth and entrench inflation. The solution is not better forecasting models or finetuned monetary policy. It is cheaper energy. Spain shows what is possible. Wholesale electricity prices in early 2024 were approximately 40% lower than they would have been had wind and solar generation remained at 2019 levels ( 👉 https://lnkd.in/edXgxh9q). Once the infrastructure is built, the energy itself is virtually free. Volatile global commodity markets simply become less relevant. Elderson is explicit: €660 billion per year in clean energy investment sounds large. But Europe already spends nearly €400 billion annually on fossil fuel imports, money that leaves the continent and buys geopolitical vulnerability. Analysis in the UK shows that for every pound invested in sustainable energy, benefits outweigh costs by a factor of 2.2 to 4.1 ( 👉 https://lnkd.in/emEXVfiw). This is precisely what I argued in my piece for Triodos a few weeks ago: Europe's crisis response has been backwards. We keep treating energy dependence as a shock to manage rather than a structural problem to fix. (👉https://lnkd.in/ehFqA6iY) The ECB cannot decarbonise Europe. What it can do is name the conditions: keep the ETS, mobilise capital toward renewable capacity, strip out fossil fuel subsidies, and stop confusing cheap fossil fuels with affordable energy. If people need help with energy costs, target it: don't suppress the price signal that drives the transition. The cheapest energy is the energy we no longer have to import.

Spain's renewables build-out has structurally decoupled its electricity prices from gas markets. Gas now sets the price in only around 15% of hours, compared to nearly 90% in Italy. The lesson for Europe is clear: countries that invested early in clean power are far less exposed to fossil fuel price shocks, and those that didn't are now paying the price

Our research center in Princeton has become a magnet for healthcare AI expertise. Every time I catch up with Dorin Comaniciu and the team there, conversations quickly move from what’s possible to what really matters in healthcare delivery. Take for instance, our work on what we call the Operational Twin, an advisory service. It starts with creating a virtual representation of a clinical department, reflecting how patients, staff, and equipment interact in everyday operations so that different scenarios can be explored more safely and at scale. By simulating billions of scenarios representing dynamic conditions, AI agents learn how operational decisions shape outcomes. They can begin to anticipate bottlenecks and understand the long-term impact of short-term choices. The goal is more efficient planning of patient schedules, staffing, and equipment use, aligning daily decisions with broader clinical and organizational priorities. This becomes even more relevant as clinical innovations accelerate workflows. Faster scanning technologies such as Deep Resolve can shorten patient timeslots and an Operational Twin can help organizations adapt by optimizing schedules and resources to fully realize gains in speed and throughput. At its core, this work is about creating clarity in complex systems so that action becomes more precise and more purposeful. We see a similar principle in clinical innovation. With photon counting CT, we can visualize the heart in extraordinary detail, including structures inside the left ventricle that were previously difficult to see clearly. That deeper insight is captured by a Foundation Model that could help physicians guide ablation therapies with greater precision and confidence, especially when combined with live ultrasound to support real-time decision making in the procedure room. In both cases, whether in clinical imaging or in operations, the ambition is the same: better insight leading to better decisions at the moments that matter most for patients. 𝘋𝘪𝘴𝘤𝘭𝘢𝘪𝘮𝘦𝘳: 𝘛𝘩𝘦 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘴/𝘧𝘦𝘢𝘵𝘶𝘳𝘦𝘴 𝘢𝘯𝘥/𝘰𝘳 𝘴𝘦𝘳𝘷𝘪𝘤𝘦 𝘰𝘧𝘧𝘦𝘳𝘪𝘯𝘨𝘴 𝘮𝘦𝘯𝘵𝘪𝘰𝘯𝘦𝘥 𝘩𝘦𝘳𝘦 𝘢𝘳𝘦 𝘯𝘰𝘵 𝘺𝘦𝘵 𝘢𝘷𝘢𝘪𝘭𝘢𝘣𝘭𝘦 𝘪𝘯 𝘢𝘭𝘭 𝘤𝘰𝘶𝘯𝘵𝘳𝘪𝘦𝘴. 𝘐𝘧 𝘵𝘩𝘦𝘴𝘦 𝘴𝘦𝘳𝘷𝘪𝘤𝘦𝘴 𝘢𝘳𝘦 𝘯𝘰𝘵 𝘮𝘢𝘳𝘬𝘦𝘵𝘦𝘥 𝘪𝘯 𝘤𝘦𝘳𝘵𝘢𝘪𝘯 𝘤𝘰𝘶𝘯𝘵𝘳𝘪𝘦𝘴 𝘧𝘰𝘳 𝘭𝘦𝘨𝘢𝘭 𝘰𝘳 𝘰𝘵𝘩𝘦𝘳 𝘳𝘦𝘢𝘴𝘰𝘯𝘴, 𝘵𝘩𝘦 𝘴𝘦𝘳𝘷𝘪𝘤𝘦 𝘰𝘧𝘧𝘦𝘳𝘪𝘯𝘨𝘴 𝘤𝘢𝘯𝘯𝘰𝘵 𝘣𝘦 𝘨𝘶𝘢𝘳𝘢𝘯𝘵𝘦𝘦𝘥. 𝘍𝘰𝘳 𝘮𝘰𝘳𝘦 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯, 𝘱𝘭𝘦𝘢𝘴𝘦 𝘤𝘰𝘯𝘵𝘢𝘤𝘵 𝘺𝘰𝘶𝘳 𝘭𝘰𝘤𝘢𝘭 𝘚𝘪𝘦𝘮𝘦𝘯𝘴 𝘏𝘦𝘢𝘭𝘵𝘩𝘪𝘯𝘦𝘦𝘳𝘴 𝘳𝘦𝘱𝘳𝘦𝘴𝘦𝘯𝘵𝘢𝘵𝘪𝘷𝘦.

A learning culture is not built by offering more training. It emerges where curiosity, connection, and purpose intersect. Andrew Barry, in The Curious Lion, describes learning culture as a lotus where several forces overlap. I find this framing helpful because it moves the conversation beyond HR programs and into the fabric of the organization. At the individual level, there is curiosity. People must feel invited to ask questions, challenge assumptions, and explore. Without individual curiosity, learning remains compliance. At the organizational level, there is mission. Learning needs direction. When people understand what the company stands for and where it is going, their curiosity becomes focused rather than scattered. At the relational level, there is human connection. Learning accelerates in environments where people feel safe to speak, experiment, and reflect together. The fourth circle is continuous learning. Learning must be ongoing, not episodic. Not a workshop, but a way of operating. Continuous learning ensures that curiosity, mission, and connection reinforce each other over time rather than fading after the latest initiative. When these circles overlap, deeper elements emerge: Shared vision aligns effort. Shared experiences create collective memory. Shared assumptions shape how reality is interpreted. Shared stories transmit meaning across generations. At the center sits what we call learning culture. Not an initiative, but a pattern of how people think, relate, and evolve together. The question for leaders is not, “Do we offer learning opportunities?” It is, “Do curiosity, mission, and connection truly reinforce each other continuously in our organization?” That is where learning becomes cultural rather than occasional.