Business Strategy

This is the most underrated way to use Claude: (and it has nothing to do with writing or coding) It's competitive intelligence. Using data that's free, public, and updated every single week. Here's my extract step by step guide: Step 1. Go to claude .ai. Step 2. Select the new Claude "Opus 4.6." Step 3. Turn on "Extended Thinking." Step 4. Pick a competitor. Go to their careers page. Step 5. Copy every open job listing into one doc. (Title. Team name. Location. Full description) Step 6. Save it as one .txt or .docx file. Step 7. Search the company at EDGAR (sec .gov) Step 8. Download its recent 10-K or 10-Q filing. (Official strategy, risks, and financials - all public.) Step 9. Upload both files to Claude Opus 4.6. Step 10. Paste this exact prompt: "You are a competitive intelligence analyst at a rival company. I've uploaded [Company]'s complete current job listings and their most recent SEC filing. Perform a strategic intelligence analysis: → Cluster these roles by what they suggest is being built. Don't use the team names they've listed. Infer the actual product initiatives from the skills, tools, and responsibilities described. → Identify capabilities or teams that appear entirely new — not mentioned anywhere in the SEC filing. These are unreleased bets. → Find roles where seniority is disproportionately high for a new team. This signals executive-level priority. → Cross-reference the SEC filing's Risk Factors and Strategy sections with hiring patterns. Where are they investing against a stated risk? Where did they flag a risk but have zero hiring to address it? → Predict 3 product launches or strategic moves this company will make in the next 6-12 months. State your confidence level and cite specific job titles and filing sections as evidence. Format this as a 1-page competitive intelligence briefing for a CMO." What you'll find: → Products that don't exist yet but will in 6 months. → Priorities that contradict what the CEO said. → Risks they told the SEC but aren't addressing. This is what consulting firms charge $200K for. It took me 10 minutes. I used the new Claude 'Opus 4.6' for a reason: ✦ It read 60 job listing & a 200-page filing together.  ✦ And connects dots across both. ✦ It is superior in thinking and context retrieval. That's why I didn't use ChatGPT for this.

Australia has quietly built the most cost-effective rooftop solar industry in the developed world – and it shows. Australia consistently has the highest per capita adoption rate globally, with over one third of all households now having rooftop solar, totalling more than four million installations. In South Australia more than half of all homes have rooftop solar. And it's easy to see why: ✅ Abundant sunshine ✅ Large detached homes with plenty of roof space ✅ Relatively high retail rates In many cases these give a payback time of just 4–5 years. On top of that, many Australians like the idea of being more independent from their energy retailer. But none of this explains why Australia installs rooftop solar for a fraction of the cost seen in other advanced economies. What really makes Australia unique is the system behind it: ➡️ A highly competitive installer market ➡️ Fast, simple permitting and interconnection ➡️ Very low customer-acquisition and overhead costs Installations are often completed within a week of quoting, with the work itself usually done in a day or two. The panels are the same everywhere. The difference is the process. In the United States, the panels aren’t the problem — the process is. Permitting can take weeks or months, sales and marketing costs are high, state-level rules add complexity, and tariffs and paperwork drive up costs. The result: a typical system can cost five to seven times more. Permit Power estimates that if US rooftop solar prices matched countries like Australia or Germany, nearly 20 million more households would install it — saving around US$31,000 over a system’s lifespan. Australia now has so much solar that the government is exploring giving everyone three hours of free electricity a day to help soak up the excess. Clean energy gets cheaper when the system gets smarter — and Australia is showing what’s possible. #energy #renewables #energytransition

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

People sometimes see Acumen raising large amounts of commercial capital and assume we no longer need philanthropy. No sooner had we announced $250M for our Hardest-to-Reach fund — to bring off-grid light and electricity to 70 million people across 17 of Africa’s most challenging markets — than some concluded Acumen must be set. In fact, the opposite is true. First, let me acknowledge how tough this fundraising environment is. I couldn’t be prouder of the team and partners who made our Hardest-to-Reach announcement possible after 2.5 years of relentless effort. And yet it’s worth underscoring: none of this would have been possible without philanthropy. Philanthropy is the first mover. It allows us to place early bets in fragile markets like Malawi and Benin, cover the development costs needed to structure and raise investment across the capital spectrum and provide the technical assistance that builds capacity. To put a finer point on it: of the nearly $250M raised for Hardest-to-Reach, more than $80M is philanthropic. That risk-taking anchor made it possible to prove new models — and ultimately unlock institutional investment. During Climate Week last month, I met philanthropists who see this as the time to pivot from grantmaking toward impact investing. While I understand the instinct, I want to offer a reframing: it’s not either/or. If you want your capital to have lasting impact, there may be no better use than catalytic philanthropy — especially when deployed through blended finance models like Hardest-to-Reach. Philanthropy cannot see itself at the margins. It is catalytic capital — risk-taking, patient, and unabashedly impact-first — creating the conditions for commercial capital to follow. And it's more important now than ever as traditional aid shrinks and many governments shift from grants to investment approaches. At Acumen, philanthropy from donors at all levels remains our bedrock. It enables us to reach the hardest-to-reach, build inclusive markets where none exist, and keep social impact at the center of everything we do. And because solving problems of poverty is Acumen’s mission, raising philanthropic capital will remain essential to our work.

Last week, China barred its major tech companies from buying Nvidia chips. This move received only modest attention in the media, but has implications beyond what’s widely appreciated. Specifically, it signals that China has progressed sufficiently in semiconductors to break away from dependence on advanced chips designed in the U.S., the vast majority of which are manufactured in Taiwan. It also highlights the U.S. vulnerability to possible disruptions in Taiwan at a moment when China is becoming less vulnerable. After the U.S. started restricting AI chip sales to China, China dramatically ramped up its semiconductor research and investment to move toward self-sufficiency. These efforts are starting to bear fruit, and China’s willingness to cut off Nvidia is a strong sign of its faith in its domestic capabilities. For example, the new DeepSeek-R1-Safe model was trained on 1000 Huawei Ascend chips. While individual Ascend chips are significantly less powerful than individual Nvidia or AMD chips, Huawei’s system-level design to orchestrate how a much larger number of chips work together seems to be paying off. For example, Huawei’s CloudMatrix 384 system of 384 chips aims to compete with Nvidia’s GB200, which uses 72 higher-capability chips. Today, U.S. access to advanced semiconductors is heavily dependent on Taiwan’s TSMC, which manufactures the vast majority of advanced chips. Unfortunately, U.S. efforts to ramp up domestic semiconductor manufacturing have been slow. I am encouraged that one fab at the TSMC Arizona facility is operating, but issues of workforce training, culture, licensing and permitting, and the supply chain are still being addressed, and there is still a long road ahead for the U.S. facility to be a viable substitute for Taiwan manufacturing. If China gains independence from Taiwan manufacturing significantly faster than the U.S., this would leave the U.S. much more vulnerable to possible disruptions in Taiwan, whether through natural disasters or man-made events. If manufacturing in Taiwan is disrupted for any reason and Chinese companies end up accounting for a large fraction of global semiconductor manufacturing capabilities, that would also help China gain tremendous geopolitical influence. Despite occasional moments of heightened tensions and large-scale military exercises, Taiwan has been mostly peaceful since the 1960s. This peace has helped the people of Taiwan to prosper and allowed AI to make tremendous advances, built on top of chips made by TSMC. I hope we will find a path to maintaining peace for many decades more. But hope is not a plan. In addition to working to ensure peace, practical work lies ahead to multi-source, build more fabs in more nations, and enhance the resilience of the semiconductor supply chain. Dependence on any single manufacturer invites shortages, price spikes, and stalled innovation the moment something goes sideways. [Original text: https://lnkd.in/gxR48TK8 ]

The disconnect between sales managers and reps in 2025 is wild. Manager: "Just pick up the phone!" Rep: *sends 47 emails, 12 texts, 3 LinkedIn messages, and a carrier pigeon* Sound familiar? 😅 After 20+ years in sales, I've watched this communication gap grow wider every year. But here's what both sides are missing: It's not about choosing ONE channel. It's about understanding WHICH channel works WHEN. The most successful reps I've seen? They've cracked the code: **First 24 hours:** • Email → Sets professional tone • LinkedIn → Shows you've done homework • Text → Only if they've given permission **Days 2-5:** • Phone call → NOW it's time (they know who you are) • Voice note → Personal touch that stands out • Video message → Shows real effort **The truth?** Your manager's right - calls DO convert better. You're also right - cold calling blind is dead. The magic happens when you warm them up FIRST. Think of it like dating: You wouldn't propose on the first date. So why are we calling strangers without context? **My top 3 strategies that actually work:** 1. The "Permission Play" End every email with: "Would a quick call tomorrow at 2pm work to discuss?" (They expect it now = higher answer rate) 2. The "Multi-Touch Warm-Up" Email → LinkedIn view → Call within 48 hours (They recognize your name = 3x more likely to answer) 3. The "Context Creator" Reference their LinkedIn post before calling "Saw your post about X, had a thought..." (You're not a stranger = conversation not pitch) Here's the brutal truth: Managers: Your reps aren't lazy. They're adapting to how buyers ACTUALLY buy in 2025. Reps: Your manager isn't wrong. The phone still closes more deals than any other channel. Bridge the gap. Use both. Win more. What's your take - Team Phone or Team Omnichannel? P.S I'm running a FREE 6-week LinkedIn Social Selling Bootcamp starting Monday 15th Sept, grab a free spot here https://lnkd.in/eVmxsMbM

I often come across resumes and LinkedIn headlines that use the word “seasoned”, such as: “Seasoned executive with over 20 years of experience in the manufacturing space.” On the surface, it might sound strong. In reality, it raises several concerns. First, this statement is not a clear differentiator. Experience alone does not make someone unique. What matters most is how that experience has been applied, what has been learned, and the results achieved. Next, the term seasoned is vague. It does not communicate specific skills, achievements, or expertise. It has also become an overused cliché in resumes, which makes it less impactful. Finally, trust me when I say that employers and recruiters are not searching for the word seasoned when evaluating candidates. They are scanning for evidence of capability, examples of impact, and quantifiable results. Instead of describing yourself as seasoned, show the details that prove your value. For example: Rather than “seasoned operations director,” consider: “Director of operations who drives operational excellence across global manufacturing organizations, overseeing multi-site production valued at $500M+. Generated over $75M in efficiency gains." That paints a far stronger picture of what you bring to the table. Lastly, there is a risk that the word seasoned can invite age bias. Whether intentional or not, highlighting age or lengthy years of experience can trigger assumptions. Eliminating terms that are vague or loaded can help reduce this risk. In your career materials, focus on what sets you apart. Share the skills, insights, and measurable outcomes that showcase why you are the right fit. Food can be seasoned. Careers should be defined by value.

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

A promising Indian health-tech startup I invested in just shut down. Hard lessons inside… I invested in Onco back in 2020. It was basically an aggregator for cancer hospitals. Patients could visit their website or app, see all the hospitals and treatment options, get online consultations with doctors, and then choose where they wanted to get treated. They raised over $7 million from top investors like Accel, Chiratae, and others. They also built a strong brand. At their peak, they had 25,000+ visitors and over 1000 unique leads (cancer patients) every month - all organic, across their website, app, and social channels. We really thought hospitals would see the value in owning or partnering with a brand like this. But it didn’t work out that way. I’m sharing some lessons I learned watching this journey. Might be useful for founders (and investors) trying to crack India’s healthcare market: 1. Hospitals in India hold all the power. If you’re trying to aggregate them, you’re basically at their mercy. They will delay payments, ignore contracts, and squeeze every bit of margin out of you. They don’t really need you. Your margins get eaten alive by collections and compliance costs. 2. Digital only healthcare sounds great in pitch decks, but it doesn’t work here yet. People don’t pay enough for online-only services. Digital is great for leads, but it can’t be your whole business. Unit economics just don’t work with digital-only solutions because of low ARPU. 3. Offline is necessary. And brutally capital-intensive. Healthcare in India is still very much offline. Patients want to see a real centre and talk to doctors in person. Building those offline centres isn’t cheap. Each one takes at least 12–24 months to break even. You need serious money upfront. If you can’t fund that, you’re stuck. So, if you are building an aggregator only business in Indian healthcare, think twice. If you don’t have strong answers for these challenges, you’re just setting yourself up to be a middleman with no leverage, no margins, and no way out. That’s business suicide. #HarshRealities

McKinsey & Company 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 𝗳𝗼𝗿 𝗵𝗼𝘄 𝗯𝗮𝗻𝗸𝘀 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗿𝗲𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝗳𝗿𝗼𝗺 𝗔𝗜: ⬇️ This is a full-stack, enterprise-grade architecture — built on agents, orchestration, and rewired workflows. The AI bank stack consists out of 4 key layers: ⬇️ 𝟭. 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗟𝗮𝘆𝗲𝗿 This is the user layer — customers and employees. McKinsey calls for fully reimagined, intelligent, personalized experiences across all channels. → Multimodal chat (text, voice, image) → Omnichannel UX across mobile, contact center, branch → Digital twins for customer simulation and workforce training It’s all about a UI refresh and UX overhaul grounded in real AI. 𝟮. 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 This is the brain of the AI-first bank. And it’s not just predictive models anymore — it’s orchestrated agent ecosystems. → AI Orchestrators: Plan, reason, delegate across workflows → Domain Agents: Specialize in credit policy, fraud, risk, legal → Copilots: Embedded in workflows to guide users and automate decisions McKinsey reports 20–60% productivity gains in decision-making with this approach. 𝟯. 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵 & 𝗗𝗮𝘁𝗮 The foundation layer most banks underestimate — until GenAI models stall in production. → Vector databases → LLM orchestration and FinOps → Search and retrieval engines → ML pipelines → Secure data architecture → API infrastructure The goal: make data accessible, tools reusable, and infra invisible to the business. Without this, nothing scales. 𝟰. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 This is where the transformation wins or fails. Without rewiring the org, the tech doesn’t matter. → AI control towers to track value and set guardrails → Cross-functional teams across business, tech, and AI → Platform operating model for speed and alignment → Enterprise-wide reuse of AI capabilities If you're building isolated projects without shared assets or central coordination, you’re not transforming — you’re experimenting. 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗮𝗹𝗹 𝗮𝗱𝗱𝘀 𝘂𝗽 𝘁𝗼? The banks that win won’t be the ones with the most pilots. They’ll be the ones that industrialize agents, orchestration, and rewired workflows, with full-stack coordination. Full McKinsey article: https://lnkd.in/dPaJzVK4 𝗜 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 — 𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 𝗵𝗲𝗿𝗲 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲: https://lnkd.in/dbf74Y9E