Business Strategy

The meltdown of Situational Awareness, a hedge fund run by Leo Aschenbrenner, a 25-year old wunderkind with an AI pedigree was almost as staggering as the run-up in the fund in the year before. While many have drawn lessons from the fund's collapse, I use it to talk about investment conviction, words that are used almost always in a positive way in investing circles. I look at investment conviction in a continuum (from absolute conviction to confused mush), why conviction can vary across investments and investors and what it leads to in investment actions (concentration & leverage). I end the article by talking about the three lessons I take away from Leo - that investment actions that are not in sync with investment conviction are disastrous, that momentum is a wildcard that can elevate and shred strategies and that humble money should be trusted more than smart money.

AI tools can make iteration much faster. But production still needs the boring layers: auth, storage, deployment, security, scaling, monitoring, and recovery. A short checklist to pressure-test an AI-built product before calling it production-ready: 1. Data access * Who can see what data? * Are permissions enforced at the data or query level, not just in the UI? 2. State and storage * Where does the data live? * What happens when users refresh, retry, upload, delete, or edit the same record? 3. Failure handling * What breaks when the API is slow, the model times out, or traffic spikes? * Is there fallback logic, retry logic, or graceful failure? 4. Observability * When something goes wrong, can the team see what happened? Logs, traces, errors, user actions, and model inputs / outputs where appropriate. 5. Recovery * Can you recover without guessing? Rollback, restore data, redeploy safely, and understand what changed. The demo milestone is: it works once. The production milestone is: it keeps working with real users, real data, and real failures. And if you are building with AI, this upcoming course may be worth checking out: Build an AI-powered content and monetization engine 🔗https://lnkd.in/gpRFwD3G

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

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.

Same industry. Completely different economics. And that is exactly why this image matters. At first glance, it looks like a staffing comparison. It is not. It is a strategy comparison. Emirates is built around premium service, widebody operations, and a high-touch customer experience. Ryanair is built around simplicity, speed, standardization, and relentless cost discipline. Both win. That is the part I think many leaders still underestimate. Efficiency is not about having fewer people. It is about building a system where everything matches: → cost structure → customer promise → operating model → pricing power What I keep seeing across industries is this: companies rarely fail because they chose the “wrong” model. They fail because they copy someone else’s model without copying the logic that makes it work. That is where things break. Emirates and Ryanair are both operationally strong. They just optimize for different outcomes. To me, that is the real lesson here. You do not need the same model to win. You need a coherent one. Because the moment your pricing, service promise, and operating reality stop aligning, the whole business starts fighting itself. If you copied one of these models into your company tomorrow, would it create efficiency, or chaos? #BusinessStrategy #Leadership #Operations #Airlines #Efficiency #Innovation #Scaling #FutureOfWork #Management

A 16-year-old Black girl from South Africa may have invented the most important women’s safety device in decades. She built it from her school in Limpopo. 🇿🇦 Bohlale Mphahlele grew up in a country where over 120,000 violent crimes against women and children are reported every single year. Where one in three women will experience physical violence in her lifetime. Where the numbers are so staggering they’ve almost become background noise. Most people scroll past. Bohlale built something. The Alerting Earpiece looks like jewellery. Just a simple, stylish earring. Hidden inside is a micro camera, a GPS tracker, and a silent panic system. One discreet press of a button and it captures photos of the attacker, locks the victim’s live location, and sends alerts to trusted contacts and police simultaneously. No sound. No attention drawn. Just quiet, immediate action in a moment where every second matters. She was a Grade 11 student at SJ van der Merwe Technical High School when she unveiled the prototype at the Eskom Expo for Young Scientists. She won a bronze medal. The Limpopo Education MEC called her a “role model and change-maker.” Her invention was formally recognised in South Africa’s National Assembly. She could have stopped there. The accolades would have been enough for most people. She didn’t stop. ✨ Five years later, Bohlale is now 21 years old, studying Information Technology, and running her own company, Mphahlele Alerts (Pty) Ltd. She’s actively seeking investors and manufacturing partners to bring the device to market at scale. Her goal is to get it into the hands of schoolgirls walking home alone, women working night shifts, and those trapped in abusive homes. “Safety shouldn’t be a privilege,” she says. This young woman looked at one of the most devastating crises in her country and refused to wait for someone else to fix it. She didn’t have millions in funding. She didn’t have powerful connections. She had an idea, the discipline to build it, and the audacity to believe a teenager from Limpopo could change how we protect vulnerable people. This is what innovation looks like when it’s rooted in empathy. This is what happens when young Black women are given space to create solutions for problems they actually understand. Bohlale Mphahlele. Remember her name. 🤎 AA🌼 We bloom together or we wilt alone™️🌱 ———————————————————— 👀 Read more : Substack link in the comments

The latest reporting from the Financial Times highlights a point that energy analysts have been making for years: geopolitical shocks consistently strengthen the case for renewables, electrification and storage. Microsoft’s global vice-president for energy notes that oil and gas price spikes linked to the Middle East conflict reinforce the value of wind, solar and batteries in providing price stability. Once installed, renewables offer predictable cost profiles and reduce exposure to volatile global fuel markets. We saw this dynamic after Russia’s invasion of Ukraine. Europe accelerated solar deployment, heat pump uptake increased in several countries, and governments revisited questions of energy security through the lens of diversification and electrification. The underlying issue remains unchanged. Fossil fuels must continuously flow through complex global supply chains. When those flows are disrupted, prices spike and economies are exposed. Renewables, by contrast, are capital intensive upfront but deliver long term domestic supply and insulation from commodity shocks. There are short term risks. Inflation, higher interest rates and supply chain constraints can slow clean energy investment. Some governments may also respond by doubling down on gas infrastructure. The policy challenge is to avoid locking in further structural vulnerability. Energy security and climate policy are not competing objectives. In a world of recurrent geopolitical instability, they are increasingly aligned.

During my time serving in government, I saw firsthand how geopolitics can impact energy production and flows, with cascading impacts on market and macroeconomic trends.   We're already seeing this play out following the last few days in the Middle East. U.S. and Israeli strikes on Iran triggered retaliatory action across the region that has disrupted energy production and transit.   The market reaction is changing quickly. Since I recorded this video on Monday, oil and gas prices have jumped further, and equities have shifted toward a risk-off move as investors price in continued escalation. Bonds sold off further, reflecting inflation fears in developed markets. Due to the segmented nature of natural gas markets, the impact of higher prices will hit regions differently, with Europe more exposed than the U.S. to elevated LNG prices.   The central question: will this remain a short-term volatility spike or evolve into a broader supply shock? The duration of the disruption and the severity of transit impacts are the core variables I'm watching.   ⬇️ Watch the full video for my latest take on what this could mean for markets.

Over the last few years, SEBI has quietly but meaningfully expanded what asset managers in India can do. Debt passive regulations. Specialised Investment Funds. And now, Life Cycle Funds. These aren’t incremental tweaks. They expand the solution architecture available to investors. And for those of us building in this industry, it is incredibly exciting. The introduction of Life Cycle Funds under the new scheme categorisation framework is a big moment for goal-based investing in India. For years, we’ve told investors to align asset allocation to time horizon. Now, the structure does it for them. As the goal approaches, the portfolio gradually shifts from equity to lower-risk assets. It reduces behaviour risk. It reduces timing errors. And it keeps investors focused on the goal, not the noise or news. All within a tax-efficient mutual fund structure. Simple idea. Powerful execution. Very relevant for long-term India. From products to solutions, an evolution I am super excited about.

Public software is down 40% in 12 months. The selloff has been indiscriminate. Companies hitting their revenue targets are getting hammered alongside the ones that deserve it. The market isn't distinguishing between well-positioned and poorly-positioned software companies.   That will change. When it does, the companies left standing will be the ones with moats that matter in a world where agents do more of the work.   The Emergence partnership spent yesterday debating a question I think every founder and investor should be asking (and, judging by my LinkedIn feed, it seems they are...):   Which software moats actually survive in an AI era?   Here's the spectrum we landed on (from least to most defensible):   1. Workflow   Pre-Claude, getting humans to do their jobs inside your software was a powerful moat. But if agents are doing the work, who cares about the human workflow? Cursor vs Claude Code is the canary in the coal mine: one owns the workflow, the other just executes—and developers are increasingly choosing execution over process.   2. Integrations   MCPs are rapidly commoditizing the glue between systems. Being the connector used to be a moat. Soon, it'll be a utility.   3. Data repository   Static repositories are table stakes. Owning customer data matters less than understanding what to do with it.   4. System of action   Now we're getting somewhere. If your software touches money, customers, or real-world outcomes (think Gusto or Shopify), ripping it out is genuinely painful.   5. Full context   The most important new moat in AI. Understanding how a full task gets done across systems, knowing what a user needs across many different sources. This is what agents need to be useful, and the companies that own it become indispensable infrastructure. But it's young and unproven. If context becomes portable (the way integrations are being commoditized now), this moat could erode too.   6. Brand   The moat that survives every platform shift. Trust compounds over time and can't be replicated by a new entrant with better tech. When everything else gets commoditized, the vendor you trust still wins.   7. Network effects   The most underappreciated moat in AI, and potentially the most enduring. But not all network effects are equal. Workflow-based ones (more humans in the tool) are vulnerable. Data and trust-based ones (every user makes the product smarter) actually accelerate with agents. LinkedIn, Doximity, and Slack all still have this. Relatively few AI native companies have prioritized it...yet.   --   The bottom line: Seat-based pricing and workflow stickiness were the backbone of the last era. Both are eroding. The next era rewards companies tied to outcomes, context, and trust.   If you're a founder, stress-test your moats against this spectrum. If your primary defense is "our users do their jobs in our software," you have work to do.   Because the world is moving towards selling outcomes, not software.