Innovation in Business Strategy

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.

Innovation isn’t just about new products. It’s about how you structure, deliver, and capture value—across your entire business model. In their book, "Ten Types of Innovation" (2013), Keeley et al. outline a powerful framework outlining no less then 10 types of innovation: Configuration 1. Profit Model – How you make money 2. Network – How you collaborate 3. Structure – How you organize 4. Process – How you operate Offering 5. Product Performance – What you offer 6. Product System – How offerings work together Experience 7. Service – How you support users 8. Channel – How you deliver value 9. Brand – How you're perceived 10. Customer Engagement – How you foster loyalty Most innovation efforts focus narrowly on the product. But real advantage comes from orchestrating multiple innovation types, often in combination. If you're looking for new strategic levers, this framework is a great place to start. Which of the ten are you already investing in?

In The Economist’s latest feature, I share insights on how Zero Trust + AI is redefining the future of cybersecurity. The article explores why organizations must move beyond legacy security models and adopt an architecture fit for the purpose of defending people, data, and operations in a digital-first world. This means: - Eliminating attack surfaces in real time - Enhancing data security with AI-driven analytics - Boosting productivity without compromising user experience The insights shared reinforce a core belief we hold at Zscaler: Innovation in security protects businesses and enables them to thrive by driving agility, scalability, and growth. ✅ No perimeter. No implicit trust. Zero Trust isn't just a framework—it's a necessity for a secure, resilient, AI future. I encourage you to explore the article and join the conversation around shaping the next era of cybersecurity. https://lnkd.in/dcqwxCgQ #ZeroTrustEverywhere #Cybersecurity #Innovation

Should you try Google’s famous “20% time” experiment to encourage innovation? We tried this at Duolingo years ago. It didn’t work. It wasn’t enough time for people to start meaningful projects, and very few people took advantage of it because the framework was pretty vague. I knew there had to be other ways to drive innovation at the company. So, here are 3 other initiatives we’ve tried, what we’ve learned from each, and what we're going to try next. 💡 Innovation Awards: Annual recognition for those who move the needle with boundary-pushing projects. The upside: These awards make our commitment to innovation clear, and offer a well-deserved incentive to those who have done remarkable work. The downside: It’s given to individuals, but we want to incentivize team work. What’s more, it’s not necessarily a framework for coming up with the next big thing. 💻 Hackathon: This is a good framework, and lots of companies do it. Everyone (not just engineers) can take two days to collaborate on and present anything that excites them, as long as it advances our mission or addresses a key business need. The upside: Some of our biggest features grew out of hackathon projects, from the Duolingo English Test (born at our first hackathon in 2013) to our avatar builder. The downside: Other than the time/resource constraint, projects rarely align with our current priorities. The ones that take off hit the elusive combo of right time + a problem that no other team could tackle. 💥 Special Projects: Knowing that ideal equation, we started a new program for fostering innovation, playfully dubbed DARPA (Duolingo Advanced Research Project Agency). The idea: anyone can pitch an idea at any time. If they get consensus on it and if it’s not in the purview of another team, a cross-functional group is formed to bring the project to fruition. The most creative work tends to happen when a problem is not in the clear purview of a particular team; this program creates a path for bringing these kinds of interdisciplinary ideas to life. Our Duo and Lily mascot suits (featured often on our social accounts) came from this, as did our Duo plushie and the merch store. (And if this photo doesn't show why we needed to innovate for new suits, I don't know what will!) The biggest challenge: figuring out how to transition ownership of a successful project after the strike team’s work is done. 👀 What’s next? We’re working on a program that proactively identifies big picture, unassigned problems that we haven’t figured out yet and then incentivizes people to create proposals for solving them. How that will work is still to be determined, but we know there is a lot of fertile ground for it to take root. How does your company create an environment of creativity that encourages true innovation? I'm interested to hear what's worked for you, so please feel free to share in the comments! #duolingo #innovation #hackathon #creativity #bigideas

The next wave of marketing innovation isn’t about automation alone — it’s about emotion. Which shoe would you get? AI today can recognize tone, facial expressions, and even micro-emotions in voice and text. This emotional intelligence is turning marketing from mass communication into personal connection. 🧠 Data speaks for itself: + 80% of consumers say they’re more likely to purchase when brands show they understand their emotions. (Capgemini Research) + Emotionally connected customers have a 306% higher lifetime value than those who are merely satisfied. (Motista) + 70% of marketers using AI-driven personalization report double-digit engagement growth. (Salesforce) 💡 Real-world examples: + Coca-Cola uses AI-powered creative tools to adapt campaigns to local culture and sentiment in real time. + Netflix’s recommendation engine reads emotional cues in viewing behavior to tailor what feels just right for each user. + Adidas combines AI sentiment analysis with influencer content to sense trends before they peak — turning feelings into foresight. This isn’t marketing as usual — it’s marketing that feels. When technology understands emotion, brand experience becomes unforgettable. #AI #MarketingInnovation #EmotionalIntelligence #CustomerExperience #DigitalTransformation #MarTech #BrandStrategy

CFO to General Counsel last week: "I read that AI can review contracts now. Why do we still need three legal FTEs?" GC's internal monologue: "Because AI can't negotiate with an angry customer at 9 AM, navigate a GDPR audit at 11 AM, and explain to the board why that 'simple contract' could expose us to €2M liability at 3 PM?" Welcome to 2025, where every General Counsel is expected to: ✅ Implement AI to "cut costs" ✅ Reduce legal headcount ✅ Still deliver faster contract turnarounds ✅ Maintain zero risk tolerance ✅ Be a strategic business partner All by yesterday. Preferably with no budget. Here's what leadership sees: --> AI reviews 100 contracts in minutes! Here's what they miss: --> Who reviews the AI's output? --> Who handles the 15 edge cases it can't process? --> Who negotiates when the customer pushes back? --> Who coordinates with Sales, Finance, and IT? --> Who makes the final call on acceptable risk? The pressure is real. CFOs read one article about "AI replacing lawyers" and suddenly expect the legal department to automate itself out of existence. But here's the truth: AI is powerful for legal teams - when used right. The goal isn't to replace lawyers. It's to free them from the repetitive work that buries them: → Initial contract reviews and risk flagging → Answering the same compliance questions repeatedly → Tracking obligations and renewals → Generating routine agreements That gives your team capacity for what actually matters: strategic negotiation, risk assessment, business partnership, and preventing the fires nobody sees. Smart legal leaders aren't asking "How do I replace my team with AI?" They're asking "How do I use AI to make my team 10x more effective?" How is your leadership team thinking about AI in legal right now?

Account-based GTM is having a big resurgence. It used to be reserved for the highest value accounts ($100k+ deals) -- frankly it was too manual & too expensive to scale beyond that. As account data becomes a commodity -- and as AI tools help automate deep account research -- we can bring our entire target market into our CRM & tailor all our pipeline efforts on the best-fit accounts. Here's the thing: pivoting to ABM is still brutal. There are no real playbooks. And there's a painful lack of tactical resources. Emilia Korczynska, VP of marketing at Userpilot, had to learn the hard way ("ABM or die trying..."). Today she shared the tactical guide she wished someone gave her *before* she started. Read it in Growth Unhinged: https://lnkd.in/eHY8Ss5t Spoiler: it worked. Emilia's team generated >$650k in pipe in 90 days with $12 in pipe per $ spent. And now they're doubling down. Here's the TL;DR - your ABM checklist: 1. Define your ABM goals & leading metrics. 2. Pick a level of personalization (1:1, 1:few, 1:many). 3. Set up campaigns: account stages, account scoring. 4. Decide on a duration: how long campaigns will last. 5. Select channels to reach your target audience (Emilia started with LinkedIn). 6. Build your list of targets: accounts, personas, etc. 7. Prepare the content, messaging, ad formats, etc. (Make sure to define a hand-off point with BDRs). 8. Approve the budget & resources. 9. Set up dashboards to track campaign performance. 10. Onboard tools/vendors for each element of ABM. As a side note, Emilia chose an 'unbundled' ABM tech stack with 8 tools, costing ~$2.5k per month. The choices: - For list building: HubSpot (CRM), Clay, BuiltWith, Apollo.io - For campaign assets: Notion - For intent recognition & account scoring: ZenABM/Fibbler - For ad campaign mgmt, lead flows, reporting, sales outreach: HubSpot (Marketing) - For prospecting: Salesloft Hope this guide makes ABM a little less of a nightmare 🙏 #abm #marketing #gtm #saas

Strategic Flexibility: LG’s Playbook in the Age of Uncertainty #3. Geoeconomics: The Precision Calibrator for Strategic Impact For some time now, we’ve been reshaping our portfolio by expanding business domains and transforming business models. Beyond home appliances, we’ve grown into B2B solutions such as mobility, smart factories, and HVAC. At the same time, we’ve moved from hardware-centric businesses to subscription services, D2C, and platform-based models. As of Q2 2025, B2B represents 37% of total revenue, while non-hardware platform sales grew 18% year-on-year. But today, the world asks a new question: “Where, when, and how should opportunities be seized?” As AI innovation and geoeconomic shifts unfold together, LG Electronics’s strategy has become three-dimensional: business expansion as the X-axis, new models as the Y-axis, and geoeconomics as the Z-axis. If AI creates opportunities, geoeconomics acts as the calibrator—defining their scale, direction, and impact. Global South: The New Stage of Growth The Global South is no longer just “emerging”—it’s becoming a central driver of growth. Across leading countries in this region, LG is laying the groundwork for the future with expanded R&D, production capacity, and locally tailored strategies. • LG India: USD 600M investment in a third plant with 5M-unit capacity; stronger R&D through LG Soft India and our Noida lab; 2024 revenue of KRW 3.79T and net profit of KRW 331.8B*; IPO preparation underway. • LG Electronics Indonesia: New Cibitung R&D base for our Media Entertainment Solution Company; reinforcing production hub role; expanding AI data center HVAC contracts. • LG Electronics Brasil: Manaus plant operating 30 years as a regional hub; BRL 2B investment in a Paraná plant by 2026 to localize premium appliances. • LG Electronics Saudi Arabia: HVAC production hub; expanding AI data center partnerships; growing as a Middle East and Africa export base. Operational Agility Our Locally Self-Sufficient Model builds complete value chains within each market, enabling fast response and supply chain stability. In parallel, our Swing Production System links 35 sites across 16 countries—including the U.S., Mexico, Vietnam, Hungary, Saudi Arabia, Brazil, and India—into a flexible global network. Together, these models let us adjust production to tariff changes or geoeconomic challenges, ensuring stability and efficiency. This dual foundation enables LG to navigate uncertainty with resilience and agility. The environment will always bring new challenges. But our commitment is clear: understand markets, capture opportunities, and deliver solutions when and where they are needed. With strategic flexibility, we aim to turn challenges into growth and open new pathways for the future. * Source: LG Electronics 2024 Annual Report

I track a cohort of about 40 cannabis companies throughout the United States that are "working”. What I’ve noticed? The top companies are all doing the same thing in about 5 or different verticals. Here's the breakdown: 1. Private Not Public Most successful cannabis companies are private. They avoid the scrutiny and regulation of public markets. They maintain control and flexibility. In cannabis, being private is the way to go. 2. They Generate Revenue and Real Cash Flow All the successful companies are either generating real cash flow or are very close. Why? • They focus on profitability • They balance growth and cash flow Cash flow is the lifeblood of a company. These companies understand this. 3. They Limit Outside Capital These companies limit their reliance on outside capital. Instead they: • Use internal resources and profits • Avoid dilution of ownership Capital is a tool, not a crutch. 4. They Only Take Non-controlling and Non-punitive Capital If they take outside capital, it's always non-controlling and non-punitive. They: • Maintain control • Structure debt to be serviceable Smart capital doesn't control, it enables. 5. Profitability Over Capital Dependence They focus on lean operations They prioritize net profits And they’ve realized one crucial thing: Profitability is more important than high capital. 6. Excellence in One or Two Areas The top companies aren’t a jack of all trades. They excel in one or two things and stick to them. • They know their strengths • They focus their resources on what they do best They have dominated their niche. 7. Maintain Privacy These guys don’t disclose much. They keep their strategies and finances confidential. They control their narrative. In the cannabis industry, silence is golden. This is what I've seen the top companies do. Do with this info what you will. Want more content like this? Hit that follow and 🛎️ to get notified when I post.