Strategic Competitive Intelligence

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.

"Many militaries are expanding the scope and speed of incorporating more complex data-driven techniques into the processes of determining courses of action, including when it comes to the use of force. These developments raise questions about the changing roles played by humans and machines, or human-machine interaction, in warfare. "This report contributes to ongoing debates on AI DSS by reviewing main developments and discussions surrounding these systems and their reported uses. It takes stock of what is known about AI DSS in military decision-making on the use of force, including in ongoing war zones around the globe. Section 2 provides a brief overview of the roles that AI DSS can play in use-of-force decision-making. Section 3 reviews main developments that we treat as indicative of trends in AI DSS in the military domain." "It focuses on three concrete empirical cases, namely the United States (US)’ Project Maven initiative, as well as systems reportedly used in the Russia-Ukraine war (2022-) and the Israel-Hamas war (2023-). Section 4 discusses opportunities and challenges associated with these developments, drawing inspiration from ongoing debates in the media and expert communities. The report concludes with some recommendations on potential ways forward to address the challenges discussed and with some questions raised by AI DSS that deserve further attention in the global debate on AI in the military domain." From Anna Nadibaidze Dr Ingvild Bode Qiaochu Zhang Center for War Studies, University of Southern Denmark

🍱 How To Design Effective Dashboard UX (+ Figma Kits). With practical techniques to drive accurate decisions with the right data. 🤔 Business decisions need reliable insights to support them. ✅ Good dashboards deliver relevant and unbiased insights. ✅ They require clean, well-organized, well-formatted data. ✅ Often packed in a tight grid, with little whitespace (if any). 🚫 Scrolling is inefficient in dashboards: makes comparing hard. ✅ Start with the audience and decisions they need to make. ✅ Study where, when and how the dashboard will be used. ✅ Study what metrics/data would support user’s decisions. ✅ Explore how to aggregate, organize and filter this data. ✅ More data → more filters/views, less data → single values. 🚫 Simpler ≠ better: match user expertise when choosing charts. ✅ Prioritize metrics: key insights → top left, rest → bottom right. ✅ Then set layout density: open, table, grouped or schematic. ✅ Add customizable presets, layouts, views + guides, videos. ✅ Next, sketch dashboards on paper, get feedback, iterate. When designing dashboards, the most damaging thing we can do is to oversimplify a complex domain, or mislead the audience. Our data must be complete and unbiased, our insights accurate and up-to-date, and our UI must match users’ varying levels of data literacy. Dashboard value is measured by useful actions it prompts. So invest most of the design time scrutinizing metrics needed to drive relevant insights. Bring data owners and developers early in the process. You will need their support to find sources, but also clean, verify, aggregate, organize and filter data. Good questions to ask: 🧭 What decisions do you want to be more informed on? (Purpose) 😤 What’s the hardest thing about these decisions? (Frustrations) 📊 Describe how you are making these decisions? (Sources) 🗃️ What data helps you make these decisions? (Metrics) 🧠 How much detail is needed for each metric? (Data literacy) 🚀 How often will you be using this dashboard? (Value) 🎲 What constraints should we know about? (Risks) And, most importantly, test dashboards repeatedly with actual users. Choose key tasks and see how successful users are. It won’t be right at first, but once you get beyond 80% success rate, your users might never leave your dashboard again. ✤ Dashboard Patterns + Figma Kits: Data Dashboards UX: https://lnkd.in/eticxU-N 👍 dYdX: https://lnkd.in/eUBScaHp 👍 Ethr: https://lnkd.in/eSTzcN7V Orange: https://lnkd.in/ewBJZcgC 👍 Semrush: https://lnkd.in/dUgWtwnu 👍 UKO: https://lnkd.in/eNFv2p_a 👍 Wireframing Kit: https://lnkd.in/esqRdDyi 👍 [continues in comments ↓]

This year, India’s defense sector unveiled advancements in AI that are reshaping military strategies & boosting national security. Here’s what the data tells us: --> AI is now central to defense modernization. --> Collaboration across sectors is driving innovation. Let’s explore these in detail. 1️⃣ AI-Powered Technologies Transforming Defense India’s armed forces are deploying AI across critical areas: ➤ Autonomy in operations: AI-enabled systems like swarm drones & autonomous intercept boats enhance mission precision, reduce human risk, & improve tactical outcomes. ➤ Intelligence, Surveillance, & Reconnaissance (ISR): AI-based motion detection & target identification systems provide real-time alerts for better situational awareness along borders. ➤ Advanced robotics: Silent Sentry, a 3D-printed AI rail-mounted robot, supports automated perimeter security & intrusion detection. Example: Swarm drones use distributed AI algorithms for dynamic collision avoidance, target identification, & coordinated aerial maneuvers, providing versatility in both offensive & defensive tasks. 2️⃣ Collaboration as the Catalyst for Innovation India’s AI advancements are the result of partnerships between the government, private industries, & research institutions. ➤ Indigenous solutions: 100% indigenously developed systems like the Sapper Scout UGV for mine detection. ➤ Startups and SMEs: Innovative contributions from tech firms and startups have fueled projects like AI-enabled predictive maintenance for naval ships and drones. ➤ Global export potential: Systems like Project Drone Feed Analysis and maritime anomaly detection tools are export-ready, positioning India as a major global defense tech player. 3️⃣ The Data-Driven Case for AI ➤ Efficiency: AI-driven systems exponentially improve surveillance coverage and reduce operational time. For example, the Drone Feed Analysis system decreases mission costs while expanding surveillance areas. ➤ Safety: Predictive AI systems in vehicles and maritime platforms enhance safety by identifying potential risks before failures occur. ➤ Economic impact: AI-powered predictive maintenance for critical assets like naval ships and aircraft maximizes uptime while minimizing costs. Real Impact ➤ Swarm drones: Affordable, scalable, and capable of BVLOS operations, offering precision in combat. ➤ AI-enabled maritime systems: Detect anomalies in vessel traffic, securing trade routes and protecting economic interests. ➤ AI-driven mine detection: Enhances soldier safety while automating high-risk tasks. What does this mean for defense organizations? AI isn’t just modernizing defense; it’s placing it firmly in the global defense innovation market. With bold policies, dedicated budgets, and a growing ecosystem of public and private sector players, this will help lead the next wave of AI-driven defense technologies. But the question remains: How do we ensure these technologies are deployed ethically and responsibly? Agree?

After designing hundreds of business dashboards, I keep coming back to these four patterns: Tall + Scrolly Stack everything vertically, organized by metric family, and let people scroll to their level of depth. Best for mobile viewing and email delivery with basic chart types that doesn't require instructions. Where I've seen this work: New product/feature introductions where audiences are different levels (executive to operators) and functions. BANs + Decomp Big numbers that focus attention and breakdowns that show differences. For when you've identified the important metrics, but want to show segment granularity. Switch group-by dimension while maintaining familiar layout. Where I've seen this work: Operational monitoring for teams that have ownership of metric outcomes. Sankey + Wide Table Flow diagram establishes a map of the whole system and reference tables show details. For diagnosing conversion and retention patterns across nodes and segments to know where to optimize. Where I've seen this work: Growth teams figuring out behavior across complex funnels and overlapping segments. Potential Show what you could be delivering versus what you're actually delivering. Makes the gap between current performance and available capacity visible. Where I've seen this work: Operational teams that have a clear action to take, but limited time. What each of these have in common: - Establish big picture awareness, but direct small picture action (think global, act local) - Strengthened by KPI ownership - Act as a prioritization mechanism Organizations often start with one dashboard trying to serve everyone, then evolve into multiple dashboards with different patterns for different groups. The more established the business, the more discrete the problems being solved are. That means early on, you go from optic oriented communications to more optimization oriented direction. I've found that organizations lack a portfolio strategy for their analytics interfaces, they take templates from one context and try to apply them to another OR they try to combine use cases together into a singular dashboard because they only have budget for one but multiple stakeholders with different needs, so they get a flying-boat-car of compromises. Some data work and analytics are going to be a cost of doing business, like reporting that just keeps everyone informed. While other data work is a strategic bet. The challenge is that some analytics deliver hard value you can measure in dollars, while others provide soft value like better collaboration and shared understanding that's difficult to quantify. Most organizations don't think about this mix deliberately. #dataAnalytics

How to Use Earned Value Management (EVM) for Project Tracking and Execution :- _______________________________ Earned Value Management (EVM) is a powerful tool for project managers to monitor, assess, and control the progress of projects. It provides a clear picture of project performance and enables timely corrective actions, ensuring projects stay on track to meet objectives. 🎯 The Power of EVM :- EVM allows project managers to measure project performance by integrating three key metrics:- 1️⃣ Planned Value (PV) :- The budgeted cost for work scheduled. 2️⃣ Earned Value (EV) :- The value of the work actually performed. 3️⃣ Actual Cost (AC) :- The actual cost incurred for the work performed. ✅️ By comparing these metrics, project managers can calculate crucial indicators like :- 4️⃣ Cost Performance Index (CPI) :EV / AC. 5️⃣ Schedule Performance Index (SPI) : EV / PV. ✅️ These indices provide actionable insights :- ✔️- CPI > 1 indicates the project is under budget. ✔️- SPI > 1 indicates the project is ahead of schedule. 💡 Real Case Study :- For a mega infrastructure project in the Middle East, a leading construction firm applied EVM during its execution phase. Using EVM for performance tracking, the project manager identified early discrepancies between planned and actual progress, preventing potential cost overruns and delays. By identifying areas of improvement, they managed to increase project efficiency by (12%), ensuring the project completed on time and (5%) below budget. 📊 Key Statistics :- ✔️- (75%) of successful projects in the construction industry use EVM for project tracking and performance management. ✔️- (58%) of projects that do not use EVM tools report delays and budget overruns. 🔆 By adopting EVM early in the project lifecycle, companies can reduce risks and improve the likelihood of achieving both scope and financial goals. 🎯 Best Practice Tip :- ➡️ To fully harness the power of EVM, integrate it into your project management processes from the start, track progress regularly, and use it to make data-driven decisions to stay within scope, time, and cost constraints. 🚨 EVM isn't just about tracking performance – it's about transforming data into actionable insights for better project execution. --------------- ➡️ If you found this post useful, feel free to like 👍, comment 💬, or share ♻️ — and follow me for more insights on Projects and Contracts Management. #EmadRamadan. #IMPM.

The rapid rise of combat drones illustrates a classic pattern described by Clayton Christensen. Drones represent a 𝐥𝐨𝐰-𝐞𝐧𝐝 𝐝𝐢𝐬𝐫𝐮𝐩𝐭𝐢𝐯𝐞 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲: initially dismissed as inferior to established systems, yet capable of reshaping the entire competitive landscape. For decades, the Western defense industry focused on increasingly sophisticated missiles, precision bombs, and air-defense systems. These technologies became extremely advanced—and extremely expensive. In that environment, small and relatively crude drones seemed strategically irrelevant. Yet disruption often starts exactly there. Take the Iranian Shahed drones now widely used in conflicts. They are cheap, simple, and can be produced in large numbers. Their real power lies not in individual performance but in scale and swarm tactics. When launched in large waves, they overwhelm traditional air-defense systems designed to intercept a limited number of high-value missiles. Using million-dollar interceptors against drones costing a few tens of thousands of dollars is economically unsustainable. This is classic Christensen logic: incumbents optimize for high-end performance while the disruptive technology improves rapidly in a different dimension—in this case cost, scalability, and operational flexibility. But the real lesson is not only technological.Ukraine has shown that the decisive capability lies in how drones are used: agile combat strategies, distributed command structures, and operators who can adapt in real time. Human intelligence, battlefield learning, and tactical creativity matter as much as the hardware itself. It all has to go together. For Europe and the wider West, the implication is that defense strategies must shift from a narrow focus on expensive platforms toward learning systems that combine low-cost technology, rapid experimentation, and shared operational intelligence. And this knowledge already exists: Ukraine today is probably the world’s most advanced laboratory for drone warfare. Western militaries should accelerate collaboration and learning from that experience. The rise of low-cost drones and other low-end digitalized warfare technologies also forces a reconsideration of how military budgets are optimized. Rather than automatically increasing defense spending, the priority should be to reassess how military effectiveness can be maximized by reallocating resources—shifting a larger share of investment toward scalable, low-cost systems such as drones. #DisruptiveInnovation #Drones #MilitaryInnovation #DefenseStrategy #Ukraine #Security #ClayChristensen #DroneWarfare

Don't underestimate the power of old-school data analysis techniques. For example, my clients love RFM analysis: (R)ecency (F)requency (M)onetary Here's how RFM analysis works. (R)ecency is the time since a customer's last purchase. Customers in the top 10% of recent purchases receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a recency score from 0 to 9. (F)requency is the number of customer orders over some time (e.g., the last year). Customers in the top 10% of frequency receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a frequency score from 0 to 9. (M)onetary is the total lifetime purchases of your customers. Customers in the top 10% of lifetime purchases receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a monetary score from 0 to 9. Your absolute best customers will have a score of 999. The next tier will have scores of 998, 989, and 899. And so on. Here's the thing, though. You can customize the ideas behind RFM to fit your situation. Here's a real-life example. I performed a marketing analysis of US geographies. The goal was to find the optimal geographies for digital ads. I joined internal data with free data from the US Census Bureau. I then performed an RFM-style analysis of the data. I scored each geography with four characteristics. For example, the count of high-income households. The best geographies scored 9999. Using this analysis, I identified US geographies with opportunities for digital ads.

We stand at a pivotal moment of extraordinary potential. AI isn't just evolving; it's revolutionizing – and how businesses ride this wave will separate the innovators from the imitators. In my latest Forbes article, I explore three key trends shaping 2025 and beyond: Hybrid AI is taking over. → Organizations are embracing hybrid AI, combining public LLMs with private models to enhance security, agility, and cost-efficiency. This approach pairs the scalability of cloud services with the control of localized systems to safeguard sensitive data. Innovation is accelerating at an unparalleled pace. → AI is driving breakthroughs in medicine, food security, and climate action at unprecedented speeds. Developing vaccines in 100 days is no longer a distant possibility. It is an active goal of the Coalition for Epidemic Preparedness Innovations (CEPI). The creative industry is being rewritten. → Powerful AI tools are reshaping content creation and shifting industry dynamics in Hollywood and beyond. The impact will be significant, as will the ongoing debates around authenticity and copyright. 2025 will redefine how we build, innovate, and create with AI. Which of these trends will impact your industry the most, and how are you preparing for it? https://lnkd.in/gk_NJM2E

If you are looking for innovating, building, investing or researching the “Big Ideas in Tech 2025”, this impressive report from Andreessen Horowitz is for you! 🔆The pace of innovation is accelerating, and here are some of the transformative trends reshaping industries and society:- 🔋 Nuclear Energy Revival - AI-driven electricity demand is sparking a resurgence in nuclear power. Decommissioned plants, like Pennsylvania’s Three Mile Island, are gearing up to restart operations by 2028. 🌌 Space Infrastructure Revolution - The first-ever “catch” of the Starship booster signals rapid reusability in heavy-lift space vehicles. This breakthrough will enable large-scale space infrastructure, from orbital data centers to biomedical labs, and redefine global transportation. 🧠 AI & Hardware Engineering Synergy - As AI integrates with complex hardware, demand for electrical, mechanical, and industrial engineers is set to outpace traditional software engineering roles. 🛰️ Earth Observation Data Explosion - With Earth observation satellites doubling in five years, industries are leveraging this data for decision-making. Opportunities abound for creating industry-specific solutions using this treasure trove of insights. 🛡️ Decentralized Defense Systems- Military operations are evolving, relying on autonomous drones, sensor networks, and battlefield AI for real-time decision-making in remote zones. This decentralization demands scalable compute power and energy solutions. 🥽 XR’s Practical Potential - Extended Reality (XR) devices like Apple’s Vision Pro and Meta’s Orion AR glasses are unlocking new possibilities in robotics, simulation, and beyond, enhancing how we interact with the physical world. 🧬 Biomanufacturing Breakthroughs - Advances in synthetic biology are enabling the creation of novel biomaterials and bio-based products, setting the stage for innovations in healthcare, materials science, and sustainability. ⚡ Energy Transition Technologies- Fusion energy and advanced battery storage solutions are moving closer to commercialization, promising to revolutionize how we generate and store energy globally. 💡 Generative AI Expanding Use Cases- Generative AI is evolving beyond text and images to fields like drug discovery, industrial design, and customer service, unlocking unprecedented levels of innovation. 🌟 These are just a few of the groundbreaking developments redefining our future. The race to innovate has never been more exciting! 👉 What trends do you think will have the biggest impact by 2025? Check out the full report here https://lnkd.in/dP2X86Qu Share your thoughts below! #Innovation #TechTrends #AI #FutureOfWork #SpaceExploration #Sustainability #XR #Biomanufacturing