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Teneo Valued at $2.3 Billion After Liechtenstein's LGT Invests
A fund backed by Liechtenstein's Princely Family is taking a minority stake in communications and consulting firm Teneo, people familiar with the matter said. The investment by LGT Capital Partners will value New York-based Teneo at about $2.3 billion, the people said, asking not to be identified because the information is private. Bloomberg News reported in July that Teneo was holding talks about bringing in a new investor.
Forbes
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Strategic Planning Is A Performance. Preparedness Is A Strategy.
We're in the thick of strategic planning season—a time of big binders, slide decks, and multi-day meetings designed to map out the future. But when the unexpected hits, how much of that work actually helps? Too often, we plan for a world that doesn't exist. We build for order when the world delivers chaos. That's why we don't need better strategic plans—we need better strategic preparedness. Because clarity is the new strategic edge. You don't just need a clear plan, you need space for clear thinking, clear priorities, and clear ways to adapt when the inevitable disruption comes. Planning vs. Preparedness: What's the Difference? Planning is based on the expectation of control. It assumes order, stability, and predictability. But in today's environment—AI disruptions, economic volatility, shifting customer demands—that assumption is broken. Preparedness, by contrast, is grounded in the expectation of change. It's about building capacity, not control. It embraces adaptability over accuracy. It prizes clarity over perfection. It's the difference between betting on a specific future—and being ready for many. 'Plans are worthless, but planning is everything.' — Dwight D. Eisenhower That quote might seem contradictory, but it nails the point. The process of thinking through possibilities is essential. But overly rigid plans become obsolete the moment reality changes—and reality always does. Everyone knows Aesop's fable about the ant and the grasshopper. But let's imagine a corporate version: The ant spends the summer preparing: gathering food, storing it for winter, strengthening its tunnels. The grasshopper? He brings in a consultant to write a 60-slide deck on 'Winter Opportunity Alignment.' When winter hits, guess who survives? Too many companies are still the grasshopper—with plans that look great on paper, but little flexibility or resilience when conditions shift. Because we've confused preparation with preparedness and planning with clarity. Companies with hyper-optimized, 'just-in-time' supply chains were exposed when COVID hit. There was a plan—but no buffer, no alternatives, no scenario readiness. Companies like Toyota adapted faster because they'd already built resilience into their systems—investing in supply chain flexibility and cultivating multiple sourcing partners even when it wasn't 'efficient' in the short term. There's an old maritime saying: 'When the seas are too rough to sail, fishermen repair their nets.' That's preparedness. But what do many companies do when seas get rough? They call more meetings. They shuffle priorities. They launch new 'transformations.' Instead of strengthening the systems that help us respond to chaos, we waste time reacting to it. We repair nothing—we just get busier. Preparedness means using downtime to sharpen tools, realign teams, clarify decision authority, and scenario plan. It means building clarity and adaptability into our culture before we need it. I'm not saying we don't need strategic planning. I'm saying that how we're doing it is onerous, uninspired, and too reliant on a single doc or direction. In too many orgs, planning is a show. We over-polish slide decks. We obsess over timelines. We write 30-page plans that no one will read again. We perform alignment instead of enabling action. We're drowning in planning meetings—while teams quietly ignore the plan and focus on the real work of making progress. According to research, unclear planning and slow decision-making processes are major drivers of leader burnout and organizational stagnation. In fact, Gartner reports that 65% of decisions made today are more complex than they were just two years ago, often involving more stakeholders, more data, and more risk. Combined with a rise in decision fatigue and change exhaustion, these unclear processes are now stalling execution, eroding engagement, and hindering growth. We need a reset. Let's stop pretending we can predict the future. Instead, let's prepare to meet it. That means: This planning season, stop obsessing over the perfect roadmap. Start asking: This isn't about ditching plans. It's about planning for the right thing: readiness, clarity, adaptability. Because if you're not preparing, you're pretending.
Forbes
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The Future Of Apps: AI-Assisted Coding And Autonomous Engineering
Hashim Hayat, CEO & Founder of Walturn. Imagine describing a mobile app idea in plain language and instantly seeing it come to life, fully operational across iOS and Android. This futuristic scenario is rapidly becoming a reality due to significant advances in autonomous AI mobile engineering platforms. Having delivered two client mobile app projects end-to-end using an autonomous AI engineering platform, I have seen firsthand the transformative power of this technology. In this article, I will explore the evolution of AI-assisted coding tools and autonomous mobile engineering platforms. I will highlight what differentiates autonomous AI and how this shift impacts the future of mobile app development, particularly with frameworks that support cross-platform development. The Limitations Of AI-Assisted Tools For Mobile Development Tools such as Cursor, GitHub Copilot and ChatGPT have significantly improved productivity for mobile developers by providing code suggestions, refactoring tips and bug-fixing support. One analysis noted that developers using AI assistants can complete approximately 126% more projects weekly. However, these tools heavily rely on the developer's technical expertise to manage critical aspects like cross-platform compatibility, user authentication, backend setup and database integration. In my experience, tools like these are excellent productivity boosters, but they remain limited because developers must manually handle app architecture, state management patterns and backend integrations. The Rise Of AI Mobile Engineering Autonomous AI mobile engineering platforms have emerged as game-changers. Unlike traditional assistants, these platforms autonomously translate natural-language prompts into complete, fully functional mobile applications optimized specifically for frameworks that support cross-platform development. In one specific case, I provided an autonomous engineering platform with a prompt to build a task-management mobile app featuring user authentication, a Firebase backend and a Flutter frontend. Within minutes, the platform generated the complete application with well-structured Flutter UI components, Firebase backend services, secure authentication methods and efficient state management—all following industry-standard architectures like model-view-viewmodel (MVVM). Generating Production-Ready Code For Mobile A recent study found that while today's top AI models can produce correct and functional code, they sometimes yield convoluted solutions that 'may need more reworking to ensure maintainability.' Modern AI mobile engineering platforms mitigate this issue by automatically ensuring that the apps follow best industry practices like clean architectural patterns, efficient directory structures and maintainable codebases. During ongoing maintenance of client projects, I have found AI-generated code to be organized, readable and easily extendable. Integrating additional features such as payment gateways or QR code-based sharing proved seamless because the platform leveraged its understanding of existing mobile app architecture to maintain consistency. Real-Life Capabilities Of Autonomous AI Mobile Engineering Platforms Autonomous AI mobile engineering platforms distinguish themselves from traditional assistants through their comprehensive end-to-end capabilities. These platforms automatically handle the setup and configuration of backend services, such as Firebase or other infrastructure solutions, tailored to the needs of the mobile app. They also implement advanced integrations, including complete user authentication flows and seamless connections with third-party APIs. In addition, they provide instant live previews across various mobile device simulators, which accelerates the prototyping and testing process. These platforms further streamline development by generating clean, production-ready code that integrates smoothly with standard version control systems like GitHub to simplify collaboration and code management. Impact On Mobile Developers And Startups The shift toward autonomous AI mobile engineering fundamentally reshapes the roles of mobile developers. Rather than spending extensive hours on routine tasks like writing boilerplate code or setting up repetitive backend configurations, developers can now concentrate on strategic architectural decisions, user experience enhancements and quality assurance. Moreover, autonomous platforms dramatically speed up the mobile app development lifecycle. For example, with autonomous engineering platforms, I have been able to deliver fully functional mobile MVPs within days rather than months. This accelerated development allows startups and businesses to quickly validate ideas, pivot faster and respond rapidly to changing market demands. Another important implication is the democratization of mobile app development. Entrepreneurs, product managers or anyone with an innovative idea can now create sophisticated mobile apps without extensive coding knowledge, which fosters broader participation and innovation in the mobile development ecosystem. Navigating The Road Ahead While autonomous mobile engineering platforms represent a significant advancement, human oversight remains essential. In my experience, mobile apps generated with AI still require comprehensive human review for final testing, security assessments and minor adjustments. Moving forward, tighter AI integration across all stages of the mobile app lifecycle, from initial design through deployment and ongoing iteration, is likely. New roles such as 'AI orchestrators' might emerge, and the tech leads of tomorrow will likely manage both human and AI contributors side by side. Conclusion In conclusion, the emergence of AI mobile engineering platforms is more than an incremental technological advancement. It signifies a fundamental transformation in how we approach mobile app development. Rather than merely automating repetitive coding tasks, these platforms allow users to shift their focus toward strategic oversight, innovation and crafting superior user experiences. Ultimately, integrating autonomous AI with human oversight sets a compelling new standard for mobile innovation, productivity and excellence. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
