Summary of the Core Message
Sandberg's remarks at the graduation ceremony, which suggested "no need for a ten-year plan," have sparked significant discussion. This article delves into the essence of the issue: in the age of AI, what is outdated is not "long-termism" (the sustained commitment to important directions) but rather the "long-term script" (the assumption that the future will unfold in a linear manner). Companies should abandon precise long-term roadmaps and adopt a more flexible planning framework that involves setting directions for ten years, making assumptions for three years, undertaking key initiatives for one year, and adjusting strategies every ninety days. This approach allows companies to remain adaptable to change and ultimately embrace a new form of long-termism that is focused on addressing problems rather than fixating on predetermined answers.
I. Sandberg's Message: Not About Giving Up, but About Rejecting a Predetermined Life Script
When Sandberg says "no need for a ten-year plan," she doesn't mean encouraging people to be impulsive or make decisions without thought. Instead, she aims to debunk the misconception that life follows a set script—entering a large company at a certain age, getting promoted to management at another age, and achieving financial freedom by yet another age. This fixed trajectory no longer applies in the AI era. Her true advice is to have a clear vision for the long term (for example, what kind of person you want to become) and specific short-term goals (such as acquiring certain skills this year), while leaving room for flexibility in the middle.
Her own experience illustrates this point: when she graduated, the internet had not yet emerged, and companies like Google or Facebook did not exist. Yet, thanks to her accumulated skills (learning, analytical abilities, and organizational skills) and her reputation, she seized unexpected opportunities by joining these companies. Her underlying message is that opportunities do not come to you; you must make yourself worthy of them.
II. Why the "Long-Term Script" Fails in the AI Era
Four structural changes have rendered traditional planning obsolete:
1. Technology Redefining Jobs: Technology used to enhance efficiency (e.g., using Excel instead of calculators); now, AI directly competes for jobs (e.g., writing copy or doing basic design work) and creates new roles (e.g., AI trainers). As jobs themselves evolve, how can you plan for your role ten years from now?
2. Blurring of Industry Boundaries: Companies in traditional industries (like automotive or retail) are transforming into technology-driven entities (e.g., using data for targeted marketing). Your competitors may no longer be within the same industry; following traditional paths will lead to failure.
3. Rapid Change Outpacing Organizational Adaptation: What used to require a three-year plan now requires frequent adjustments (e.g., short-video platforms change their strategies every six months). By the time you adjust, the opportunities may have passed.
4. Shift from Linear Growth to Uncertain Trends: The assumption of 20% annual growth no longer holds true. AI and other factors can drastically impact costs or market dynamics, making fixed plans ineffective.
III. Avoid Misunderstandings: Not Planning Means Giving Up
Many people mistakenly interpret "abandoning a long-term script" as giving up altogether or simply chasing the latest trends:
- It's not about being impulsive: Lack of direction can lead to aimlessness (e.g., learning AI one day and then switching to live streaming without gaining anything substantial). You need a clear goal (e.g., solving health management issues for ordinary people), but the approach can be flexible.
- Don't chase every trend: Focusing on trends wastes resources; true long-termism means focusing on changes that are relevant to your core issues. For example, if AI can improve your educational offerings, invest in it; if the metaverse is unrelated to your core business, ignore it.
- Not all industries require long-term planning: Industries with longer R&D cycles (e.g., semiconductors or pharmaceuticals) still need long-term investment, but you shouldn't bet on a single path (e.g., don't specialize in just one chip manufacturing process).
- Planning is About Transformation, Not Cancellation: Shift from fixed routes to multiple scenarios (e.g., what if AI replaces 30% of jobs? What if user preferences shift towards personalization?), and from annual plans to ongoing adjustments.
IV. A New Planning Framework for Companies: Four Levels of Stability with Flexibility
The article proposes a practical framework that divides planning into four time scales:
1. Ten-Year Direction (North Star): Define your long-term vision—e.g., "How can we serve people and solve what problems?" For a restaurant, this could mean "providing healthy and affordable food." This direction remains stable regardless of future advancements (AI in cooking or unmanned stores).
2. Three-Year Assumptions (Not Promises): Identify key possibilities (e.g.,预制 meals may become popular, or community stores may replace malls), but plan for potential failures. If assumptions prove wrong, act promptly (e.g., try out a pilot project for预制 meals or discontinue it if users don't buy them).
3. Annual Key Initiatives: Focus on one or two critical tasks (e.g., building a central kitchen or increasing online orders from 10% to 30%).
4. Quarterly Adjustments: Regularly assess your assumptions and adapt strategies (e.g., if预制 meals don't sell well, adjust the recipe; if AI can save time in the kitchen, test its use).
The logic behind this framework is: the more stable your long-term direction, the more flexible you can be in short-term adjustments.
V. The Importance of "Choice" Over Prediction
In the AI era, no one can predict the future with 100% accuracy. Therefore, companies need to retain the ability to make choices. This means:
- Maintain Resource Flexibility: Don't invest all your funds in one project; keep some cash for unexpected changes.
- Conduct Small-Scale Tests: Experiment with new ideas at a low cost (e.g., open a pilot store instead of 100).
- Develop Versatility: Skills like user management can be applied across different projects.
- Quick Response: Be responsive to market signals (e.g., if customers don't like预制 meals, adjust your strategy immediately).
Sandberg was able to seize opportunities at Google because she had the necessary skills, reputation, and courage. Companies should do the same: they may not always predict the future, but they must be prepared to seize it.
VI. The Core of the New Long-Termism
Traditional long-termism focused on a single path; the new approach emphasizes:
- Clear direction with flexible paths: Your goal remains the same (solving health management issues for ordinary people), but the methods can evolve.
- Constantly Updating Answers to Changing Problems: Solutions may change over time (e.g., from selling health supplements to using AI for health management, or opening smart clinics).
In summary, don't focus on "what I want to do in ten years"; instead, focus on "what problems I still need to solve in ten years." This is the essence of long-termism in the AI era.