When Everyone Has AI, How Do You Win? Howard Marks on "Second-Level Thinking"

In the age of AI, information is overwhelming, and opportunities appear to be everywhere. Every company is talking about boosting efficiency by 50% or cutting costs by 30% after implementing AI. Every investor is chasing the hottest AI stocks. It all seems so simple, straightforward, and full of promise.

But let's pause for a moment to consider a classic question posed by the legendary investor and founder of Oaktree Capital, Howard Marks: "And then what?"

In a future where everyone possesses the superpower of AI, what will a true competitive advantage look like? When everyone in the market agrees that something is an "obvious" opportunity, is it still an opportunity at all? This is where Howard Marks' core philosophy—"Second-Level Thinking"—becomes more critical than ever before.

First-Level vs. Second-Level: The Depth of Your Thinking Determines Your Endgame

Let's use a simple analogy to differentiate these two modes of thought.

First-level thinking is simplistic, superficial, and linear.

• A first-level investor says, "This is a great company, so let's buy the stock."

• A first-level business manager says, "AI boosts productivity, so let's immediately deploy AI tools." This is the conclusion that nearly everyone arrives at instantly. As Howard Marks describes it, first-level thinkers seek simple formulas and quick answers.

Second-level thinking is deep, complex, and interactive.

• A second-level investor says, "This is a great company, but because everyone knows it's a great company, its stock is already overvalued and possibly in a bubble. Therefore, the risk of buying it now is high."

• A second-level business manager says, "AI will boost our productivity. But it will also boost the productivity of all our competitors. If everyone achieves the same efficiency gains, it will likely lead to an industry-wide price war, and in the end, no one's profit margins will improve. So, how can we use AI to do things that our competitors cannot easily replicate?"

Second-level thinking always asks, "And then what?" It requires us to consider not just the immediate consequences of an action, but the consequences of those consequences.

How to Apply Second-Level Thinking in the Age of AI

Applying this powerful mental framework to the current AI wave yields some profound insights.

1. On Corporate Strategy: From Chasing Efficiency to Creating Uniqueness

• First-Level Thinking: We'll use AI to automate customer service, optimize our supply chain, and accelerate content creation to do what we currently do, just faster and cheaper.

• Second-Level Thinking: These efficiency gains will ultimately be passed on to consumers as lower prices and will not form a long-term competitive moat. Our real opportunity lies in using AI to create entirely new and unique customer experiences. For example, using AI to provide deeply personalized product recommendations or dynamically altering a product's features for each user. Or, using AI to analyze previously ignored "unstructured data" to uncover entirely new market needs. The key is to use AI to do new things, not just to do old things faster.

2. On Talent Development: From Using Tools to Mastering Thought

• First-Level Thinking: We need to hire more "Prompt Engineers" and train our employees on how to use AI tools more proficiently.

• Second-Level Thinking: When AI can handle 90% of the executional work, the critical 10% that determines success will be the ability to ask the right questions, to think critically, and to exercise sound judgment over AI-generated outputs. The most valuable professionals of the future won't be those who are best at operating AI, but those who are best at questioning it and combining its power with deep industry insight. The core mission of a company should be to cultivate the depth of its employees' thinking, not their proficiency with tools.

3. On Investment Decisions: From Chasing Hot Stocks to Finding Blind Spots

• First-Level Thinking: AI is the future, so buy the most famous AI-related stocks immediately.

• Second-Level Thinking: To what extent is the potential of these giants already priced into their high valuations? Has the market's euphoria created blind spots regarding potential risks (e.g., regulation, energy bottlenecks, technological disruption)? Beyond the star companies, what overlooked "second-order" industries will be profoundly affected by the AI wave (such as energy, cooling systems, and data verification, as we've discussed before)? Conversely, which traditional industries, thought to be "doomed" by AI, might actually find a unique way to integrate it and experience a renaissance?

A Final Thought

Howard Marks' philosophy provides a necessary dose of sobriety in this exuberant age of AI. He reminds us that when a new technology becomes universally accessible, the technology itself ceases to be the advantage. The "quality of thought" behind its application becomes the differentiator.

First-level thinking might allow you to keep up and avoid being left behind. But only those businesses and individuals who engage in second-level, or even third-level, thinking will truly distinguish themselves and achieve superior returns in the tectonic shift being driven by AI.

This ultimately leaves a question for all of us, whether we are managers, team members, or individual investors: As AI increasingly commoditizes the value of "execution," will human "thought"—especially this deep, second-level thinking—become the scarcest and most valuable asset of all? In your company or your portfolio, are you engaged in first-level imitation, or second-level introspection?