Letter to Spiritual Shareholders 2026

Preface

2025 was a volatile year. As AI models grew more powerful, change accelerated. Every few months brought new capabilities or applications that exploded across the landscape. Meanwhile, AI continued to penetrate new domains. Everyone had to accept these changes as reality.

The faster things change, the more important it becomes to see through surface phenomena to their essence—like a fixed needle in a vast ocean, responding to change with constancy. So at the start of each year, I want to write down the conclusions from the past year. Then practice them in the new year. Keep what works. Fix what doesn’t.

Some things are worth doing for the long term. Year-end reviews rank among them. Berkshire’s annual shareholder letters have taken this to the extreme. At the end of 25, when Buffett writes his final letter, we’ll lose another wise elder sharing wisdom freely. I’ve been deeply influenced by this kind of altruism. Each letter brings new investment insights, but what stays constant is genuine sharing and reflection.

For me, writing sharpens thought. Sharing connects like-minded people (spiritual shareholders) and amplifies personal influence. As someone who benefits, I want to continue this tradition. Consider it making friends. If this helps any spiritual shareholders, I’m honored.

Now let’s talk about the internet world I know so well yet still find strange.

Change in the Internet World

The internet still generates massive amounts of data daily. But data producers, production speed, and ownership have quietly shifted. AI now plays a key collaborative role in productivity. It has even entered a flywheel phase of self-reflection and iteration without human prompts. While we enjoy AI’s tremendous efficiency gains, humans gradually give AI more authority. Data expands at unimaginable speed while human attention overload grows.

So I started thinking: In this age of information overload, what role do humans play in the production relationship and consumption chain coexisting with AI? Or when experience and skills matter less, what directions can humans improve to participate in this wave? How can we make AI work as leverage in our desired direction?

Past events weren’t just productivity changes—the consumption model also shifted. So I’ll explain some recent conclusions.

AI Agent Production Cycle Mechanism

From first principles, analyzing the production side, AI agent cycles break down into:

Context (data) + Model inference + Tool calls

For context, we can:

• Define clear problems and needs for AI (problem definition and engineering breakdown)
• Actively provide or produce high-quality, unpretrained context (unique or real-time content first)
• Extract quality content from model pretraining data through prompts as context

For model inference, we can:

• Work in AI models or agents—model algorithms or infrastructure
• Invest in related supply chains to capture inference demand growth
• Use inference’s analogical reasoning for reverse engineering and mimicry
• Use best models in each vertical for maximum productivity

Tools are human experience plus repeated workflows crystallized. For tools, we can:

• Use AI inference to automate repetitive processes
• Summarize domain experience into SOP documents
• Package valuable tools into products for scale

For the cycle mechanism:

• Define strict acceptance plans and standards
• Maintain judgment within the domain during process
• Intervene when off-track, correct quickly
• Summarize experience, form reusable long-term memory

Consumption-Side Change

On the consumption side, AI-generated content has exploded across major social media. Right now, Seedance 2 video models are going global. Text, images, music, and video generation quality exceeds imagination. When the world stops asking whether content is AI-generated, AI-driven production and consumption mature. I believe we’ll increasingly struggle to find original content not processed by large models. Eventually, most consumable content will be AI-driven, including client-side distribution and recommendations.

Meanwhile, generated consumer content faces huge intellectual property disputes. Without data owner authorization, model companies scrape raw data directly into pretraining as prior knowledge, then profit from derivatives on the consumption side while data copyright holders get no share. This model isn’t sustainable—it doesn’t encourage platform creators to produce better content. But short-term solutions seem limited. Let content platforms handle it.

The Power of Words

Understanding that the transformer architecture’s smallest unit is the token helps enormously. It shows us where human agency might still leverage the most in the future. All model input and output are tokens, but quality output depends on quality input. Dividing by input-output types gives this table:

Smart shareholders may already see the pattern. Text input enables all “magic”—it’s decisive and leverages the most. The power of words speaks for itself. As model capabilities grow, writing skills may become the most important basic skill. Everything else can be defined in text and produced by AI.

Since text input generates text output, anyone can quickly create various content. Massive AI-generated fast-content will spread like viruses across the internet until everything drowns. Some say originality died because AI copying is so fast that finding true authors across the web is hard. But because of this, human-like content may become scarce in the future.

Human touch means the creator’s unique life experiences—the ups and downs lived, the mistakes made, the lessons learned. This combination forms spiritual assets no AI can copy. So independent human thinking remains important—fitting human learning curves and paths rather than cold mathematical polynomials.

When literary power has never been stronger, not acting would be wasteful. So the long-silent me returned to social media. In 26’s first month, I decided to act immediately. I reorganized old study notes and, with AI assistance, classified, tagged, summarized, and translated hundreds of technical notes in three weeks. I published them all on my bilingual independent blog built with vibe coding. I’ll publish more independent thinking, with WeChat updates too. Anyway, I’m on the train.

Looking Forward

In the future, we’ll have more “creators” around us than ever. AI lets everyone easily pick up the writer’s pen, painter’s brush, and director’s viewfinder. Honestly, I can’t predict where this world of universal creation leads. But I believe participating and creating valuable content isn’t a losing bet. Whether these investments convert to real value? Time will tell. I know I can’t be perfect or see where the path leads. But persistence matters—maybe we’ll scale big.

At New Year’s start, I follow my most admired idol Buffett and share my shallow thoughts on the AI internet world. Thanks to all readers. May we all become better versions of ourselves in the new year.

Happy New Year!

End.