How I Built My Books and Research Workflow with DingTalk AI

In the past, writing a book meant long nights, piles of notes, and endless revisions. Today, I can design, write, and analyze data for entire books and articles inside one intelligent platform: DingTalk. It’s no longer just a communication tool; it has evolved into an ecosystem for creation, automation, and collaboration — and it has transformed how I think, write, and teach about technology.

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From a Blank Page to a Living Document

When I began using DingTalk AI Docs, I didn’t expect it to become my creative co-author. Traditional word processors are static — you type, you edit, you save. DingTalk AI Docs, however, is dynamic. It works more like a real-time creative assistant, capable of brainstorming, rewriting, translating, and even analyzing tone.

For instance, when drafting articles for my AI column or chapters for my books, I start with a single idea or paragraph. The AI in DingTalk Docs then expands that into a coherent structure — proposing outlines, offering examples from current technology trends, and summarizing related research from my previous works. It can even detect inconsistencies in logic or suggest better phrasing in both English and Chinese.

When I wrote about Agentic AI — the idea that AI agents can autonomously perform tasks and collaborate like digital employees — I used AI Docs to refine my language so that both business executives and students could understand the concept. The tool didn’t just improve grammar; it helped me strike the right balance between academic precision and human readability.

Over time, I began to treat DingTalk AI Docs not as software, but as a collaborative editor. It remembers my writing tone, frequently used terminology, and the format I prefer for different audiences. That consistency became crucial when producing multiple outputs — books, columns, proposals, and speeches — all aligned in tone and philosophy.

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Turning Web Chaos into Organized Intelligence

Writing modern books, especially about AI and technology, demands constant access to updated information. Manually collecting and cleaning data from hundreds of websites is inefficient. That’s where DingTalk’s AI Spreadsheet became my secret weapon.

This spreadsheet isn’t a passive table. It’s an active, thinking assistant. I programmed it to conduct automated web research, pulling data from APIs and public websites — such as AI startup directories, academic databases, and software trend trackers.

Once the data arrives, the AI instantly categorizes, filters, and tags information according to my criteria — for example:

• Emerging AI tools by region
• Venture funding trends by month
• Open-source model updates
• Technological adoption rates among SMEs in Asia

Then comes the part I love most: automated visualization. With a few clicks, the spreadsheet generates graphs, bar charts, or trend lines that summarize weeks of data collection in seconds. When I was researching the energy consumption patterns of large language models for my article on Sustainable AI, I didn’t have to manually calculate or design the charts. DingTalk’s AI did it — generating interactive visualizations that updated automatically as new data flowed in.

This system turned what used to be an exhausting research phase into an enjoyable discovery process. Instead of wasting time on data cleaning, I could focus on insights and narratives. I began to see patterns earlier — how policy changes affect funding, or how adoption of Chinese AI tools was accelerating after new data security regulations. These insights directly shaped the arguments and forecasts in my columns.

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Automated Reporting: My Personal Research Dashboard

After I set up the AI spreadsheets, I realized that the real treasure wasn’t just in data collection — it was in reporting. DingTalk’s AI reporting system connects the spreadsheets to a dynamic dashboard that updates daily. I can see live statistics about the topics I track: AI company valuations, keyword trends in research papers, or sentiment analysis across media outlets.

For each category, the AI generates concise summaries, highlighting the most important movements — for example:
“Funding for AI-powered healthcare startups rose 24% this quarter, with notable growth in Southeast Asia.”

That kind of insight used to take hours of manual analysis. Now, DingTalk delivers it to me automatically in report format, complete with graphs, explanations, and even predictions.

This reporting system doesn’t just save time; it sharpens judgment. It allows me to write more confidently, backed by fresh data visualizations. When preparing slides for an AI seminar or writing a column about cross-border digital transformation, I can export the charts directly into PowerPoint, already formatted and styled. The AI assistant even suggests captions that summarize the data trends accurately.

Over time, I’ve noticed how these AI-generated visuals became part of my storytelling. Numbers alone are cold; insights, when visualized elegantly, make readers feel the transformation.

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Building My Book Content Assistant: When Readers Talk to the Author’s Mind

One of my most ambitious experiments with DingTalk AI was creating a Book Content Assistant — an AI-powered interactive companion for readers of my books. It started from a simple question: What if readers could ask my book questions directly?

With the help of DingTalk AI Assistant, I designed an intelligent system that reads the full manuscript of my books, understands the chapters, and can answer reader queries in natural language. It’s like turning a static book into a living, conversational textbook.

Here’s how it works:

1. I upload the book’s content and notes into DingTalk Docs.
2. The AI Assistant processes the material, identifying key terms, technical explanations, and thematic relationships.
3. I define the tone and context — for instance, “Explain like a professor who is also a mentor.”
4. The AI is then embedded as a companion link at the end of each chapter, accessible via QR code.

Readers who scan the code can chat with the AI Assistant to clarify complex ideas — for example, asking, “What’s the difference between AI Plus and AI First?” or “How do AI agents change the future of HR?” The assistant gives contextual answers, referencing examples from the book or external updates from recent AI research.

The most powerful part is that the assistant keeps learning. As readers ask questions, it refines its explanations, identifies commonly confusing topics, and even suggests updates for the next edition of the book. This transforms the publishing process from one-directional (author → reader) into an interactive dialogue. Knowledge no longer ends with publication; it evolves through the reader community.

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AI as a Collaborative Network, Not a Tool

Through these experiences, I’ve realized DingTalk AI is more than a productivity suite — it’s a creative ecosystem. Each component — Docs, Spreadsheet, Assistant — interacts with the others, forming a digital nervous system for my work.

For example, when I draft an article in AI Docs, I can embed live charts directly from my AI Spreadsheet. When the spreadsheet data updates, the graphs in the article refresh automatically. If the AI Assistant detects that readers often misunderstand a term, it can highlight that section in the document, prompting me to revise it for clarity in future editions.

This interconnectedness creates a closed loop of learning:

• I research using AI spreadsheets.
• I write using AI Docs.
• I publish with AI Assistant integration.
• I receive feedback through reader interactions.
• I revise based on that feedback — and the cycle continues.

It’s a new model for digital authorship — one where the writer and reader evolve together, mediated by intelligent systems that understand both language and data.

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A New Philosophy of Creation

What I’ve learned from this journey is not just technical efficiency but philosophical transformation. DingTalk AI allows me to practice what I call “AI-First Authorship.” It’s not about using AI to replace creativity but about reorganizing the creative process around intelligence.

In traditional writing, you start with a fixed idea and push it forward linearly. In AI-First writing, ideas emerge dynamically. The system acts as a partner — questioning, researching, editing, and visualizing. You move from a one-person author to a multi-agent collaboration environment.

This shift also changes how I manage my time and mental energy. With AI automating data work and summarization, I can focus on interpretation and imagination — the parts that still demand a human touch. It’s like having an infinite research team that never sleeps, yet still listens carefully to your tone and intent.

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The Broader Impact: From Individual Productivity to Organizational Intelligence

My experience isn’t unique. Many organizations adopting DingTalk AI are discovering similar transformations. When an individual learns to integrate AI tools — like I did with Docs, Spreadsheet, and Assistant — the entire organization gains what I call “AI literacy momentum.”

A single author using AI can write faster. A team using the same system can innovate faster. Data no longer lives in silos; it circulates across departments, feeding insights back into marketing, HR, or product development. For example, my own writing workflow inspired colleagues in insurance and education to build internal AI knowledge bases — turning their static documents into living systems of intelligence.

The result isn’t just better content; it’s a smarter organization where ideas move freely between people and AI systems.

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Looking Ahead: Books That Think, Readers That Teach

I often say the future of writing isn’t about faster typing — it’s about thinking with machines. DingTalk AI has made that future real for me. Every document I write is connected to a network of intelligence — data sources, feedback loops, and interactive assistants.

In my next book, I plan to integrate even deeper with DingTalk’s AI capabilities: voice-driven idea logging, real-time fact verification, and co-writing sessions with multiple AI personas — one for technical review, one for reader empathy, and one for future foresight.

We’re entering an era where books will not just be read but will converse. Where spreadsheets won’t just calculate but analyze narratives. And where AI assistants will not just answer but educate.

That is the promise of DingTalk AI — not merely a collection of features, but a revolution in how knowledge is created, refined, and shared. It has allowed me to become both author and architect — designing not just texts, but intelligent ecosystems of learning.

And for the first time, I feel that writing, research, and education are no longer separate crafts. They are one continuous flow — powered by AI, guided by human curiosity, and living in the digital heart of DingTalk.