Many have asked me to write sth on the AIGC frenzy happening in China since my last post. So here it is, this time I am telling it like a story. When ChatGPT dropped in late 2022, Silicon Valley 🇺🇸 looked like Goliath—$5B+ poured into training GPT-4, a handful of fortress-like labs guarded by prestige PhDs. China 🇨🇳, meanwhile, seemed like David, locked out behind the Great Firewall. But then the dragon awakened: instead of waiting, China built hundreds of its own models—and the story flipped.Here’s what’s fascinating: two completely different playbooks for the same revolution.🔹 The Fortress (U.S.)- 3–5 dominant labs.- Training costs: $100M–$5B per model.- Release cycle: 12–18 months.- Talent: PhD pipelines from Stanford/MIT, 5–7 years to leadership roles, avg. comp skewed to salary + big tech stock. 🐉 The Swarm (China)- 200+ serious LLM contenders launched in 24 months.- Training costs: DeepSeek R1 at <$6M (≈16:1 cost advantage).- Release cycle: monthly iterations.- Talent: 11.8M annual university grads feeding the ecosystem, recruiters camping outside Tsinghua/PKU, equity offers of 0.5–2% even for senior engineers, promotions in 12–18 months.And it’s not just about AI models—it’s about talent philosophy (Knights in armor VS. Agile warriors) 1️⃣ Velocity vs. Prestige – do you prize speed of impact or brand credibility? 2️⃣ Scale vs. Resilience – one fortress or many agile units? 3️⃣ Career Promise vs. Career Acceleration – longevity or fast-track growth?As the AIGC race unfolds, the question isn’t just who builds the best models. It’s this: will the future of talent look more like fortresses… or swarms?

When foreign companies ask me for suggestions for entering China's talent market, my usual answer is - try to partner or acquire something domestic, or go completely local. This one is for China 🇨🇳. With 11.8M university graduates annually—the largest talent pool on Earth—China’s job market is massive but uniquely volatile. Salaries in AI can spike 35% in just one quarter, and entire hiring landscapes shift within days when a unicorn moves. Behind the Great Firewall, billion-dollar empires can spring from viral phenomena like Labubu collectibles, while domestic tech giants evolve at breakneck speed—from the BAT era (Baidu, Alibaba, Tencent) to the TMD wave (Toutiao, Meituan, Didi) and now the TTMAP generation dominating AI and consumer tech. Layer on the “35-year career ceiling,” the exodus from Tier-1 cities, and a legal grey zone where crypto firms still employ thousands of mainland professionals… and you’ve got one of the most paradoxical and high-stakes talent markets in the world.💡 So how do you win here?1️⃣ Build multi-hub hiring models that tap emerging cities without losing Tier-1 prestige2️⃣ Offer career longevity paths to keep mid-career talent in play3️⃣ Hedge against market shocks by diversifying hiring pipelines across regions & sectors

Hi fellow subscribers,

If SCALE UP has sparked your curiosity and inspired your growth journey, give a listen to this 🎙️ compelling review of the book, packed with deep insights, practical examples, and thoughtful discussions on the future of work in the era of AGI.

In this podcast episode, you'll explore:

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