This is quite interesting.
OpenClaw has been all over social media lately, right? Everyone’s posting screenshots of “AI writing code automatically” or “AI running workflows on its own.” But honestly, most people have missed the point—this isn’t just a “fancy tool,” and the logic of the capital market isn’t about how much work it can do.

1. Where the Real Value of AI Agents Lies
Right now, everyone’s obsessing over “how many jobs it can replace,” treating it like buying a Roomba. But the real value isn’t about “getting work done”—it’s about how AI Agents could reconstruct entire workflows. For example: Back in the day, factories upgraded by buying better machine tools, but the Industrial Revolution happened when machines started dictating production rhythms. The problem today? Too many people are still stuck in the “buying machine tools” mindset when evaluating AI Agents.

2. What’s Capital Betting On? Probably the Wrong Thing
In China, 80% of AI Agent investments are pouring into the application layer. Build something that can book flights or draft weekly reports, and suddenly it’s IPO material. But look at companies like Adept or Inflection abroad—they’ve been working on foundational decision-making frameworks for ages. The funniest part? Some investors keep shouting about “China’s AutoGPT” while struggling to distinguish between task decomposition and reinforcement learning in agents.

Here’s the risk: If it turns out OpenClaw and its peers are just glorified workflow automation tools, how hard will today’s valuations crash? And let’s not even talk about bosses expecting “AI employees” to cut labor costs—have they factored in training expenses and API call fees?

3. The “China Model”? Might Be a Myth
Some claim OpenClaw represents “localized innovation.” But take a closer look at its tech stack, and it’s not much different from foreign counterparts. The real difference lies in the market:

  • Overseas companies pay for decision-making AI (e.g., directly optimizing supply chains).
  • In China, what’s hot are “showcase-ready” use cases (auto-generating PPTs, scraping data).
    And that’s telling—we haven’t even finished digitizing yet, and now we’re leaping into agents? No wonder things are going sideways.

One last gripe: Some AI startups’ demo videos look like sci-fi blockbusters. Ask about the tech details, though, and it’s all “parameter tuning + manual review.” That bubble? It’ll pop by Q2 next year.

(End)