Terry Zhu in Conversation with Yao Xin: In the AI Era, the Biggest Competitive Edge Isn't Technology — It's Speed of Evolution | Booming Talk EP05

蓝驰创投蓝驰创投··2·0

Know the mistake, be willing to fix it, fix it fast.

In the AI era, code is getting cheaper, but organizations are getting more expensive.

As model capabilities keep spilling outward and Coding Agents take over more of the work that once required team collaboration, startups may need to rethink not just their products, but the organization itself: why does a company exist, how does division of labor happen, and how should founders define their own roles?

In this episode of BoomingTalk, Terry Zhu, Managing Partner at BlueRun Ventures, and Xin Yao, Founder & CEO of PPIO, sat down for a deep conversation. The two started with OPC, AI Native organizations, Agents, and multi-agent systems, and went on to discuss the cognitive boundaries of founders, organizational evolution, and what truly scarce capabilities look like in this wave of AI transformation.

Sixteen years ago, BlueRun invested in Xin Yao's PPTV. After leaving PPTV, Xin Yao joined BlueRun as a venture partner. Now, BlueRun has invested in Xin Yao's second venture, PPIO.

When Xin Yao was a venture partner at BlueRun, Jui and Terry always told him: we should pay attention not just to what is happening now, but to what will happen in the future — knowing the long-term trends and the key drivers behind them. This conversation is a serious interpretation of that "trend."

If technology will eventually diffuse and tools will eventually democratize, then what ultimately creates distance may not be who plugged into models earlier, but who can adjust their cognition faster, restructure their organization, and complete their evolution.

The conversation started with OPC, but the focus wasn't on the concept of "one-person companies" itself — it was on the organizational shift behind it: when AI starts taking on more and more work that previously required team collaboration, why should companies still exist in the same way they always have?

From there, the discussion extended to AI Native organizations. For truly AI-native companies, AI isn't a bolt-on tool — it's infrastructure that reshapes products, collaboration, and decision-making from the ground up. Teams burdened with legacy systems and old processes, by contrast, are more likely to be slowed down by new paradigms.

On this foundation, the two also discussed multi-agent systems. Rather than a "universal model," what may be closer to real industrial environments is a set of Agents with clear division of labor, mutual coordination, and mutual verification. When planning, execution, review, and feedback are re-decomposed, the way organizations work and their collaboration interfaces will change accordingly.

And beneath all these changes, the same question ultimately remains: in the AI era, the greatest competitive advantage isn't technology itself, but speed of evolution. For entrepreneurs, code is increasingly approaching a supply that can be rapidly generated. What's actually becoming scarcer is the ability to handle context, memory, workflows, and problem definition. In other words, the future competition won't just be about "who can write more code," but who can organize intelligence at higher quality.

This also means AI isn't just rewriting organizations — it's rewriting the founder. What truly creates distance between people and between companies isn't technical background or tool proficiency, but whether one can continuously correct their cognition, move beyond old experience, and rapidly complete self-iteration.

For this reason, what BlueRun has consistently paid attention to has never been just "who is using AI," but "who is changing their way of working, organizing, and judging because of AI."

01:56 AI-Era Entrepreneurs: Core Capabilities and Iteration Logic

  • Core criterion at the bottom: self-awareness — the founder determines the organization's ceiling
  • Entrepreneur's three stages: knowing you're wrong, willing to change, changing fast — iteration speed determines company scale
  • Sensitivity to AI frontiers and technical understanding; product taste; ability to make differentiated experience trade-offs; hands-on experience at leading tech companies or in frontier scenarios; no wrapper apps

10:21 AI-Native Organizations: From Coding Agent to Paradigm Restructuring

  • Technical inflection point: end of 2025 when large models' coding capabilities explode; enterprises enter all-hands Coding Agent era; small teams of 10 can rewrite 5 years of Unix history in 3 months
  • AI-native organizations restructure around business context as the core, building Agent context, memory, and toolchains to create productivity gaps
  • Two paths for enterprise transformation: old and new systems run in parallel — maintain legacy systems, develop new systems AI-natively
  • Transformation attitude: not selling anxiety, but must embrace change

21:59 Technology Trends and Practice: Multi-Agent and Agent Infrastructure

  • Technical direction: from single Agent to multi-Agent collaboration; solving hallucination, improving stability; commercial viability depends on robustness and delivery capability
  • Infrastructure: Agent-driven cloud infrastructure upgrades to high elasticity, millisecond-level fluctuation, fragmented scheduling; architecture moves toward cloud brain + local execution, balancing security and efficiency

55:37 Practical Implementation: Enterprises, Investment Institutions, and Individuals

  • Inside enterprises: all-hands Agent usage, cross-department hackathons, deep efficiency gains for non-technical roles
  • Investment institutions: BlueRun establishes AI Lab, skill-ifying experience, restructuring workflows
  • Individuals: knowledge distillation, building AI avatars, improving decision efficiency; next-generation opportunities belong to young people without baggage, daring to be first, with 10,000 hours of passion

  • Legacy: Historical legacy systems, hard to update, hard to adapt to AI
  • Robustness: The ability to produce stable results, avoid errors, and withstand complex scenarios
  • Self-awareness: A founder's ability to see their own strengths and weaknesses and rapidly self-iterate
  • Frontier scenarios: Exploring, stumbling, and accumulating firsthand knowledge at the cutting edge
  • ZPC: Zero People Company, corresponding to OPC
  • Hybrid: "Mixed" or "hybrid"; in the podcast, refers to a mixed, half-new-half-old, transitional state
  • Sensor: In multi-agent architecture, a metaphor for the role/module that helps AI acquire external information, business context, and environmental data — equivalent to AI's "sensory organs"
  • Pinterest: Well-known American visual inspiration and image search platform

"Code is increasingly like basic supply; what's truly scarce is how to organize context."

"AI doesn't rewrite one job — it rewrites the entire organization's collaboration model."

"All-hands coding agent — not just developers, but the entire function, including the CEO."

"A founder I know, with 11 people, is preparing to completely rewrite the company's systems from the past five years in 3 to 6 months."

"How far an organization can ultimately evolve depends on how far the founder can evolve."

"The greatest competitive advantage in the AI era isn't technology — it's speed of evolution."

"Code isn't worth much anymore; writing code has become something that can be scaled."

"Will Agents have taste?"

"Knowing you're wrong, willing to change, changing fast — that's the difference between a $1 billion founder and a $100 billion founder."

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