Zero Bureaucracy, Better AI: DeepSeek's Winning Formula

In early 2025, DeepSeek stunned the technology world. This relatively unknown Chinese AI lab demonstrated that world-class AI models could be built and run for a fraction of the usual cost. Their V3 model not only matched the performance of leading systems but did so by turning a constraint—limited access to high-end hardware and computing power—into a competitive advantage. DeepSeek's advances threaten to upend the economics of the AI industry, which had largely relied on NVIDIA's powerful but pricey chips. Within days, NVIDIA's market value plunged by $600 billion as investors confronted a future where expensive hardware may no longer be essential.

Much has been written about DeepSeek's technical innovations. Far less attention has been paid to the company’s unconventional management practices, which were instrumental in enabling algorithmic breakthroughs. Here are three distinctive elements, which I pieced together from Chinese media coverage and other sources like the excellent ChinaTalk:

1. Lean Management

DeepSeek has stripped away the machinery of traditional corporate control—management layers, fixed roles, KPIs, and rigid processes. "DeepSeek is entirely bottom-up," explained founder Liang Wenfeng in a rare interview last year. "We generally don’t predefine roles; instead, the division of labor emerges organically."  

Without the burden of performance metrics or rigid deadlines, researchers focus on discovery rather than arbitrary targets. Teams form spontaneously around promising ideas, with individuals collaborating across boundaries based on shared interests. Former research intern Zihan Wang notes, "Even with 200 people, everyone is unique—there’s no standardization where people become interchangeable cogs."

Knowledge flows horizontally rather than top-down. When teams make progress, they share their insights openly, enabling colleagues to quickly grasp changes and their implications. This transparency eliminates the need for management oversight while accelerating innovation. As Wang observes, "You can understand what’s happening in minutes and how it affects your role." Even DeepSeek’s office layout reflects this philosophy. Meeting rooms have two separate entrances and open doors, a deliberate design choice to encourage serendipitous interactions. 

"Innovation requires minimal intervention and management. It needs space to experiment and the freedom to make mistakes. True innovation often emerges spontaneously—it can’t be forced or planned."
— Liang Wenfeng, founder of DeepSeek

2. Freedom to Experiment

At DeepSeek, anyone with an idea gets immediate access to the resources needed to test it. Researchers can use the company’s specialized AI processors without approval, allowing them to validate new concepts within hours. To ensure this autonomy is exercised productively, hunches are quickly tested against the latest baseline model, with rigorous documentation ensuring others can understand and build on successful experiments.

The company's breakthrough Multi-Head Latent Attention (MLA) architecture began with a young researcher questioning how AI models process information (Instead of having AI store multiple complete copies of information as it works— like ten people each taking full notes in a meeting—the idea was to create a single compressed version everyone could reference, allowing AI to run faster, handle longer conversations, and use less computing power.)

Rather than requiring layers of approval, DeepSeek immediately assembled a team to explore the concept. The result was an architecture that slashed memory requirements by 90% and made advanced AI dramatically cheaper to run. Ideas like MLA advance not through internal competition but through their value to the collective effort. As Wang notes, "Everyone contributes their own ideas to the final model. When an idea proves useful, everyone celebrates together."

3. Impact Over Credentials

While most AI companies chase veteran researchers, DeepSeek prioritizes academic ability, curiosity, and drive to transform the world through AI.  “Many of our team members have unconventional backgrounds,” explains Liang. “Their desire to do research often comes before making money."  Unlike other AI labs that prize industry veterans, DeepSeek discounts industry experience and the mental models that come with it. The company typically passes on candidates with more than eight years' experience. As Liang puts it, “We need people who are extremely passionate about technology, not people who are used to using experience to find answers. Real innovation often comes from people who don't have baggage.”

This talent philosophy has spawned novel roles like the "know-it-all data whisperer." These positions seek candidates with broad knowledge spanning anime, games, literature, and culture. One researcher describes lunchtime conversations ranging from Chinese historical dramas, gaming strategies, and global pop culture—these intellectual collisions spark the kinds of unexpected connections that fuel innovation.

DeepSeek is the latest example of how, in a world of hyperkinetic change, resources matter less than resourcefulness. While tech giants throw massive computing power and experienced talent at AI development, DeepSeek achieves more through an organizational model that amplifies collective creativity. This, as Liang notes, is the least replicable—and most important—source of competitive advantage:

"We anchor our value in our team—our colleagues grow through this process, accumulate know-how, and form an organization and culture capable of continuous innovation. That’s our moat."

Time will tell if DeepSeek can preserve this organizational DNA as it grows. But one thing's for sure: building exceptional artificial intelligence requires creating environments where people are free to pursue exceptional accomplishment.