DeepSeek's Liang Wenfeng on AGI, Restraint, and Why the Company Finally Took Capital
DeepSeek's decision to raise capital marks the end of its no-funding era and signals that even mission-driven AI labs must use equity to retain talent when competitors are poaching aggressively. Liang's candid admission that team stability was the 'biggest risk' reframes the financing as a defensive talent play, not a pivot to commercialization.
In a closed-door investor call, DeepSeek founder Liang Wenfeng detailed a stepwise path to AGI: chain-of-thought reasoning last year, agents this year, and a coming singularity where agents achieve self-iteration and continuous learning, unlocking embodied intelligence. The company maintains strict restraint, refusing to build image or video generation tools to stay focused on the AGI main line. Liang pegged the gap with the US at roughly two years, driven entirely by a 20-to-1 compute disadvantage, and predicted Nvidia's CUDA moat will erode as dedicated AI chips and domestic Chinese silicon mature.
The most revealing operational detail was the motive for DeepSeek's first-ever financing round. Liang identified team stability as the company's single largest risk and said the funding, which delivered substantial option grants, directly addressed that risk. The calculus was not about buying loyalty but about removing financial anxiety so researchers could stay focused in a relaxed, KPI-free environment.
On competition, Liang framed DeepSeek as a challenger willing to take a thinner slice of the value chain than OpenAI, betting that lower costs and comparable product quality will win. He projected that even a worst-case scenario of selling API access could sustain a public company, though B2B demand alone may take a long time to push the firm to net profitability.
Liang's framing of team stability as the company's single largest risk, and financing as the fix, reveals that even a mission-driven lab cannot ignore the market price of AI talent when competitors are offering large packages.
The explicit refusal to build multimodal generation products is a bet that AGI will subsume those capabilities later, making today's image and video tools a distraction rather than a moat.
Liang's claim that China can compete by taking a smaller share of the value chain than OpenAI is a deliberate strategy of undercutting on margin, not just on price.
The assertion that Scaling Laws have not hit a wall for DeepSeek, while Silicon Valley debates their limits, suggests the compute-constrained Chinese labs are still climbing the curve that well-resourced US labs may be plateauing on.
Treating open source as cost-free to the AGI mission assumes that commoditizing model weights does not erode any future pricing power DeepSeek might need, a bet that only works if the real moat lies elsewhere.