Agentic AI
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Artificial Intelligence & Machine Learning
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Black Hat

Rain Capital’s Chenxi Wang on Why Closed AI Models Risk US Competitiveness

Tom Field (SecurityEditor) •
August 6, 2026    

Chenxi Wang, founder and general partner, Rain Capital

Mythos-class models now let attackers strike at machine speed, overwhelming traditional human-paced defenses. Security teams must respond with equally fast, machine-scale artificial intelligence defenses, said Chenxi Wang, founder and general partner of Rain Capital.

See Also: Why an AI Harness May Matter More Than the Latest Model

That urgency, Wang said, extends to national AI policy. As the United States weighs open- versus closed-weight model development, restricting open models won’t stop their spread, she said. “If we don’t allow open-weight models, somebody else will build them,” she said.

Her solution: Keep working with the world’s best researchers and technologists, the same approach that built America’s tech dominance in the first place.

In this video interview with ISMG at Black Hat USA 2026, Wang also discussed:

Why university research labs are becoming pipelines for AI startup unicorns;
How human checkpoints are giving way to full agent autonomy;
Why founder capabilities outweigh market timing in AI investing.

Wang identifies and invests in cybersecurity, AI and infrastructure startups while advising founders on product strategy, go-to-market execution and growth. She has more than 20 years of cybersecurity experience and previously held leadership roles at Twistlock, Forrester Research and Intel Security.