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Former Anthropic Researchers Raise $200M for AI Startup Mirendil to Automate AI Engineering

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Why it matters

Mirendil, a San Francisco startup founded by former Anthropic researchers Behnam Neyshabur and Harsh Mehta, has raised $200 million at a $1 billion valuation to build self-improving AI models that autonomously perform AI engineering work. The seed round, co-led by Andreessen Horowitz and Kleiner Perkins with participation from NVIDIA, ranks among the largest in AI history. Mirendil plans to use the capital to develop neural networks that automate tasks currently requiring manual effort—data preparation, debugging, hyperparameter optimization—in frontier AI model development.

Neyshabur and Mehta departed Anthropic in December 2025, less than a year after joining the lab. The company has not yet shipped a product. Specific details about the technical approach and timeline remain undisclosed.

The funding reflects a broader bet that AI systems capable of automating their own research cycles could disrupt the current dominance of well-resourced frontier labs. Mirendil's stated goal is to compress research cycles from months of human work into days of automated iteration, potentially enabling universities and research institutions to build and refine AI models without dedicated machine-learning engineering teams. For attorneys tracking AI governance and competitive dynamics, this signals accelerating consolidation of AI research talent into new ventures and growing investor confidence that self-improving systems will materially advance scientific discovery in biology and materials science within the next two to three years.

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