CompanyClaude

Anthropic invests $100M to train 10,000 engineers

Original title: Anthropic invests $100 million to train 10,000 engineers and tackle the enterprise AI talent gap

Plain language

What it is: Anthropic launched the Claude Frontier Academy, investing 100 million dollars to train 10,000 engineers by the end of 2027. The program aims to address the shortage of skilled talent capable of implementing AI in businesses.
How it works: Selected engineers participate in a program modeled after medical residencies. They learn from experts, practice on realistic business cases, and manage a real Claude project at their own company for 12 weeks with support from Anthropic.
Where it is available: The program is available in San Francisco, New York, and London. Organizations can nominate their engineers through their Anthropic account team or partner manager.
Example: An engineer from Novo Nordisk can participate in the program to manage a Claude project within the company's medicine research and development workflows.

What it is: Anthropic announced the Claude Frontier Academy and its Frontier Deployed Engineer Residency program. The initiative aims to train 10,000 software engineers to deploy Claude in enterprise environments.
How it works: Engineers undergo a multi-day in-person training with Anthropic engineers, complete a simulated enterprise deployment, and pass a practical exam. They then complete a 12-week residency managing a production Claude use case at their organization.
Where it is available: The cohorts are currently running in San Francisco, New York, and London. Eligible organizations can nominate software engineers who have experience building with LLMs.
Example: A software engineer from Commonwealth Bank of Australia can join the residency to build and secure Claude applications for banking systems.

The headline and explanation on this page are based on Anthropic's post. The full details are in the original.

Anthropic invests $100 million to train 10,000 engineers and tackle the enterprise AI talent gap