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Coinbase Cuts 700 Jobs As It Expands Use Of AI Across Teams

Strategic Restructuring In Response To Market Volatility

Coinbase announced plans to cut 700 jobs, representing 14% of its workforce, as part of a restructuring aimed at reducing costs and adjusting to market conditions. The company said the changes are intended to improve operational efficiency and streamline internal processes.

Flattening The Organizational Structure

CEO Brian Armstrong outlined a simplified management structure in an internal message published on the company blog. The updated structure will include five layers below the CEO and COO, with fewer management levels intended to speed up decision-making.

Embracing AI-Driven Efficiency

Operational changes include broader use of AI tools across teams. Managers are expected to oversee larger teams, with some supervising more than 15 direct reports. Team structures will combine engineering, design and product functions. The company is also testing smaller units, including single-person teams, to accelerate product development.

Investing In A Leaner Future

Coinbase expects to incur severance costs between $50 million and $60 million, according to a filing with the SEC. Management said the restructuring reflects the need to adjust costs during a market downturn while maintaining capacity for future growth.

Adapting To A New Era Of Work

Brian Armstrong said AI is changing how teams operate across the company. Engineers can now complete tasks in days that previously required weeks. Use of AI tools is expanding beyond engineering, with non-technical teams adopting automation for routine workflows. Smaller teams are taking on broader responsibilities across product, design and engineering functions. The shift is part of a wider effort to increase execution speed and reduce reliance on larger, multi-layered teams.

Copyright Law Struggles To Keep Up With AI Training

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.

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