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This is the first model release since the company called for pacing the frontier, which means keeping safety practices ahead of model capabilities.

Teams already use AI to write code, generate tests and summarize pull requests. The next step is to use it deliberately in secure software development.

While synthetic data is widely perceived as the ideal approach for protecting data in AI/ML environments, real-world usage trails far behind expectation.

To achieve accurate cost tracking, organizations must connect token spend directly to work units.

There are three questions we keep hearing from engineering leaders this year, whether directly, in conversations at conferences, or in the subtext of the pitches landing in our inbox. What is this actually costing us. Are we testing it well enough to ...