Insights tagged ‘AI Security & Trust’
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Why AI models hallucinate
In September 2025, OpenAI published a paper that said something the AI industry already suspected but hadn’t quite articulated. The paper, “Why Language Models Hallucinate”, authored by Adam Tauman Kalai, Ofir Nachum, Santosh Vempala, and Edwin Zhang, didn’t just catalogue the p…
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Claude Opus 4.6 just shipped agent teams. But can you trust them?
Anthropic shipped Claude Opus 4.6 this week. The headline features are strong: a 1M token context window (a first for Opus models), 128K output tokens, adaptive thinking that adjusts reasoning depth to the task, and top-of-the-table benchmark scores across coding, finance, and l…
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Tooling around: letting agents do stuff is hard
There is a messy reality of giving AI agents tools to work with. This is particularly true given that the Model Control Protocol (MCP) has become the default way to connect AI models to external tools. This has happened faster than anyone expected, and faster than the security a…
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How Claude Code and Cowork talk to your other systems
Anthropic’s products have become the most aggressive movers in the race to connect AI to the messy sprawl of software that runs modern businesses. Claude Code talks to GitHub, Sentry, Postgres, and Jira. Cowork reads your local files, pulls data from your CRM, and drafts message…
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Security for production AI agents in 2026
Note: This article represents the state of the art as of January 2026. The field evolves rapidly. Validate specific implementations against current documentation. This article is for anyone building, deploying, or managing AI-powered systems. Whether you’re a technical leader e…
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AI governance: between the committee and the catastrophe
Every large organisation deploying AI currently faces two failure modes. Moving too slowly by requiring extensive committee approvals and detailed risk assessments causes the technology to become outdated before it can deliver results. Conversely, moving too quickly by allowing …
