Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Every major technological shift reshapes the landscape, creating both winners and losers. AI will be no different. The key question is which companies are positioned to capture the value it generates, and which ones may fall behind as it unfolds. If you look at previous technology shifts, the winners were not always the companies building the most visible products. They were often the ones that enabled the shift to happen in the first place, or those that benefited from the structural changes it created.

Boris Kurktchiev is a Field CTO at Teleport, known for his expertise in Zero-Trust identity solutions for cloud and AI, and for his contributions to the CNCF's Cloud Native AI working group. Doyensec dropped a piece last week called The MCP AuthN/Z Nightmare, and I think anyone deploying MCP in production needs to read it.

We built 1Password Unified Access to extend identity security beyond humans to the agents and machine workloads operating across your business. In practice, that means securing not just who gets access, but how agentic systems connect to tools, services, and data.

What happens when a $29 billion company forgets to rename a model ID, and what it means for every organization using open-source AI. On March 19, 2025, Cursor, the AI-powered coding tool valued at $29 billion and generating an estimated $2 billion in annual recurring revenue, launched Composer 2, its newest and most powerful coding model.

In AI systems, PII detection is the first step. Not the most glamorous step. But the one that, when it fails, takes everything else down with it. Identifying sensitive data (names, Social Security numbers, financial records, health information) has to happen before any of it reaches an LLM. Get this wrong, and you’re looking at one of two bad outcomes: Traditional DLP systems could afford to be aggressive with detection. LLMs can’t. They depend on full context to generate correct outputs.