Senior Manager, Software Development, WorkSpaces for AI Agents, Applied AI Solutions

Deliver the tooling and governance layers that make agents effective and trusted. Lead the teams building the managed MCP service and forwarded tools that improve agent accuracy while reducing cost, and the security model — session isolation, agent identity, permission boundaries, audit trails, and human-in-the-loop controls — that enterprises require.

What is actually required for an AI agent to handle critical functions?

While the momentum surrounding AI and agents has been nearly unstoppable, the Hugging Face Attack has forced the industry and enthusiasts to take a step back and reevaluate. We all see tons of value in AI assistants, chatbots, LLMs, agents, and many of the other new platforms and products based off this new paradigm in technology. It's likely the individuals who read this post will continue to use them more and more. How, then, do we actually use them without opening ourselves up to real dangers? In our case, we foresaw and are continuing to see week by week that the agentic commerce space is going to be a real use case of agents. When agents are tasked with making purchases, the danger is immediately obvious: you don't want a machine to have access to your actual payment credentials. Even with payment credentials that are for a specific amount and have a purpose with the request, a responsible owner of an agent would want to manually approve transactions over a certain amount. Companies with well-defined spending policies maintain a similar protocol of large transactions requiring an approval from someone who didn't propose the purchase. Protocols like these are useful and exist within companies for good reason. There's every reason to see that this control and other external ones ought to extend to agentic work too. In agentic commerce, external safeguards like Authoryze can handle a wide array of vulnerabilities, but what about the safeguards within the agent itself? Risks still exist from attack avenues as complex as prompt injection and agent swarms or as simple as stolen login credentials and social engineering of the agent's owner. Some of these have simple fixes such as strong passwords, passkeys, and segregated access, however, some of these require advanced solutions. Tactics such as segregating responsibilities across a larger number of agents can keep individual agents siloed and ...

Best AI Agentic security tools for AI?