Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo David Melamed is Head of Emerging Technologies at Torq. He joined through Torq’s acquisition of Jit, which he co-founded and led as CTO since 2020, building agentic security on a production Context Graph. A cloud security veteran with 20+ years of experience, David previously held senior technical roles at Cisco (via the CloudLock acquisition) and MyHeritage.

AI coding agents are changing the pace of software development. With tools like Claude Code, developers can move from idea to implementation faster than ever, generating code, exploring unfamiliar repositories, refactoring services, and turning plain-language intent into working software. That speed is powerful. But speed without governance = risk. It also creates a new challenge: how can you govern what an AI agent builds, suggests, and pulls in from the internet?

Agent skills are the newest piece of plumbing quietly making its way onto developer machines. They're easy to install, they get to call into the user's tools on the agent's behalf, and once they're in place they tend to stay in place. While auditing the popular installer vercel-labs/skills, we saw several ways a bad actor can make the tool install something other than what the user thought they were installing.

Least privilege is foundational. It's been a core security principle for decades, and it's no less relevant in agentic AI environments. An agent shouldn't hold permissions beyond what its task requires, and remediating over-permissioned agents is one of the highest-value quick wins available to any agentic AI security program. But here's what the security industry has been slow to acknowledge: correctly implemented least privilege still isn't sufficient.

The Trump administration has spent much of its second term removing regulatory constraints on AI development. On June 2, it added one back voluntarily and carefully. Earlier this week, President Trump signed "Promoting Advanced Artificial Intelligence Innovation and Security" after months of internal debate, a last-minute pull of the signing in May, and a compressed final timeline. The result of this tumult is an order that strikes a deliberate balance.

Most enterprise teams already run some form of workflow automation. The question is whether it can hold up when an AI step makes decisions within the chain, an auditor asks for a trail, and three teams need to build on each other's work without stepping on governance. That is where consumer-grade tools and enterprise-grade platforms part ways. The gap is architectural, not a feature lag, which is why it cannot be retrofitted.