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James Berthoty (@JamesBerthoty) on X
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James Berthoty (@JamesBerthoty) on X

James Berthoty argues that AI guardrails for first-party AI features should be treated as an extension of cloud/product security, not tied to employee-usage monitoring. Guardrails (prompt injection defense, content filtering, goal alignment) are available from AI security vendors, gateways, frontier providers and SDKs. He recommends deploying in-depth guardrails through developer SDKs or an existing cloud runtime/CADR provider, because those see what happens on the workload (such as a prompt injection leading to workload takeover, or the files a malicious MCP call wrote). Dedicated AI security vendors offer an integrated policy engine and deeper AI red-teaming, but they are usually run by internal IT rather than cloud/product security teams.

TL;DR Berthoty: treat first-party AI guardrails as cloud/product security (SDK or runtime tooling), separate from IT-run employee AI usage controls.

Organisations named here

  • James Berthoty

Technologies named here

  • AI Security tools/vendors
  • AI guardrails
  • Developer tools / SDK-deployed guardrails
  • Cloud application detection and response tools
  • Cloud runtime security provider
  • AI gateways
  • Model Context Protocol

Techniques named here

  • Prompt Injection
  • Malicious MCP call
  • Workload takeover following prompt injection
  • Network inspection-based guardrails
  • API-based guardrail integration
  • AI red-teaming
  • Content filtering