Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
Guardrail cost comes from traffic, policy upkeep, review time and tool metering. Here is how to size each driver and ask vendors the right questions.
Track owner coverage, time to assign and age of exposure. Be wary of raw asset counts, finding totals and risk scores with no method behind them.
Attack surface management finds assets your scanners never knew about. Feed its output into scanning, ownership and patch workflows, and measure the chain.
You can build a basic attack surface inventory from DNS, certificates and cloud APIs. Buy when scale, upkeep and ownership workflows outgrow scripts.
AI detection and response is a young category. A small team can start in 90 days: inventory AI use, log model and tool activity, then write response steps.
Year one guardrail mistakes for AI agents and delivery: block mode on day one, prompts as controls, no owner, no exception path. And the fix for each.
Trial agent and delivery guardrails in report mode first, then enforce on one team. Use constructed test cases and score blocks and overrides.
Plain definitions for terms people mix up around AI agent and delivery guardrails: policy, gate, sandbox, scope, proxy, approval and agent identity.
A 90 day plan for a small team to put guardrails on AI agents and delivery pipelines: inventory, least privilege, logging, approvals and a first review.
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