AI Coding Agent Guardrails enforced at runtime
SigmaShake — AI Agent Guardrails
What is AI Coding Agent Guardrails enforced at runtime?
SigmaShake is a runtime safety layer for AI agents that prevents unwanted tool calls before they execute. It enforces guardrails in under 2 milliseconds, meaning you can set rules like 'never delete production databases' or 'block API calls to unauthorised endpoints' without slowing down your agent. The tool works by intercepting every action your AI agent plans to take, checking it against your declared rules, and either approving or blocking it. This is useful for anyone deploying AI agents in production environments where mistakes could cause real harm. You define the rules once, and SigmaShake applies them consistently across all agent interactions.
Key Features
Runtime action blocking
Intercepts and prevents destructive tool calls before execution
Declarative rule engine
Write rules in plain language to specify what agents can and cannot do
Sub-2ms latency
Guardrails run fast enough for real-time agent operations
Audit logging
Records every agent action attempt, successful or blocked
Deterministic enforcement
Rules apply consistently without randomness or variance
Pros & Cons
Advantages
- Prevents costly mistakes by stopping dangerous actions at runtime rather than after the fact
- Low performance overhead; sub-2ms latency means minimal impact on agent speed
- Freemium pricing model allows small teams to start without upfront cost
- Clear audit trail for compliance and debugging when agents behave unexpectedly
Limitations
- Requires upfront effort to define rules; poorly written rules may block legitimate actions or miss actual risks
- Limited to tool-call level enforcement; cannot prevent issues that happen within a tool itself
- Specific pricing for paid tiers and limits on free tier not clearly documented
Use Cases
Protecting production databases from accidental deletion or modification by autonomous agents
Enforcing API access restrictions so agents cannot call unauthorised external services
Auditing financial or healthcare-related agent decisions for compliance purposes
Running customer-facing chatbots safely by restricting what systems they can access
Sandboxing experimental AI agents during development before wider rollout