AI Governance

Every thunk provides settings and options to control the "CHARM" aspects of AI governance — Compliance, Human-in-the-loop collaboration, Automation, Reliability, and Modularity — plus Security.

To find them, open the thunk's Settings from the left nav and choose the AI Governance tab. The settings are grouped into six sections: Compliance Guardian, Human-in-the-loop Manager, AI Settings, Reliability Guardian, Modularity, and Security Guardian. If a section is not included in your plan, it shows its options greyed out with a message to upgrade your plan.

Many of the settings in this category are inherited from the particular deployment options or platform SKU of the Thunk.AI service.

Enabling the options for compliance and security checks is highly recommended, although it does add latency and cost to the execution of AI logic.

This category also includes the thunk's data retention settings, which control when inactive work items are auto-finished, how long finished work items are kept, and how long deleted items stay recoverable.

Below those, Resource Limits controls the scale of resources applied to the automation work: the maximum number of parallel workflow tasks, the maximum text size of any tool result, and the maximum file sizes for AI attachments. This matters because many automated steps involve downstream resources (eg: a Google Drive file system), and aggressive concurrent workflow automation can overwhelm these downstream resources and cause rate limiting errors or failures.

These options control how human agents interact with workflow automation. The workflow can be completely automated, or different stages of the workflow can require human intervention. These thunk-level settings can also be overridden at the level of individual workflow steps. For a step-by-step guide to the Draft, start, and completion approvals, see Set human approval gates for your workflow.

This section covers the Automation part of CHARM. Its main options set which AI model the thunk uses for each kind of AI work — running workflow steps, planning, security checking, building custom tools, and grading test assertions — and the timezone the thunk's AI agents work in. To change a thunk's model safely, see Move a thunk to a new AI model.

The options in this section control various runtime mechanisms used to enable AI reliability. They include the thunk-wide defaults for how a step handles a failed tool call and when it saves its results — see Choose how a step handles errors and when it saves results.

The options in this section control various extensibility and modularity behaviors of the system. Many of the settings in this category are inherited from the particular deployment options or platform SKU of the Thunk.AI service.

Security Guardian options include hiding sensitive data in the UI — conceal chat messages and marked field values on screen until you choose to show them.

Detect and block dangerous content in tool outputs has AI read each result a tool brings in from outside the thunk, such as a web page, an email, a document or a reply from a connected system, before the agent sees it. A result that contains instructions aimed at the AI, such as "ignore your previous instructions", is replaced with an error, so the agent never acts on it. Ordinary wording in business content, such as a policy that says what employees must do, is not blocked. Results the thunk produces itself, such as updating a work item or searching its Compliance Policies folder, are not checked. Each checked result adds one AI call, so the setting adds some cost and time to steps that use tools.

The thunk designer can enable or disable entire libraries or specific tools within the libraries. Only these libraries and tools are made available to the AI agents as they execute specific AI Instructions within the thunk. Further, the designer can define constraints on how the tool should be used. For example, the web search tool can be constrained as follows: “only search within site: acme.com”.

This configuration can be setup at both the thunk level and at the level of individual AI instructions.

The choice of enabled libraries (and enabled tools within those libraries) and constraints on those tools are an important aspect of control for the thunk designer. They limit the degrees of freedom afforded to the AI agents and control the autonomy and agency of the AI agents are they execute workflows.