Announcing MCP Toolbox Java SDK v1.0: Agentic data access for the enterprise
cloud.google.com·6d ago
Cloud & Infrastructure
The New Stack·Aug 6·5 min read
Your AI agent’s next tool call may be valid but wrong. AWS’s Dogwood promises to fix that.
TL;DR
AWS has launched Dogwood, an open-source policy language that allows developers to manage AI agent tool calls in context, improving decision-making. This tool enhances the existing Cedar language by considering previous actions in a workflow.
✦ Why It Matters
Start using Dogwood to enhance your AI agent's decision-making capabilities today.
Key Takeaways
- Implement Dogwood to manage sequences of AI agent actions effectively.
- Ensure event histories are complete and trustworthy for accurate authorization.
- Utilize temporal conditions to enforce rules based on past actions.
- Transition existing Cedar policies to Dogwood without rewriting them.
How It Works
Dogwood allows developers to define policies that consider the sequence and timing of actions taken by AI agents. It uses temporal conditions to evaluate past events, enabling more complex decision-making processes.
For instance, it can check if a previous approval was granted before allowing a sale, thus ensuring compliance with business rules.