Foundry-protocol – A framework for orchestrating complex tasks with AI agents (github.com)

The Foundry-protocol has been introduced as a pioneering framework designed to orchestrate complex tasks involving AI agents. This reusable structure integrates a human/AI orchestrator protocol, Claude planning, and sub-agent executors, informed by experiences from a compliance-audit project. A key feature of the protocol is its capacity for continuous improvement; lessons learned from each project—such as strategies that worked or overlooked acceptance criteria—are documented and fed back into the repository. This iterative learning process ensures that subsequent projects benefit from accumulated insights, reducing repeated mistakes and enhancing agent competence over time. For the AI/ML community, this framework is significant as it not only streamlines the task orchestration process but also promotes knowledge sharing and adaptability within AI systems. Key components of the Foundry-protocol include templates for documentation, decision-making registers, and evaluation criteria for agent autonomy, all designed to foster collaboration between humans and AI. The implementation of an autonomous cycle, human validation gates, and the recording of project memory further highlight the system's ability to adapt and learn dynamically. By codifying experiences into actionable lessons, the Foundry-protocol represents a step forward in making AI agents more effective and responsive, setting the stage for future advancements in collaborative AI technologies.