llm-patterns

Build reliable LLM workflows by defining interaction patterns with explicit schemas, validation, and fallback boundaries. This approach enforces contracts across tool usage to prevent silent failures in multi-step agent tasks.

Confirmation boundaries create human-in-the-loop checkpoints for sensitive actions within multi-step agent tasks. They require explicit operator approval before critical tool usage executes, preventing irreversible automated actions.

Add observability to LLM agent workflows by implementing persistent task state, logs, and artifacts. This provides operators with continuous visibility into execution progress, tool usage, and recovery events across long-running tasks.

Yes, you can enforce stateful orchestration contracts for tool-using LLM agents. This involves specifying explicit schemas, timeouts, and fallback boundaries to govern state transitions and ensure reliable recovery.

Handle recovery and validation in complex LLM tool usage by enforcing explicit contracts across multi-step behaviors. This approach applies schemas, timeouts, and persistent state to manage failures and maintain workflow reliability.