AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Working, tested LangGraph implementations of the seven agentic design patterns from Anthropic's
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Working, tested LangGraph implementations of the six agentic design
patterns from Anthropic's "Building Effective
Agents":
five fixed workflows (prompt chaining, routing, parallelization,
orchestrator-workers, evaluator-optimizer) and one open-ended agent
loop (ReAct) — plus a seventh, human-in-the-loop, extending the agent
loop with the approval-gate mechanism every current production agent
architecture treats as required infrastructure, not optional.Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Working, tested LangGraph implementations of the six agentic design
patterns from Anthropic's "Building Effective
Agents":
five fixed workflows (prompt chaining, routing, parallelization,
orchestrator-workers, evaluator-optimizer) and one open-ended agent
loop (ReAct) — plus a seventh, human-in-the-loop, extending the agent
loop with the approval-gate mechanism every current production agent
architecture treats as required infrastructure, not optional.Read the full README ↗