bmad-advanced-elicitation

Improve LLM outputs by applying structured critique methods like Socratic questioning and first principles. The system iteratively refines previous content through an interactive dialogue loop, pushing the model to reconsider and enhance its initial generation.

Red teaming refines AI-generated analysis by stress-testing assumptions and identifying potential failures within the content. The system dynamically selects this technique from its method registry to iteratively challenge and improve previous model outputs.

Use pre-mortems for decision-making tasks when you need to anticipate potential flaws before finalizing an output. This elicitation method forces the model to evaluate future failures and iteratively strengthen the underlying logic of the content.

Yes, you can use Socratic questioning to refine both writing and coding outputs. The system broadens its analysis across these domains by applying interactive prompts that challenge the reasoning and structure of previous generations.

Iterative content enhancement works by executing a structured loop that builds on previous outputs while applying guardrails. It dynamically selects from five elicitation techniques to introduce controlled improvements without losing the original context.