A new agentic feedback framework uses VAL plan validator output and symbolic landmarks to refine planning domains. The researchers address the failure of LLMs to produce deployable domains from natural language alone. This approach treats space reasoning as a search in feedback space. It provides a more reliable path for generating executable symbolic domains.