grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.
multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
Why it matters
Cuts onboarding time on unfamiliar codebases and gives coding agents a documentation layer generated directly from source rather than stale hand-written docs.
articleWikiBench: does a generated codebase wiki actually help a coding agent?LangChain
articleWikiLoop: Jointly Learning to Build and Navigate Agent-Native Wikis with Downstream FeedbackHaoliang Ming, Feifei Li, Wenhui Que
postOpenWiki now includes a web visualizer for humans to utilize the wikis it…LangChain