autoresearch

Research loops and training pipelines are orchestrated by coordinating automated hypothesis generation with curated documentation and external research. This unifies knowledge bases, codebase documentation, and experiment tracking into a single evidence-grounded workflow.

Experiment tracking with Linear integrates by managing the lifecycle of experiments from hypothesis generation directly into Linear issue tracking. This connects automated training pipelines with result synthesis to maintain a grounded research lineage.

Personal notes and repository documentation synchronization is supported through knowledge integration. It syncs insights between personal notes in Obsidian or OKF formats and codebase documentation to maintain a unified research knowledge base.

OpenWiki CLI is required to run automated discovery and prior-work audits. The integration with local documentation and OpenWiki facilitates novelty checks to ensure research hypotheses are grounded and unique.

Generating falsifiable hypotheses from a codebase is best handled by reading the repository brain and refreshing codebase knowledge. This initiates a research loop that coordinates automated training pipelines with curated documentation.

Research workflow fragmentation happens when personal knowledge bases, codebase documentation, and automated training pipelines are disconnected. Orchestration fixes this by providing a unified, evidence-grounded layer that connects all three components.