Agentic Research
Agentic research uses AI agents to structure and execute research workflows: decomposing questions, searching for evidence, comparing perspectives, checking claims, and producing synthesis.
Key facts
- The STORM-inspired Claude skill in [src-183] turns research quality into an agent/team-design problem with multiple lenses and explicit disagreement mapping.
Related
Evidence checked on 14 September 2026
Google reports precalculated predictions for nine billion single-nucleotide changes in a one-petabyte atlas. Its AVI score helps researchers prioritise variants across coding and non-coding regions. [src-449] Predicted molecular effects and selected research cases are not clinical validation for every variant.
OpenAI reports its supervised research-intern milestone for well-defined tasks that can take skilled humans several days. [src-455] 3.1 is runtime, not a 3.1x productivity or ROI uplift. Experiment growth is correlated with agent adoption and increased compute. Research intern is not autonomous researcher or achieved recursive self-improvement. Preliminary internal measurements; causal limitations.
Keep reading from this thread
From 500 indexed pages and articles.
- Wiki concept Multi-perspective Research Agents Split a research task across several specialised lenses, then compare disagreement and verify sources before synthesising the answer. Related by research
- Wiki concept Deep Research Workflows Use agents, retrieval, critique, source verification, and structured synthesis to produce research briefings beyond a single chat response. Related by research
- Wiki concept Agent Workflows Define repeatable handoffs, roles, artefacts, and verification steps for tool-using AI systems. Related by research