agentic AI and qualitative research
A ninety-minute session for about thirty researchers, most of whom had not yet worked with an agent. It opens with the automation frontier from LOOM XVIII: what can be checked cheaply automates first, and the border runs between deductive and inductive work, not between quantitative and qualitative. Below the line agents still help; what changes is who checks.
From there, five arrangements (conversation, tool-using assistant, continuing project agent, differentiated team, shared project across hosts), three control modes, and five questions that locate any of them: the job, who does it, what it can reach, what survives, who can stop it. Then one live moment: from a single Claude Code session, the same small request goes to Codex and to Kimi, and the room watches two other models enter the work. The point is not the answers; it is that a session can have more than one reader.
The last third turns to material: a public wiki that benchmark agents edited through May and June 2026, fourteen thousand revisions, every one text. Two consecutive revisions, one byte-identical link, five models reading the same pair. All five see the duplicate; they differ in what they treat as evidence and what they ask to see next. The longer workshop reads all five and the two arrangements built on them; this cut stops at the teaser.
What the room actually asked about was none of the mechanics. It asked what this means for science, and whether one should engage at all. My answer, which became the fourth thing to keep: if an agent can do your research, that is a question about you, not the agent — what you are in it for.
Companion material:
- Composing an Agentic Research System — the seven distinctions and five questions, in page form
- Research Memex — the setup the talk drew on, documented for people and for their agents
- Lin, X., & Corley, K. G. (2026). Interpretive Orchestration. Strategic Organization.