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This is where a store gets its content and stays current: you capture knowledge through interviews, consolidate it by working with Clara, and keep it accurate by tracking signals.

Interviews

Interviews are the primary way knowledge gets into a store. The most valuable expertise is rarely written down, and the people who hold it rarely have time to document it. So instead of asking them to write, you create an interview on a topic and assign it to the person who knows it best. Clara conducts the conversation asynchronously and in the contributor’s own language: she follows up where an answer is thin, moves on where it’s solid, and lets people pause and come back whenever it suits them. The Interviews list shows what’s outstanding so you can see coverage at a glance. A completed interview is raw input, not finished knowledge. Once answers come in, you consolidate them by working with Clara. The way Clara interviews is shaped once at the organization level through shared context and reusable templates, see Organization settings.

Work with Clara

Work with Clara is where raw input becomes consolidated knowledge. Captured knowledge is rarely clean: interviews overlap, sources disagree, and important context is missing. In a session, Clara reads new interviews and sources against the current artifacts, surfaces contradictions and gaps rather than guessing, and proposes concrete edits to your artifacts. You steer every change; Clara handles the analysis and the mechanical work. Come here whenever new input needs consolidating, a process has changed, or signals have piled up and you want to fold them in.
Work with Clara vs Chat and Task. Work with Clara changes the knowledge (adjusting how you answer an RFP after a policy shift). Chat and Task use it as it stands today (asking a question about the policy, or actually filling the RFP).

Signals

A store is only useful while it stays accurate, and accuracy decays. Signals are how it keeps up: a signal is anything that should prompt an update, a correction, a gap, drift, or new context worth capturing. A signal can come from anyone, anywhere, the moment they notice the knowledge is out of date or incomplete: from an AI client using the Clarifeye skill, from a chat or a task, from inside Clarifeye, or from an expert who simply knows a policy changed. They all land in one place so nothing is lost. What a signal points at depends on the use case. When the store is context for an implementer, on an ERP migration for instance, signals mostly flag missing information the implementer needs to move forward. When the store is used directly through Chat, Task or an AI client, they more often surface something that needs the project owner’s attention: a rule that changed, an answer that was wrong, a decision nobody has taken yet. Signals are an input, not the change itself. Take them into Work with Clara to turn each one into a concrete update to your artifacts or sources; when closing a gap needs fresh expertise, a signal can trigger a new interview. Keeping the store current is the most important ongoing job, so encourage everyone to leave a signal whenever something looks off.