See what ReacherX △ Agent is doing

Check what △ Agent remembers

The Memory tab lets you inspect saved knowledge and instructions. Look at the source, status, and supporting information. A direct instruction from you carries different meaning from a lesson inferred by the system.

A confidence number is the system's assessment, not a guarantee. Ask whether the memory is supported and still relevant to the current workspace.

If you recently changed your audience or product, look for instructions that no longer apply. Tell △ Agent what should replace them, then check the saved result. This guide gives examples of useful corrections.

Follow the activity behind a result

The page includes Overview, Discovery, Quality, Memory, and Activity tabs. Activity records can lead to details about an event, an evaluator run (an automatic quality check), or a memory suggestion.

Those distinctions help when you're investigating learning. An event happening, a lesson being suggested, and a memory being promoted (a suggestion turned into a saved instruction) are separate steps. A suggested lesson hasn't necessarily become an instruction △ Agent will use.

You can filter the view and use the date range to narrow the investigation. If something failed, record the visible reason and what you were doing before retrying. That makes a useful bug report.

Use the two dashboards together

Start with Analytics when you want to review outcomes and work waiting for you. Use Agent observability when you want to inspect how that work happened.

For example: Analytics shows few qualified people. Discovery shows broad searches. A person's qualification explanation shows missing evidence. Together, those details give you a more useful question to ask than “Why is AI bad today?”

If you need help interpreting a result, join Discord and describe the workspace's purpose and the record you inspected. Share a redacted screenshot. Developers can continue with how the reporting system works.