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The AI assistant test: 12 capabilities to verify before you buy

A vendor-neutral test for memory, scheduling, tools, permissions and auditability—based on a real workflow rather than a feature-page checklist.

A glowing chatbot avatar opposite a professional at a laptop, with checklist, email, code and timer icons between them.

TL;DR

  • Start with one repeatable workflow and a known baseline.
  • Verify memory, scheduling, tools and channels with real inputs—not a staged demo.
  • Test permissions, approval, cancellation, failure handling and the audit record.
  • Measure setup, review, correction and successful completion before deciding whether the assistant saves work.

“AI assistant” can describe a chat interface, an application copilot, a workflow builder or an agent that acts across systems. Product labels do not tell you whether a tool fits your work. A controlled trial does.

Choose one recurring job with a clear successful result. Record how long it takes today, which accounts and files it touches, what requires approval and what a serious failure would look like. Then test these twelve capabilities.

Context and continuity

1. Recall after time has passed. Give the assistant a decision and its rationale. In a new session several days later, ask for both. Note whether it recalls accurately, retrieves irrelevant material or invents missing details.

2. Distinguish similar entities. Use two contacts or projects with overlapping names. Confirm it asks when the target is ambiguous.

3. Apply preferences without overriding instructions. Store a real formatting or communication preference, then provide a task-specific exception. The current instruction should win.

Scheduling and channels

4. Run a scheduled task. Configure a small recurring job and verify timing, output and what happens after the device or runtime was unavailable.

5. Maintain continuity across supported channels. Start in one channel and continue in another. Check which context follows and which capabilities differ by channel.

6. Notify without auto-sending risky work. A draft, reminder or status update is safer than an unreviewed external message. Confirm the approval boundary explicitly.

Tools and files

7. Work with a real document. Use a non-sensitive test file. Verify read, edit, save location and format preservation rather than accepting a summary as proof of file handling.

8. Use the web with traceable inputs. Ask for current research and require source URLs, dates and clear separation between source facts and inference.

9. Handle an authenticated service. Test the minimum permission level first. Confirm which account is connected and whether read and write access can be separated.

10. Stop and recover. Cancel a running task, provide a correction while it is working and verify that partial output or side effects are understandable.

Control and evidence

11. Respect permission and approval settings. Try an action outside the granted scope. The assistant should refuse or request approval, not silently broaden its access.

12. Produce a useful activity record. Inspect what ran, which tools were called and what changed. A log helps review work; it does not prove that the work was correct.

Score the workflow, not the demo

For each attempt, record setup time, active human time, review/correction time, successful result, failed result and any unwanted side effect. Compare those totals with the original baseline after several repetitions.

Brainmox supports persistent memory, scheduling, web/desktop/Telegram/Slack access, file and browser tools, Google Workspace services, configurable Mission Control approvals, cancellation and audit history. Some capabilities vary by runtime, channel and permission. A buyer should still run the same test rather than treating this list as proof that every workflow is a fit.

See Brainmox’s current capabilities →

Use the printable AI assistant evaluation scorecard →

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