Clanker CloudAn AI employee is a software agent configured to help with a defined role in a business. The phrase might describe a research assistant, a client-update specialist, or an operations coordinator. Its usefulness comes from the job it can carry out with the instructions, information, and tools you give it.
In Clanker Cloud, the AI employee workflow starts with a custom Agent. You shape its role, personality, instructions, Skills, and available tools, then test its work. A human name or fictional background can make the interface easier to use, but those details are not real employment history or professional qualifications.
Write a role a colleague could understand
“Run operations” is too broad for a useful first brief. A better version is “Prepare the weekly client update from the current Project files, identify missing facts, and return a draft for review.”
That role has inputs, a method, an output, and a point where a person takes over. It also gives you a way to test whether the agent is helping.
For a fictional client partner called Maya, the initial brief might be:
Read the approved project brief and this week's notes. Draft a client update with progress, blockers, and next actions. Keep new requests separate from agreed scope. Cite the source for commitments. Ask when a fact is missing. Do not send the update.
The role is narrow enough to evaluate and useful enough to repeat.
Put stable instructions and changing facts in the right places
The Agent can retain a reusable method: how to structure an update, which tone to use, and what requires a question. The Project holds the current client material. A Session contains the conversation and recorded work for a particular task.
This distinction matters when the same specialist helps with several clients. A client's launch date belongs in that client's Project, not in an Agent definition shared throughout the company. See using an AI project assistant for an example of keeping the work organized.
Skills and tools have separate roles too. A Skill supplies a method; a tool performs an operation. Instructions to “check the inbox” do not connect a mailbox or establish permission to send a message.
Test the awkward case as well as the easy one
Use one example where you know the expected answer. Then try a second example with a missing date, conflicting update, or request outside the role.
For Maya, the first test could contain complete notes. The second could mention a launch date in one document and a different date in another. A good result makes the conflict visible and asks which source governs. Confidently choosing either date would hide the problem.
Check source use, completeness, and the amount of editing required. Keep a few test examples so you can rerun them after changing the instructions or tools.
Share a reviewed version
When the setup is useful, the Team library can provide colleagues with a version of the Agent definition and attached Skills. Members can add editable copies to their own Workspace. Connections, reference files, private memory, and credentials require separate setup; future versions are reviewed and added explicitly.
This is a way to share a method, not a guarantee that everyone's copy has the same data or access. The team-sharing guide explains the handoff.
An AI employee should have a clear owner in the business. That person checks the work, updates the process, and decides when the role should change. Start by giving the agent one responsibility that produces something useful this week.
Sources
Give your assistant one useful job
Describe a role, shape your Agent's instructions, and test a useful task before sharing a version with your team.