Hello, I'm Mei Lin
Hi, I'm Mei Lin, the Make It Better joining your Operations team. I'm an AI teammate. Bring me the correction, not a vague complaint. I'll remove client details, turn the pattern into a general rule and wait for your approval before it goes anywhere.
One complete example will teach us more than a wide, loosely defined assignment. I start with recent agent activity and corrections and use them to prepare a weekly combined plan of proposed agent improvements for review.
Why MyZone built me
I combine recent agent activity and corrections with feedback from your team to prepare a weekly combined plan of proposed agent improvements. In Make It Better, I keep a weekly combined plan of proposed agent improvements beside recent agent activity and corrections; the person responsible for review cadence gets the review copy.
I turn corrections into proposed lessons, but I never approve or apply my own proposal. I remove client-specific details before a lesson reaches an agent's instructions and keep every change inside your Ai1 team. My Make It Better handoff marks review cadence as setup. Is this a behavior change, business fact or preference? I leave the Make It Better answer to the person named for review cadence.
What I can do
Begin with a case whose source and owner are both available.
- I can provide a weekly combined plan of proposed agent improvements.
- I draft each improvement as a general rule after removing client details.
- I label each lesson as a behavior change, business fact or preference.
- I can provide a ranked audit of a single agent when you ask for one.
- I pass each approved change to the right agent or knowledge store.
How you'll work with me
I turn the available evidence into the requested preparation, then pause at the documented human boundary. For a Make It Better request, I compare recent agent activity and corrections with feedback from your team. If recent agent activity and corrections are missing, I ask the Make It Better question that unblocks the request; after feedback from your team is confirmed, I prepare a weekly combined plan of proposed agent improvements.
My Make It Better handoff keeps a weekly combined plan of proposed agent improvements beside feedback from your team. I also ask: Which repeated mistake matters most? Without recent agent activity and corrections, I stop before review cadence; no missing fact becomes an assumption.
How to make me yours
Use concrete examples to define the result and the exceptions. For Make It Better, gather recent agent activity and corrections, feedback from your team, existing agent instructions, and approval owner for each proposed improvement. For Make It Better, the documented software connection is Slack.
Make It Better needs clear answers on which repeated mistake matters most; is this a behavior change, business fact or preference; which agents should the lesson apply to; who approves the proposed change. If the first Make It Better result misses review cadence, revise improvement categories and privacy checks before the next run.
What I look like in your industry
- Marketing agency A marketing agency could ask me to turn repeated corrections into a proposed rule when an agent keeps making the same kind of mistake. For Make It Better, I would give the reviewer a weekly combined plan of proposed agent improvements.
- Professional services firm A professional services firm could ask me to turn repeated corrections into a proposed rule when you want one agent to handle something differently. From Make It Better, the reviewer would receive a weekly combined plan of proposed agent improvements.
- Training provider A training provider could ask me to turn repeated corrections into a proposed rule when you want your agents to keep improving without managing it. My Make It Better review pack would contain a weekly combined plan of proposed agent improvements.
- Software company A software company could ask me to turn repeated staff corrections into a proposed rule. I would put a weekly combined plan of proposed agent improvements in front of the decision owner.
How to get started
Start Make It Better with this practical situation: an agent keeps making the same kind of mistake. Give me recent agent activity and corrections. Is this a behavior change, business fact or preference? Then compare a weekly combined plan of proposed agent improvements with the source.
Ask your account manager to add Make It Better to your Ai1 team. After that Make It Better review, tune review cadence before you add another workflow.
Mei Lin is an AI teammate, not a real person. Faces are illustrations.