Improvement Agent: Your AI Team Learns From Your Corrections

Your AI agents learn from your corrections, with your approval on each change.

The Improvement Agent is the AI agent feedback loop in the Ai1 platform by MyZone AI: each week it reads the corrections and feedback your AI agents received, turns repeated ones into clear instruction improvements with client details removed, and applies each change only after you approve it.

We'll show you the Improvement Agent on your own AI agents. Nothing is applied until you approve it.

Plans & pricing

  • Fewer repeat mistakes

    When staff correct an agent for the same thing again and again, the lesson becomes a lasting rule instead of a note nobody reads.

  • Agents that get sharper over time

    Your agents improve from what really happens in your business rather than staying fixed at their first setup.

  • You decide every change

    Each proposed update comes to you in one readable plan, and nothing is applied until you say yes.

  • One lesson, shared where it fits

    A fix learned by one agent can reach the other agents it applies to, and only those.

Get to know Mei Lin

Mei Lin reads what your agents are learning and turns it into real improvements, one approval at a time. She is patient, thoughtful and loves a small change that makes a big difference.

AI agent. Fictional persona; not a real person.

Mei Lin, the persona of the Improvement Agent
NameMei Lin W.
RoleImprovement Lead
Experience26 years
Work historyQuality improvement manager at a hospital group
Operations excellence lead at an electronics maker
PersonalityPatient, one step at a time
Based inSingapore, Singapore

Why Mei Lin has a personality

AI does better work as a specific expert, so the Improvement Agent works as Mei Lin (Improvement Lead, Singapore, Singapore). You can rename Mei Lin or change the personality, experience and profile settings at any time.

Why our agents have personalities

The Improvement Agent in short

Last updated · Reviewed by the MyZone AI team

The Improvement Agent at a glance
ReviewsWhat your agents did, the corrections they got and your team's feedback, every week
Sorts each lessonA behaviour change, a business fact or a preference for one agent
Client detailsStripped out of every rule, then checked again
Requests in SlackPicked up straight away, not held for the weekly review
On requestA ranked audit of one agent, without changing anything
What it never doesApply a change, or approve its own proposal, without you

What the Improvement Agent does for you

  • Reviews feedback across your AI team

    Each week it reads what your agents have done, the corrections they received and the feedback your team left, so useful lessons are not lost.

  • Turns feedback into clear proposals

    Groups similar corrections together and writes each one up as a single, concrete improvement.

  • Sorts each lesson to the right home

    Decides whether a lesson is a behaviour change for an agent's instructions, a business fact for your shared knowledge or a small preference for one agent.

  • Keeps client details out of instructions

    Rewrites every behaviour change as a general rule with no client names, project names or specific figures, then checks it again.

  • Handles requests from your team straight away

    When someone asks in Slack for an agent to work differently, it picks that up at once instead of waiting for the weekly review.

  • Audits a single agent on request

    Reviews one agent's instructions, conversations, hand-offs and corrections and ranks what would make it safer, faster or cheaper, without changing anything.

How the Improvement Agent differs from a feedback log

A feedback log collects corrections and nobody reads it. The Improvement Agent reads it for you each week, groups repeated corrections, labels each lesson as a behaviour change, a business fact or a preference and rewrites behaviour changes as general rules with client details removed. You get one plan, approve each change yourself, and every approved lesson goes only to the agents it fits.

How this differs from the Continuous Improvement Agent: the Continuous Improvement Agent tests changes to your business processes, while the Improvement Agent audits and improves your AI agents themselves and only recommends, with every change yours to approve.

From your request to a finished result

It runs inside your Ai1 system and works in the tools you already use. You ask, it works, it reports, and it stops for your OK where it matters.

How the Improvement Agent works: you ask through the Comms Hub and Ai1 runs the steps: read, distil and sort, clean up, your approval and apply. It works with Slack. You approve at: your approval. It returns a weekly combined plan.
Tap the diagram to enlarge it

Step 1: Read

Goes through each agent's recent activity, corrections and feedback since the last review.

Step 2: Distil and sort

Groups the signal into distinct improvements and labels each as a behaviour change, a business fact or a preference.

Step 3: Clean up

Rewrites behaviour changes as general rules with client details removed, and checks them before moving on.

You approve

Step 4: Your approval

You get one combined plan to review and approve or decline, change by change.

Step 5: Apply

Each approved change is passed to the right place: the agent's instructions, your shared knowledge or that agent's memory.

Hand these situations to the Improvement Agent

Illustrative photo: the managing director of a logistics firm asks the Improvement Agent for help from their phone.
Illustrative photo. Ask in plain words how an agent should work differently.
  • An agent keeps making the same kind of mistake
    It spots the pattern in the corrections and proposes a rule that fixes it, for you to approve.
  • You want one agent to handle something differently
    Ask in Slack. It confirms the plan with you and applies the change once you agree.
  • You want your agents to keep improving without managing it
    It reviews feedback every week and brings you a single plan to accept or decline.
  • Staff corrections are piling up with no effect
    It turns that backlog into specific instruction updates, so the corrections finally count.

What you get

  • A weekly combined plan of proposed agent improvements
  • Each improvement written as a general rule with client details removed
  • Every lesson labelled as a behaviour change, a business fact or a preference
  • A ranked audit of a single agent when you ask for one
  • Approved changes passed to the right agent or place

What it won't do

  • Edit an agent's instructions itselfHandled by: The agent concerned, once you approve
  • Write to your shared knowledge base directlyHandled by: A person on your team
  • Build new agents or move existing onesHandled by: The Agent Manager
  • Approve its own proposalsHandled by: You

Example: agent improvement audit

Example with a fictional company. Names, people and figures are invented to show the agent's output. Any resemblance to a real company or person is unintended. Industry facts are real and cited with their sources.

What it was asked: Our tenant enquiry agent has been live for three months: tell me what would make it safer, faster and cheaper, ranked, without changing anything yet.

Example report
Four headline numbers for a tenant enquiry agent, five biggest opportunities, and a table of what the audit reviewed in full, sampled or did not review.
Executive summary and what was reviewed
A ranked table of six recommendations with category, evidence grade, impact, risk, confidence and effort scores, a priority score, likely owner, first safe action and success metric.
Top recommendations, ranked
A table tracing five learning loops from signal to later check, marked broken, partial, noisy or working, beside a bar chart of the reasons conversations were handed to staff.
Learning loops and handoff reasons
Three cards covering security notes, tests to add before any change and work already in progress, then the decision waiting for the client and two cited security references.
Safety notes, tests and next steps

What it found: 3 findings, with the numbers

  • The agent sends arrears reminder emails with no person checking them: 64 went out in 30 days, and in 2 of 120 chats read, text a tenant pasted changed the wording.
  • About half the handoffs to staff were avoidable: 214 of 612 happened only because the agent cannot see the repairs calendar, and 88 more because the answer was missing from its handbook.
  • Staff left 41 corrections in the feedback inbox, but none reached the agent's instructions, so 17 of them repeat the same three mistakes. A weekly review with a test per fix closes the loop.

Read-only audit, run the way Make It Better audits any agent: instructions, workflows and skills read in full; all 1,860 conversations counted and 120 read in full; every handoff record, staff correction and cost record traced. Findings are graded Verified, Corroborated or Inferred and scored Impact + Risk + Confidence minus Effort; the rent payment system and email settings were not reviewed, and nothing was changed. Run date: .

Sources

  1. LLM01:2025 Prompt Injection, OWASP Gen AI Security Project (accessed )
  2. LLM06:2025 Excessive Agency, OWASP Gen AI Security Project (accessed )

Want an agent audit like this for your own AI agents? Book an Improvement walkthrough.

Book an Improvement walkthrough

It asks before it acts

Every Ai1 agent works under human approval. Here is how the Improvement Agent keeps you in control.

  • Nothing is applied automatically. Every proposed instruction change needs your approval, and it never approves its own proposals.
  • Client names, project names and specific figures are stripped out before any lesson goes near an agent's instructions, and a second check runs before it moves on.
  • Changes stay within your own Ai1 team. Nothing is shared outside it.
  • A lesson is only sent to the agents it applies to.

Part of Ai1, by MyZone AI

Trusted by leaders at Plastic Bank, Outback Team Building, RMG Advertising, Keeran Networks, and Titan Training Centre.

No analysis or aggregation of your conversations.

How we keep your data safe

Your data, your server

Your data belongs to you, and it is stored on your own server.

How we keep your data safe

Frequently asked questions about the Improvement Agent

How do you improve AI agents from feedback?

Collect the corrections your team gives, group the repeated ones and turn each into a clear rule in the agent's instructions. The Improvement Agent in Ai1 by MyZone AI does this weekly, strips out client details and brings you one plan to approve change by change.

That is an AI agent feedback loop: the corrections and comments your team gives an agent are collected, turned into clear improvements and fed back into how that agent works.

Who approves changes to an AI agent's instructions?

You do. The Improvement Agent proposes each instruction update in a combined plan, never approves its own proposals and passes an approved change only to the agents it applies to.

A fix for one agent changes all of them only if it truly applies to all of them, and even then it comes to you for approval first.

How often does the Improvement Agent review feedback, and could client details leak into instructions?

It does a full review once a week and brings you one combined plan. Requests your team sends in Slack are handled straight away rather than waiting for the weekly review.

Client details do not end up in instructions. Each behaviour change is rewritten as a general rule without names, project details or specific figures, and checked again before it is sent anywhere.

How is the Improvement Agent different from the Continuous Improvement Agent?

The Continuous Improvement Agent runs capped, reversible experiments to test what works better.

The Improvement Agent learns from the corrections and feedback your agents already received and turns them into instruction updates, one approval at a time.

About Ai1

Do I get just the Improvement Agent, or the whole platform?

The whole platform. The Improvement Agent is not sold on its own: every Ai1 agent, including this one, is included on Developer Pro and every Fully Managed option, with no per-agent charge. Developer Core includes the development agents. Compare plans

Two paths, one platform. Build it yourself on a developer plan, or let our team run your AI operations for you. Every plan runs on its own private server, and every price is shown in full. See Ai1 pricing

More about Ai1: security, setup time

Put the Improvement Agent to work

See the Improvement Agent turn your team's corrections into better instructions.

We'll show you the Improvement Agent on your own AI agents. Nothing is applied until you approve it.

Plans & pricing

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