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AI agent for headteachers

Lesson Observation Feedback Cycle Agent

Every teacher observed each term with specific next steps followed up

PlanningAutomationManagementEducation
See how it worksGet access
Lesson Observation Feedback Cycle Agent: what goes in, what the agent does and what you get

What it does

School leaders observe lessons and agree development steps with teachers, but cycles drift and next steps are often too vague to check. This agent schedules observations from the timetable and leave calendar so every teacher is seen at least once a term. It collects observation notes and drafts feedback that links strengths and next steps to the school's teaching framework. It checks that each next step names a visible change; vague ones go back to the observer to sharpen. The leader approves feedback before it reaches the teacher. The agent then books a follow-up visit and checks whether the step was met; if not, it suggests coaching or training. Edge case: a teacher is on leave during the observation window, so the agent reschedules and keeps the cycle balanced across the term.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Term starts 2 USES A TOOL Pull timetable, leave calendar and last term's cycle 3 USES A TOOL Schedule observations evenly across the term 4 USES A TOOL Draft feedback from observation notes 5 CHECKS THE RESULT Are next steps specific and observable? If not: send back to observer to sharpen. Back to step4. 6 YOU APPROVE Leader approves feedback 7 DOES Schedule follow-up visit and record outcome 8 CHECKS THE RESULT Was the next step met at follow-up? If not: suggest coaching or training and book anothervisit. Back to step 7. 9 RESULT Cycle log updated
Read the steps as a list
  1. Term starts
  2. Pull timetable, leave calendar and last term's cycle
  3. Schedule observations evenly across the term
  4. Draft feedback from observation notes
  5. Are next steps specific and observable?If not: send back to observer to sharpen. Back to step 4.
  6. Leader approves feedbackThe agent waits here for your OK.
  7. Schedule follow-up visit and record outcome
  8. Was the next step met at follow-up?If not: suggest coaching or training and book another visit. Back to step 7.
  9. Cycle log updated

How it decides

It schedules evenly across the term and only accepts next steps that name an observable change.

  • Each teacher observed at least once per term
  • Next steps must describe a visible change
  • Unmet steps lead to coaching suggestions

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Observations per term
  • Framework
  • Follow-up interval
  • Feedback template

What keeps you in control

It always asks you first

  • Feedback to teachers
  • Coaching plans

Hard limits

  • Notes visible only to the teacher and leaders
  • Not used for pay decisions

It stops when

  • Done: all teachers observed
  • Stop: staffing changes, reschedule

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn autumn term, a draft next step for a Year 4 teacher said improve questioning. The specificity check failed, so the observer rewrote it as use no-hands-up questioning in the first 10 minutes. The principal approved the feedback. At the follow-up on November 20, the step was seen in 3 of 4 checks, so the agent marked it met and logged it.

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