How an AI agent can prepare a course-aware learner support response
This workflow gives an AI agent a defined job, a bounded set of records, and a result a person can review. The agent reads the relevant Heights Platform context and matches it with Gmail, applies the rules in the prompt, and keeps the source behind every recommendation. It returns a proposed handoff rather than taking consequential actions on its own.
Can an AI agent prepare a course-aware learner support response?
Yes. Start with the scope, date range, decision rules, and fields that identify the right records. The agent can collect the evidence, compare states or sources, mark conflicts and missing data, and organize the result around the outcome above. A reviewer then checks the matches and judgment calls before approving messages, record updates, bookings, purchases, publishing, or other write actions. The guide below shows the records, boundaries, prompt, and handoff needed for this specific workflow.
Match the learner and course
Gmail supplies the learner’s wording and prior support context. Heights Platform supplies enrollment, course version, lesson structure, and permitted progress context. Match by verified identity and name the thread. Limit access to the course involved.
Example starter prompt
Review Gmail thread [link/query] and Heights Platform context for learner [reference] in course [course/version].
Identify the exact question, relevant lesson or requirement, available progress evidence, and any content or access issue. Draft a concise reply with direct course links and steps. List any proposed course correction separately. Do not send, change progress, or expose other learner data.Avoid assumptions about the learner
Incomplete progress does not explain why someone is stuck. Use only the evidence needed to answer the question. If the course itself is inconsistent, acknowledge the issue and route it to the course owner rather than blaming the learner.
Check that every link in the draft points to the learner’s current Heights Platform course version and permission context. Do not send a staff-only or other-cohort resource.
Expected handoff
Return the support summary, course evidence, reply draft, unresolved access or content issue, and proposed internal follow-up. A support owner approves the message and any course changes.
Questions this workflow answers
Could an agent draft a helpful answer to a learner by checking the actual course path instead of sending a generic support reply?
Yes. Gmail supplies the learner’s message, thread history, attachments, and exact wording. Heights Platform supplies the relevant course, module, lesson, enrollment, and available progress context. The agent matches the sender to the correct learner and course only when identity and scope are clear, then checks the requested step against the published learning path.
The response should separate an access problem, content question, progress issue, and request for personal guidance. A learner who cannot open a lesson may face enrollment, prerequisite, publishing, or browser conditions; the agent should report what the platform shows and avoid guessing. If the question asks for advice beyond the course material, route it to the instructor rather than inventing an answer.
Ask the agent to cite the lesson or setting behind its draft and to preserve the learner’s privacy. Progress does not establish motivation, ability, or personal circumstances. Keep other learners’ records, internal notes, and restricted course content out of the email. When the course itself appears inconsistent, create an internal issue separately instead of exposing speculation to the learner.
The handoff includes the support summary, verified course evidence, draft reply, unresolved question, and proposed owner action. A support specialist confirms identity, tone, and the intended course behavior before sending. Any enrollment change, progress reset, content edit, or refund stays outside the draft. The learner receives a specific next step grounded in the course they are taking, while the team retains a separate record of the underlying platform or content problem.
If the agent finds that instructions and platform behavior disagree, the learner reply should focus on the safe immediate path while an internal ticket preserves the broader defect. That avoids asking the learner to diagnose the course or exposing unconfirmed implementation details.