How to build an AI Course Assistant
This agent answers student questions about a specific university course by searching across course documents, Google Drive, and SharePoint, then generates a concise, well-formatted answer.
Challenge
Answering student questions eats up valuable faculty and admin time. It requires digging through syllabi, schedules, and policies to give accurate responses, pulling focus from teaching and engagement.
Industry
Education
Department
HR
Integrations
Anthropic
Google Drive
TL;DR
What it does:
This agent answers student questions about a specific university course by searching across course documents, Google Drive, and SharePoint, then generates a concise, well-formatted answer. It can also create a task in Asana based on the AI’s response.
Who it’s for:
- University students in the course 
- Course instructors or TAs managing student queries 
- Academic support staff 
Time to value:
Immediate—students get instant, context-rich answers to course questions, and staff can automate follow-up actions (like creating tasks).
Output:
A markdown-formatted answer to the student’s question, citing course materials and knowledge bases, and (optionally) a new task on a workload management platform with the answer as its title.
Common Pain Points For Onboarding Students
- Students struggle to find up-to-date, relevant information across multiple document sources (syllabus, schedules, exams, etc.) 
- Answers to logistical or deadline questions are buried in different platforms (Google Drive, SharePoint, etc.) 
- Manual triage and follow-up actions (like creating tasks) are time-consuming for staff 
- Inconsistent or incomplete responses due to fragmented knowledge 
What This Agent Delivers
- Unified search across course documents, Google Drive, and SharePoint 
- AI-generated, concise, and friendly answers tailored to student questions 
- Consistent formatting and citation of sources 
- Automatic creation of follow-up tasks (e.g., for unresolved or important queries) 
- Reduced manual workload for instructors and support staff 
See the Agent in Action:
Step-by-Step Build (StackAI nodes)
1) Student Question
What it does:
- Receives the student’s question as text input 
Goal:
- Capture the user’s query to drive the rest of the workflow 
2) Course Documents
What it does:
- Searches a curated set of course files (syllabus, exams, schedule, etc.) for relevant information 
Goal:
- Provide authoritative, course-specific context for the AI’s answer 

3) Google Drive
What it does:
- Searches connected Google Drive for additional course-related content 
Goal:
- Expand the context pool to include any relevant files stored in Google Drive 
4) SharePoint 2
What it does:
- Searches connected SharePoint for course materials 
Goal:
- Ensure no relevant information is missed, even if stored in SharePoint 
5) Anthropic
What it does:
- Receives the student’s question and all retrieved context from the three knowledge bases 
- Generates a brief, polite, and conversational answer, citing sources as needed 
Goal:
- Synthesize a high-quality, student-friendly response using all available information 

Instructions
Prompt
6) Template
What it does:
- Formats the AI’s answer and the original question in a clear, markdown-styled output 
- Adds a note that the answer was generated using course documents and knowledge bases 
Goal:
- Ensure the response is easy to read and consistently branded 
7) Create Task
What it does:
- Creates a new task in Asana with the AI’s answer as the task name 
- For example, to track follow-up or escalate complex questions 
- Can be changed to suit your course's workload management platform 
Goal:
- Automate administrative follow-up, reducing manual work for staff 
8) Answer
What it does:
- Presents the formatted answer to the student/user 
Goal:
- Deliver the final, polished response 






