AI Coding Assistant for CS Courses

1. From virtual TA to coding assistant, you decide

CodeGrade's AI assistant lives inside the environment where students write and run their code. Students ask it questions while they work, and it responds based on rules you set. The same model, the same assignment, wildly different outcomes depending on how you configure it.

Want a virtual TA that never writes code, only asks guiding questions? Write that into the system prompt. Want a coding assistant that helps debug and explains errors? Configure it that way instead. You set the rules per assignment, so the AI fits your teaching goals.

Configure the assistant per assignment via a system prompt
Three assistant types: Learning, Feedback, and Coding
Range from "never write code" to full coding help, your call

CodeGrade's AI assistant asking guiding questions instead of writing the solution.

Configuring CodeGrade's AI assistant: assistant type, guardrail level, and system prompt per assignment.

2. Content guardrails and full visibility into every conversation

Content guardrails add a safety layer on top of your system prompt. Three levels: Standard Safety blocks harmful content. Privacy Protected also masks student PII. Exclusive Educational also blocks off-topic discussions, prevents prompt injection, and stops jailbreak attempts.

Every student-AI conversation is visible in the Assistant Chat tab. You can see exactly what the AI told your students, whether it followed your rules, and where students got stuck. Ban AI and students use it where you cannot see it. Give them a sanctioned assistant with rules you set, and the help-seeking stays inside your course, visible.

Three guardrail levels: Standard Safety, Privacy Protected, Exclusive Educational
All conversations visible to instructors in the Assistant Chat tab
Guardrails work on top of your system prompt, not instead of it

3. The assistant reads the student's actual code

The AI assistant has full file context. It reads all files in the editor: Python, Java, JavaScript, Jupyter notebooks, quiz questions, everything. When a student asks "why isn't my code working?", the assistant sees their actual code and gives a relevant answer, not a generic one.

This means the AI can reference specific lines, explain errors in context, and guide students through their actual assignment, not a textbook example.

Full file context: reads .py, .js, .java, .ipynb, and all other files in the editor
Answers are grounded in the student's actual code, not generic advice
Part of the AI add-on; your first course includes it free

Instructor reading a student's AI assistant conversation in CodeGrade.

Give every student feedback that actually helps.

Inline comments, peer code feedback, and an AI assistant that works on your terms. All in one place.

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Frequently Asked Questions

Can instructors control what the AI assistant tells students?

Yes. Instructors configure the AI assistant per assignment. They choose from three assistant types (Learning, Feedback, or Coding), set custom system prompts, and pick from three guardrail levels to control how much help the assistant provides. This prevents the AI from giving away solutions when the goal is learning.

Can instructors see what students ask the AI assistant?

Yes. Every conversation between a student and the AI assistant is fully visible to instructors. This gives you insight into where students are struggling and whether they are using the AI to learn or trying to shortcut the assignment.

Does the AI assistant have access to the student's code?

Yes. The AI assistant has full context of the student's files in the editor. This means it can give specific, relevant help based on what the student has actually written, rather than generic advice. Instructors control the type and depth of help through custom system prompts, and use guardrail levels to prevent prompt injections and misuse.

Is the AI assistant available on the free plan?

The AI assistant is an add-on to paid plans. Every new user's first course runs on the full environment free, and that includes the AI assistant, so you can experience it with your own students before any budget conversation.

What is the difference between the three AI assistant types?

The Learning assistant helps students understand concepts without giving direct code answers. The Feedback assistant reviews submitted code and suggests improvements. The Coding assistant provides more hands-on help with writing code. Instructors pick the type that matches the assignment's learning goals.

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One place inside Canvas, Blackboard, Moodle, or Brightspace where students write and run real code, get instant feedback, and use AI on your terms. And where you see all of it.

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