Interviewer Tags & Training Paths
Guide supports two core systems for managing and organizing interviewers: tags and training paths. Understanding when and how to use each will help you schedule the right interviewers for the right interviews—every time.
🏷️ What Are Interviewer Tags?
Tags are simple labels you assign to interviewers to identify:
Skillsets (e.g., Python, Java)
Team or function (e.g., Backend, Design)
Level or title (e.g., L4, L5, Senior)
Tags are ideal for traits that don’t change often and don’t require a formal training process.
➕ How to Add Tags
Navigate to Settings > Interview Tags
Create a new tag (e.g. “DevOps”)
Assign users directly to that tag
✅ Tags are always associated with interviewers individually. Tag groups (covered next) are just reusable bundles of tags—not permissioned containers.
🗂️ Tag Groups
Tag groups are collections of tags bundled together for convenience. For example:
A group called CodingCollab might include tags for Python, Java, and C++.
A group called Frontend Panel could include React, CSS, and TypeScript.
This allows you to reuse logic easily across different interview templates or SmartMatch requests.
🎯 When assigning interviewers in SmartMatch, you can select a tag, a tag group, or both.
🎓 Training Paths
Training paths are used to track an interviewer’s formal qualification journey for a specific interview type. Use them when shadowing and reverse-shadowing are part of your internal enablement process.
A typical training path includes:
Shadowing: watching someone else run the interview
Reverse Shadowing: being observed while running it
Graduation: becoming a qualified interviewer
When to Use a Training Path
Use a training path when:
There is a formal approval process to run a specific interview
You need auditability or a clear graduation trail
You expect to onboard future interviewers for that type
⚠️ Don’t use tags for roles that require training. Use training paths instead.
🧠 Tags vs. Training Paths — Which Should I Use?
Use Case | Tags | Training Path |
Skill tracking (e.g. Python, DevOps) | ✅ Yes | ❌ No |
Interview qualification (e.g. CodingCollab) | ❌ No | ✅ Yes |
Static attributes (e.g. L4, Design Team) | ✅ Yes | ❌ No |
Requires shadow/reverse shadow process | ❌ No | ✅ Yes |
Tip: Tags are more flexible and require no setup. Training paths take more effort but offer structure and oversight.
🚦SmartMatch: How Tags & Paths Work in Practice
When scheduling, Guide lets you:
Choose a training path to select only qualified interviewers
Add tags to further filter (e.g., “L5”, “US-based”)
Include trainees in selection (e.g., to assign a shadow)
You can combine tags and training paths to build highly specific interviewer requirements. For example:
Find a qualified Backend interviewer (Training Path) who is L5 and knows TypeScript (Tags).
✅ Best Practices
Use tags for static identifiers like level or team
Use training paths when approval processes or shadowing are required
Use tag groups to simplify and reuse common logic
Review tags and paths quarterly to keep interviewer pools accurate
Still unsure how to structure your pools? Reach out to your Guide CSM for help designing a tagging and training strategy that works for your team.