How to build a Staff Training AI Assistant
This agent turns your manuals, SOPs, and best-practice docs into an interactive coach that answers questions, quizzes staff, and recommends next steps. It personalizes learning by role and skill gaps so teams ramp faster and retain more.
Challenge
Training content is scattered, outdated, and hard to search, so employees ask coworkers instead of finding answers. One-size-fits-all courses waste time and don’t stick, while managers struggle to track who knows what. New hires take weeks to ramp, and policy changes don’t reach the front line consistently. The result is uneven performance, avoidable errors, and higher support and onboarding costs.
Industry
Operations
Department
HR
Legal
Integrations
Anthropic
TL;DR
Turns manuals, SOPs, and docs into a friendly, interactive coach for staff.
Workflow: Input → KB lookup → LLM response (Claude 3.5 Sonnet) → Output.
Gives brief, polite responses and suggests four follow-up questions.
Includes citations and maintains consistent, friendly tone.
Quick to launch via Workflow Builder.
Common Pain Points of Staff Training
New hires spend hours digging through documentation.
Onboarding is inconsistent and poorly retained.
No conversational or guided learning format.
Hard to scale training without overloading trainers.
Knowledge base inaccessible or uncited.
What the Agent Delivers
AI coach grounded in your actual documentation.
Friendly, brief, and polite answers with follow-up prompts.
Keeps training on-brand and consistent.
Easy to update with new manuals or SOPs.
Fully deployed via Stack AI—chat-ready.
Step-by-Step Build (StackAI nodes)
1. Files Node (doc-0)
Purpose: Upload and process training docs (PDF, DOCX, TXT).
How it works: Extracts plain text for downstream AI nodes.
Safety: Only uploaded docs are used.
2. Input Node (in-0)
Purpose: User interface for questions or lesson topics.
Field: “Ask a Question or Generate Lesson”
3. Training QA (LLM) (llm-0)
Purpose: Answers “how do I…?” questions using uploaded docs.
Model: gpt-4o-mini, temperature 0.2
Rules:
Use only uploaded docs.
Always cite document + page/section.
If no match: “Not in training docs. Please check HR.”
Refuse legal, medical, or personal questions.
If confidence is low: suggest contacting HR.
Keep answers 2–4 sentences.
4. Lesson Generator (LLM) (llm-1)
Purpose: Creates short, structured lessons from uploaded docs.
Model: gpt-4o-mini, temperature 0.2
Output (Markdown):
Title
3 key objectives
5–6 step walkthrough
1 practice task
Citations (doc + page/section)
Rules: Same safety/citation standards as Training QA.
5.Template Node (template-0)
Purpose: Combines outputs of Training QA and Lesson Generator.
Format: Markdown showing both the short answer and lesson.
6. Output Node (out-0)
Purpose: Displays the final result in a clean, readable format.
Node Connections
Files → Training QA / Lesson Generator: Provide knowledge base.
Input → Training QA / Lesson Generator: Provide user prompt.
Training QA + Lesson Generator → Template → Output: Deliver final response.
Safety Practices
Only uploaded docs are used (no external data).
Every answer/lesson requires citations.
Legal, medical, or personal questions are refused.
Low confidence triggers HR referral.
If no match is found, user is directed to HR.
