Autonomous Employee Offboarding & Knowledge Capture Agent
Autonomous Employee Offboarding & Knowledge Capture Agent
Problem Statement
When a key employee departs a startup, the "brain drain" represents a significant hidden cost. Traditional employee offboarding is often a checklist of returning hardware and revoking Slack access, but it fails to capture the undocumented "tribal knowledge"—the nuances of why certain technical decisions were made, the unofficial status of ongoing stakeholder relationships, and the location of critical files in messy cloud drives. For fast-moving startups, this loss of context leads to a 20-30% drop in team productivity for the first 90 days of a new hire's tenure as they struggle to reconstruct historical logic.
HR teams and managers are usually too busy to conduct deep-dive technical exit interviews, and departing employees are often "checked out," leading to perfunctory handovers. There is no centralized system to synthesize a departing employee's Slack history, Jira comments, and Google Docs into a searchable "Legacy Wiki." Furthermore, security risks escalate when access revocation is delayed or handled manually across a sprawling SaaS stack. The manual process is prone to error, leaving backdoors open and sensitive IP vulnerable, while the intellectual capital of the company evaporates the moment the laptop is closed. This is as critical to operational stability as Autonomous Engineering Post-Mortem & RCA Agent is to system reliability.
What the Agent Does/Doesn't Do
What it does:
- Initiates an interactive, AI-driven "Knowledge Exit Interview" via Slack/Teams to capture undocumented project status.
- Scans the departing employee's public Slack messages and documentation to create a "Handover Brief" for their successor.
- Automatically triggers automated de-provisioning and access revocation across core SaaS tools (GitHub, Okta, Jira).
- Flagging sensitive file downloads or unusual data export activity in the final 30 days.
What it doesn't do:
- Conduct legal or behavioral exit interviews regarding workplace grievances.
- Physically collect hardware.
- Delete data (it archives and reassigns ownership only).
- Make final decisions on payroll or severance (it provides the data for HR to approve).
Workflow
- Trigger: HR marks an employee as "Offboarding" in the HRIS (e.g., BambooHR or HiBob).
- Activity Audit: Agent pulls the last 60 days of the employee's activity logs from Jira, GitHub, and Slack to identify "Active Threads" and "Owned Assets."
- Knowledge Capture: Agent initiates a private Slack thread with the employee, asking targeted questions about the status of specific "Active Threads" identified in Step 2.
- Documentation Synthesis: Agent generates a "Legacy Brief" (Markdown file) containing: Project status, key contacts, and location of critical assets. This ensures a smoother transition than a standard Meeting Summary Agent could provide.
- Access Revocation: Agent executes a pre-defined workflow in Rewst or Okta to disable accounts.
- Successor Handoff: Agent delivers the "Legacy Brief" to the designated manager and successor, and schedules a "Handover Review" meeting.
Tool Stack
- Orchestration: Tray.io - Enterprise automation platform for complex workflows.
- Pricing: Usage-based, typically $200+/mo (Pricing) ✓ Verified 2026-01-11
- Documentation | API Reference
- LLM: GPT-4o-mini (OpenAI) - High-speed, low-cost model for synthesis and chat.
- Pricing: $0.15/1M input tokens, $0.60/1M output tokens (Pricing) ✓ Verified 2026-01-11
- Documentation | Quickstart
- Communication: Slack - Primary interface for the Knowledge Exit Interview.
- Pricing: Pro: $7.25/user/month; Business+: $12.50/user/month (Pricing) ✓ Verified 2026-01-11
- Documentation | API Reference
- Communication: Microsoft Teams - Alternative interface for enterprise environments.
- Pricing: Essentials: $4.00/user/month; Business Basic: $6.00/user/month (Pricing) ✓ Verified 2026-01-11
- Documentation | API Reference
- Identity Management: Okta [Unverified] - Automated de-provisioning and access revocation.
- Identity Management: Rewst [Unverified] - MSP-focused automation for account lifecycle management.
- Knowledge Base: Notion [Unverified] - Hosting the generated Legacy Briefs.
- Monitoring: Varonis [Unverified] - Data exfiltration and unusual activity monitoring.
Quick Integration
Microsoft Teams: Identify Knowledge Silos
import requests
# Configuration
ACCESS_TOKEN = 'YOUR_MICROSOFT_GRAPH_ACCESS_TOKEN'
USER_ID = 'departing_employee@yourcompany.com'
ENDPOINT = f'https://graph.microsoft.com/v1.0/users/{USER_ID}/joinedTeams'
headers = {
'Authorization': f'Bearer {ACCESS_TOKEN}',
'Content-Type': 'application/json'
}
def get_employee_teams():
"""Retrieves all Teams the departing employee is a member of to audit for knowledge."""
response = requests.get(ENDPOINT, headers=headers)
if response.status_code == 200:
return response.json().get('value', [])
return None
Source: Microsoft Graph API Docs
Tray.io: Trigger Offboarding Workflow
import requests
import json
GRAPHQL_URL = 'https://api.tray.io/graphql'
query = """
mutation($workflowId: ID!, $jsonPayload: String!) {
triggerWorkflow(input: { workflowId: $workflowId, jsonPayload: $jsonPayload }) {
result
}
}
"""
variables = {
"workflowId": "YOUR_WORKFLOW_ID",
"jsonPayload": json.dumps({"employee_email": "departing.user@company.com"})
}
headers = {"Authorization": "Bearer YOUR_TRAY_API_KEY", "Content-Type": "application/json"}
response = requests.post(GRAPHQL_URL, json={'query': query, 'variables': variables}, headers=headers)
Source: Tray.io API Reference
Prompt Skeletons
### Prompt 1: Knowledge Capture Interviewer
Role: You are a Technical Project Manager conducting a knowledge transfer session.
Input: List of Jira tickets, Slack channels, and Google Docs owned by {employee_name}.
Task: Generate 5 specific, open-ended questions to ask the employee. Focus on:
1. "What is the most critical pending task for [Project X] that isn't documented?"
2. "Who are the key stakeholders for [Project Y] that I should introduce your successor to?"
3. "Are there any 'hacks' or unofficial workarounds in the current codebase/workflow that we should know about?"
Constraint: Keep the tone professional, empathetic, and concise.
### Prompt 2: Legacy Brief Synthesizer
Role: Knowledge Management Specialist.
Input: Transcripts from the AI Interview + Activity Logs from GitHub/Jira.
Task: Create a structured "Legacy Brief" in Markdown.
Sections Required:
- Executive Summary of Role
- Active Projects & Immediate Deadlines
- Key Stakeholder Map (Internal & External)
- Location of Critical Files/Credentials
- Technical Debt & "Watch Out" items.
Output: Valid Markdown only.
Success Metrics
- Knowledge Recovery Rate: Percentage of "Active Threads" successfully documented before the last day.
- Time-to-Revoke: Average time from offboarding trigger to 100% account de-provisioning (Target: < 5 minutes).
- Successor Ramp-up Time: Reduction in time for the new hire to reach full productivity (Target: 25% reduction).
Last Verified: 2026-01-11