AI Context Playbook

AI Context Playbook

AI Context helps your organization define shared business language so responses are more consistent and actionable.

What to Put in AI Context

Add durable, high-reuse information such as:

• KPI definitions used in your business
• Line, area, and shift naming conventions
• Product-family and SKU grouping rules
• Quality defect taxonomy and reason codes
• Escalation thresholds used in meetings

Think of AI Context as your operating glossary, not a daily log.

Best Content Types

You can add:

• Text entries for definitions, rules, and standards
• File-based references for stable lookup material
• Image references where visual context matters
• Voice notes transcribed into reusable text context

Choose the format that makes upkeep easiest for your team.

Writing High-Quality Context Entries

Use this structure:

1. Term or policy name
2. Exact business definition
3. Scope (which plant/line/team it applies to)
4. Exceptions or edge cases
5. Last review owner

Short, explicit entries outperform long narrative notes.

Example Entries

• "Planned downtime excludes sanitation windows between 2:00-2:30 AM."
• "Line naming standard: PlantCode-LineNumber (P3-L2, P3-L3)."
• "First-pass yield is calculated before any rework."

Governance Model

Use lightweight ownership:

• Assign one owner per major context domain (operations, quality, finance)
• Review high-impact entries monthly
• Remove duplicates and outdated definitions quickly

Consistency matters more than volume.

Common Mistakes to Avoid

• Adding temporary updates that expire quickly
• Mixing policy with opinion in the same entry
• Keeping multiple conflicting definitions for one KPI
• Leaving context unowned after initial setup

Health Check (Monthly)

Run this quick check:

1. Spot-check 5 critical KPI definitions
2. Verify line/shift names match current operations
3. Remove obsolete files or duplicate entries
4. Confirm each section has an active owner

Next Guide

Continue with Mobile and Voice Usage.