CODER Framework
Apply Brian Balfour's CODER Framework to systematically drive AI adoption across your organization.
Entry Point
When this skill is invoked, start with:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CODER FRAMEWORK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Drive AI adoption across your organization. - Constraints: Make new behavior easier than old - Ownership: Assign clear responsibility - Directives: Create specific, actionable instructions - Expectations: Set measurable goals - Rewards: Tie to career progression What do you want to do? 1. Diagnose adoption barriers 2. Create full CODER plan 3. Focus on specific team ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
What This Does
Guides you through creating an AI adoption plan using the CODER framework:
- •Constraints - Make new behavior easier than old behavior
- •Ownership - Assign clear responsibility
- •Directives - Create specific, actionable instructions
- •Expectations - Set measurable goals
- •Rewards - Tie to career progression
Usage
/coder
Optional parameters:
- •
/coder --diagnose- Identify your primary adoption barrier - •
/coder --team [team-name]- Create plan for specific team - •
/coder --export- Generate implementation doc
What Happens
- •
Diagnoses your situation:
- •Company size and structure
- •Current AI adoption level
- •Primary barriers (political, retrofitting, procurement, knowledge, permission)
- •Team composition (catalysts 15-20%, converts 60-70%, anchors 15-20%)
- •
Guides through CODER framework:
- •Designs 1-2 constraints for your context
- •Assigns ownership (CEO/functional leaders)
- •Creates 2-3 directives per function
- •Sets specific, universal, measurable expectations
- •Defines how to tie to rewards (performance reviews, leveling)
- •
Generates implementation plan:
- •Immediate actions
- •30/60/90 day milestones
- •Metrics to track
- •Common pitfalls to avoid
The Framework Components
C - Constraints
Make AI behavior easier than old behavior:
- •Time constraints (hackathons, dedicated AI days)
- •Process constraints ("I only review work demonstrating AI augmentation")
- •Tool constraints (Copilot required, AI in workflows)
O - Ownership
Assign clear responsibility:
- •CEO: Overall cultural shift
- •Functional leaders: Team-specific directives
- •Clear escalation paths for blockers
D - Directives
Create specific, actionable instructions (2-3 per team):
- •Product: "All features must include AI prototype before design review"
- •Engineering: "All code reviews must use GitHub Copilot"
- •Design: "Design critiques include AI generation process"
E - Expectations
Set specific, universal, measurable goals:
- •✓ "100% of PMs prototype features with AI" (not "use AI effectively")
- •✓ "90%+ of code commits show Copilot usage"
- •✓ AI fluency levels: Aware→Exploratory→Proficient→Advanced→Expert
R - Rewards
Tie to career progression:
- •Performance review criteria
- •Leveling guide updates
- •Promotion requirements
Common Adoption Barriers
| Barrier | Symptom | Solution Focus |
|---|---|---|
| Political | Leaders disagree on value | Ownership, CEO mandate |
| Retrofitting | "We can't use AI for X" | Directives, examples |
| Procurement | Tool access blocked | Constraints, budgets |
| Knowledge | Don't know how to use tools | Directives, training |
| Permission | Fear of doing wrong | Expectations, psychological safety |
Learn More
See the full CODER framework at:
frameworks/ai-era-practices/organizational-ai-adoption.md
Framework: Brian Balfour (Reforge, 2025) Best for: Driving organizational change, AI adoption, behavioral transformation Key insight: Move from value capture (10-15% efficiency) to value creation (new capabilities)