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:

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 CODER FRAMEWORK
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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

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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

1. 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%)

2. 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)

3. 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

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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)