Services

I help organizations move beyond AI experimentation to deliver meaningful business outcomes. My work centers on a disciplined Plan-Do-Check-Act approach to AI-assisted engineering — a framework I've developed, published, and taught to help teams move from pilots to sustainable production practices. Whether you're struggling to scale AI adoption or need guidance developing technical leaders, I bring practical experience from both building software and leading organizations.

AI Adoption Consulting

Most organizations today face a common challenge: AI pilots that fail to deliver meaningful ROI within the agreed timeframe. Teams get stuck between adoption metrics and actual business outcomes, without clear governance approaches that scale.

I work with teams to bridge this gap, helping you move from pilots to production with confidence. My approach focuses on practical implementation patterns, structured governance, and building capabilities that last beyond the engagement.

What I Bring

• PDCA Coaching for Agentic Coding: My published Plan-Do-Check-Act framework structures every AI-assisted development session into four phases: agent-led analysis and planning, test-driven implementation, validation against stated goals, and targeted retrospectives to refine prompts and process. I coach teams to internalize this cycle — turning agentic coding from an unpredictable experiment into a repeatable, quality-controlled practice. This is the discipline that separates teams that accumulate AI code debt from those that build durable systems.
• Practical Governance: Build governance frameworks that scale from individual contributors to entire engineering organizations, balancing innovation with quality and security.
• Real-World Experience: From analyzing the Roslyn Compiler with GPT-4 and Claude to developing AI adoption assessment methodologies, I bring hands-on experience with enterprise AI challenges.
• Focus on Outcomes: Move beyond "AI-assisted commits" toward meaningful business metrics like delivery velocity, quality improvements, and technical debt reduction.

Common Engagement Areas

I typically work with organizations on:

• AI adoption assessment and roadmap development
• Governance framework design and implementation
• Engineering team training and capability building
• Team coaching on the PDCA framework for AI-assisted development
• Pilot program design and scaling strategies
• Tool evaluation and selection guidance
• Integration with existing software development practices

Leadership Coaching

As a CTA certified coach, I mentor technical leaders on practical AI adoption and help teams avoid common implementation pitfalls. My coaching focuses on building sustainable practices that benefit both organizations and the people who build and maintain software over time.

Drawing on experience as COO/CEO of a software services company, I help leaders build transparent, accountable, learning-focused cultures. I believe in responsible development practices—doing what you say and saying what you mean, respecting people, practicing humility, and continuous learning.

Coaching Focus Areas

• Technical Leadership Development: Helping engineers transition into leadership roles while maintaining technical credibility and connection to the work.
• AI Implementation Strategy: Guiding leaders through the challenges of introducing AI capabilities without disrupting team dynamics or quality standards.
• Building Learning Organizations: Creating cultures where experimentation is safe, feedback is valued, and continuous improvement is the norm.
• Agile Leadership: Moving beyond process adoption to understanding the mindset and practices that make agile teams successful.
• Sustainable Pace: Building organizations that deliver value consistently without burning out teams or accumulating crushing technical debt.

Who I Work With

My coaching clients typically include:

• Engineering managers navigating AI adoption with their teams
• Technical leaders struggling to balance innovation with discipline
• Product leaders trying to integrate AI capabilities into their roadmaps
• Executives responsible for organization-wide AI strategies
• Startup founders building their first engineering teams

My Approach

Whether consulting on AI adoption or coaching leaders, I bring a consistent philosophy:

Start with outcomes. Technology choices and processes should serve business goals, not the other way around. I help you clarify what success looks like before diving into implementation.

Build capabilities, not dependencies. The goal of any engagement is to make your team stronger and more self-sufficient, not to create ongoing dependency on external expertise.

Practice what I preach. Every recommendation comes from real-world experience—both successes and instructive failures. I don't offer theoretical frameworks; I share what actually works in production environments.

Respect your context. What works at a startup won't necessarily work at an enterprise. I help you adapt practices to your specific situation, constraints, and culture.