AI Championship

Beyond Code Completion: The AI Mindset

Many teams use AI tools merely as prompt-based code completion. My approach focuses on agentic coding and spec-driven development. I help teams move from manual coding to "curating" code generated by AI agents based on precise specifications. This ensures that the AI serves your application architecture and design system, rather than producing generic boilerplate.

AI-enhanced workflows benefit both design and software engineering teams by creating a common language. I demonstrate how to use AI to bridge these disciplines, allowing designers to produce code-ready specs and developers to implement them with high fidelity. A prime example is my popular public workshop, Cursor for Design Systems, where I train professionals to use spec-driven development to unify their design and engineering processes.

My career has been defined by pioneering standardized approaches to software development. I was an early evangelist for Design Systems, helping to popularize them from a niche idea to a global industry standard. I bring that same foresight to AI-native development. I believe agentic coding is the next major shift, and I am here to guide your organization through this transformation just as I did with Design Systems—pragmatically, effectively, and with a focus on long-term value.

The Transformation: From Traditional to AI-Native Workflows

The journey to AI-native development isn't just about adopting new tools, it's about fundamentally restructuring how teams approach the entire product development lifecycle. Let me show you the three stages of this evolution:

1. Traditional Workflow: Before AI

The conventional approach relies heavily on manual processes across all phases: from discovery research to final code release. While structured, it's time-intensive and prone to handoff friction between design and development teams.

2. Unstructured AI Adoption: The Pitfall

Many teams jump into AI tools without changing their underlying processes. This leads to fragmented workflows, inconsistent outputs, and technical debt. Teams get caught in cycles of re-prompting and manual fixes, often ending up with more work than before.

3. Structured AI-Native Approach: The Solution

The optimal approach integrates AI strategically across all phases while maintaining quality and consistency. AI handles research synthesis, specification generation, and code production, while humans focus on strategic decisions and quality assurance. Notice the "Coffee Time" 😜, it is an opportunity for your team to celebrate success and for your company to win the competition.

What I Offer

• Embedded AI Championship: I work hands-on (100% allocation) as a member of your software development team. I act as a role model, utilizing agentic coding for daily tasks and showing practical "tips and tricks" in real-time.
• Workflow Optimization: I identify opportunities to offload repetitive or complex sub-tasks to AI agents, establishing a baseline for AI-assisted best practices tailored to your tech stack (AWS, React, Python, etc.).
• Bridging Design & Development: Leveraging my background in design systems, I implement workflows where Figma designs and requirements are systematically translated into code using AI, reducing handoff friction and ensuring fidelity.
• Mentorship & Culture Shift: I mentor existing team members, helping them transition from traditional coding methodologies to AI-native workflows with patience and empathy.

Why It Works

I combine the hands-on technical mastery of an AI-native developer with the strategic mindset of an engineering leader. I understand the challenges of adoption in both legacy and cloud-native environments. My goal is to "level up" your existing team, leaving them with the skills and processes to continue innovating long after our engagement.

Get Started

Ready to transform your team's velocity and quality with AI? Let's discuss how an AI Champion engagement can fit your organization's needs.

Or book a call session directly via Calendly.