Operational & Team Effectiveness Examples

Strong learning cultures rely not only on great training, but on the systems, processes, and structures that support people in their day-to-day work. This pillar focuses on the behind-the-scenes enablement that helps teams operate with clarity, consistency, and confidence, whether through streamlined workflows, improved documentation, scalable onboarding systems, or clear performance pathways.

 

The projects in this section highlight how operational design and enablement tools can remove friction, strengthen collaboration, and empower teams to do their best work. Here, learning becomes more than a moment. It becomes an ecosystem that supports performance long after the training is over.

 

Note: For much of my previous work, original documents are not available due to NDA, copyright, or having been replaced by more current versions. I have included what I can for context, including external media that relates to each project if available.

Everbright: AI Usage and Policy Sessions

The logo for the company Everbright - a White E on a pink background

As AI adoption accelerated across industries, our company needed a structured way to understand how internal teams were using AI and use those insights to define responsible, ethical, and practical guidelines.

 

I designed and facilitated a multi-part session experience that helped individual contributors reflect on their current AI workflows, surface the tools and practices already in use, and articulate their hopes, concerns, and needs. These IC sessions were paired with manager-focused synthesis sessions to begin shaping an internal AI policy, mission/values statement, and a future-facing AI playbook.

 

The result was a shared understanding of how our team uses AI today, what guardrails and values matter most, and what commitments employees want leadership to make as we move toward formalizing an AI ethos.

Media

Everbright AI Session - Facilitator Guide (PDF)
Download File
An image of a sheet of paper with the text Project Summary

• Multi-part session series designed to assess current AI usage and align staff around ethical, intentional practices

 

• Included IC learning + discovery sessions and manager synthesis sessions

 

• Outputs informed a draft AI policy, values statement, and ethical guidelines

 

• Designed as a repeatable framework for internal and client-facing conversations about responsible AI usage

Icon of a person with the text My Role

Learning Designer / Facilitator

 

• Designed the full workshop experience, including slide decks, facilitator scripts, and breakout activities

 

• Created Figma boards and collaborative documents for real-time data collection and synthesis

 

• Facilitated the inaugural IC session and gathered participant insights, patterns, and themes

 

• Built a structured method for capturing AI tools, use cases, best practices, and concerns from staff

 

• Developed manager-facing synthesis sessions to translate findings into draft policy elements

 

• Led the initial drafting of an internal AI values statement and preliminary playbook structure

 

• Balanced instructional content with discovery-oriented questions to surface honest, nuanced input

Challenges & Complexities

A Rapidly Evolving AI Landscape

 

  • Constant tool and capability changes made it difficult to establish a reliable “source of truth”
  • Needed materials that could age gracefully, emphasizing principles over specific tools
  • Required ongoing updates as practices and technologies shifted

Mixed Levels of AI Experience

 

  • Participants ranged from daily power users to those just beginning to experiment
  • Sessions needed to balance learning, discussion, and discovery without overwhelming anyone
  • Required scaffolding to ensure equitable participation and psychological safety

Emotional & Ethical Nuance

 

  • Discussions touched on artistic integrity, environmental impacts, job security, data risks, and personal identity
  • Some staff were hesitant to disclose how much they rely on AI
  • Needed to create a safe, non-judgmental environment to encourage transparency and honesty

Outcomes

  • Rich, organization-wide insight into current AI tools, use cases, and workflows
  • Surface-level and deep concerns documented to inform future policy decisions
  • Early alignment on AI values, including ethics, transparency, and intentional use
  • A consolidated list of employee needs and requests for leadership commitments
  • Initial draft of an AI mission/values statement created collaboratively
  • Clear structure for an evolving AI Playbook, including tools, best practices, guidelines, and open questions
  • A repeatable session model that can be used internally and delivered to clients as a service offering