Our mission
Learning drives everything we do. As our labs team, we're the scouts who venture into new tech territories, assess what's worth pursuing, and bring valuable insights back to the team. We're the bridge between emerging technology and practical application.
What we do
Our approach is simple but effective:
- Explore - We stay ahead of tech trends and identify promising new tools, frameworks, and methodologies
- Assess - We evaluate new technologies through hands-on experimentation and real-world testing
- Trial - We build proof-of-concepts and small projects to understand practical implications
- Share - We create content, documentation, and training materials to spread knowledge across the team
This cycle keeps us at the forefront of technology while ensuring our entire organization benefits from our discoveries.
2025 initiatives
Treasury allocation for labs team
We're establishing a dedicated budget for the labs team to invest in:
- New tools and platforms for experimentation
- Courses and certifications for cutting-edge technologies
- Hardware and software needed for testing emerging tech
- Conference attendance and networking opportunities
Experiment-based approach with build-logs
Every experiment we conduct will be documented through build-logs:
- Clear problem statements and hypotheses
- Step-by-step implementation process
- Results and key learnings
- Recommendations for broader adoption
These build-logs become valuable resources for the entire team and contribute to our knowledge base.
AI Apprenticeship batch 2025
We're launching our second AI apprenticeship program to:
- Train team members on AI engineering fundamentals
- Build practical experience with AI tools and frameworks
- Create a pipeline of AI-capable engineers
- Foster innovation through hands-on AI projects
Unlock: AI as copilot for everyone
Our goal is to make AI tools accessible and useful for every role:
- Identify AI tools that enhance productivity for developers, designers, and operations
- Create training materials and best practices guides
- Establish guidelines for AI tool usage and governance
- Measure and track AI adoption across teams
Content production strategy
We create materials in multiple formats to serve different learning styles and use cases:
- Technical deep-dives for engineering teams
- High-level overviews for leadership and decision-makers
- Tutorial content for practical implementation
- Video content for broader audience engagement
- Case studies showing real-world applications
How we measure success
- Tech adoption rate - How quickly new technologies are adopted across teams
- Content engagement - Views, shares, and feedback on our materials
- Knowledge transfer - Team members successfully applying new technologies
- Innovation metrics - New projects and solutions enabled by our research
Working with other chairs
The learning chair collaborates closely with:
- Communication chair - to publish and promote our findings
- Delivery chair - to integrate new technologies into client projects
- Partnership chair - to identify client needs that drive our research priorities
- Engagement chair - to ensure learning opportunities align with career development
Related: 2025 Roadmap
