Introduction
Balancing customization in H2O Wave with maintaining a streamlined codebase is a critical challenge for H2O.ai. This trade-off involves meeting diverse client needs while ensuring efficient development and maintenance. I'll analyze this situation, propose a strategic approach, and recommend a path forward.
I'll start by asking clarifying questions, then identify the trade-off type, understand the product, analyze potential impacts, design an experiment, and provide a data-driven recommendation.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Helps prioritize customization efforts against overall business impact Expected answer: 60% from custom, 40% from standard Impact on approach: Higher custom revenue would justify more resources for flexible architecture
Why it matters: Identifies which user needs to prioritize in our solution Expected answer: Enterprise clients request the most customizations, followed by mid-market Impact on approach: Would focus on modular architecture that caters to enterprise needs first
Why it matters: Determines the extent of architectural changes needed Expected answer: Custom code often requires core modifications Impact on approach: Would suggest a more modular, plugin-based architecture
Why it matters: Helps assess feasibility of different approaches Expected answer: 70% core, 30% customization Impact on approach: Might need to reallocate resources or hire for customization expertise
Why it matters: Influences the pace and scope of potential changes Expected answer: Aiming for next major release in 6 months Impact on approach: Would prioritize quick wins and phase longer-term architectural changes
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