I went straight to severity and user impact, which felt right, but I didn't anchor it to anything business-specific until they pushed back.
Start by framing the decision as a trade-off between user impact, business value, and risk, not just a binary choice. Use a structured framework to evaluate both the bug and the feature, considering severity, reach, strategic alignment, and cost of delay. Then explain how you'd communicate the decision and involve stakeholders.
Pro tip: In crypto, bugs can have financial and regulatory consequences, so always assess if the bug poses a security, compliance, or trust risk—if so, it automatically takes priority. Also, consider if the feature can be shipped with a workaround or if the bug can be fixed in a follow-up release.
Determine how many users are affected, whether it causes financial loss, security issues, or regulatory breaches, and if it blocks core functionality. Use a severity matrix (e.g., critical, high, medium, low).
Consider the feature's alignment with company goals, revenue potential, user demand, and competitive pressure. Also assess the cost of delay—what happens if we postpone it?
Estimate the effort required for both, the potential impact on key metrics (e.g., retention, conversion), and the risks of not doing each. Use a simple scoring model or RICE framework.
Can the bug be hotfixed quickly? Can the feature be partially shipped or delayed? Are there workarounds? Explore if both can be addressed with resource reallocation.
Make a recommendation based on data and strategic priorities, and align with engineering, design, and leadership. Document the rationale and revisit if new information emerges.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.