Brex·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Brex software engineer interview with a coding problem centered on extending an existing card game system. The problem itself was well-scoped and felt like real product work, which I appreciated, though the discount logic had some edge cases that tripped me up.

Questions Asked (1)

You have a card trading game where each card has a gem cost broken down by color and is itself associated with a color. Players hold a gem inventory and a hand of owned cards. Given two existing functions for checking affordability and executing a purchase, update both to account for a new rule: each card a player already owns reduces the cost of its associated color by 1 (stacking, floored at 0) for all future purchases.

Data ModelingAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

The setup took me a minute to internalize.

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AI HintsAI Generated

Suggested Approach

First, clarify the data model and the exact discount rule, including how owned cards are counted and whether the discount applies per color. Then, design a shared helper function that computes the effective cost for a given card, ensuring both affordability and purchase functions use it to avoid duplication. Finally, discuss trade-offs such as performance and maintainability, and consider edge cases like negative costs.

Pro tip: Emphasize that the discount should be computed dynamically based on the current hand, not cached, to avoid stale data when cards are acquired or removed. Also, mention that flooring at zero prevents negative costs, which could otherwise lead to unintended game mechanics.

1. Clarify requirements and assumptions

Confirm how owned cards are counted (e.g., duplicates count separately) and that the discount applies to all future purchases. Ask if the discount stacks per card and if it applies to each color independently.

2. Design a shared cost calculation function

Create a helper function that takes a card and the player's hand, computes the discount per color based on owned cards, and returns the effective cost. This ensures consistency between affordability and purchase.

3. Update affordability check

Modify the existing affordability function to use the shared cost calculation, comparing the player's gem inventory against the effective cost.

4. Update purchase execution

Modify the purchase function to deduct the effective cost from the player's inventory and add the purchased card to their hand, triggering the discount for future purchases.

5. Discuss trade-offs and edge cases

Address performance (e.g., recomputing discounts on each call vs. caching), maintainability (single source of truth), and edge cases (e.g., discount exceeding cost, multiple colors, empty hand).

Key Points to Mention

Single source of truth: use a shared helper to compute effective cost to avoid inconsistencies.
Dynamic discount calculation: recompute based on current hand to reflect real-time changes.
Floor at zero: ensure effective cost per color is never negative.
Stacking: each owned card of a color reduces that color's cost by 1, including duplicates.
Performance considerations: caching vs. recomputation, and potential optimizations.
Edge cases: empty hand, multiple colors, discount exceeding base cost, and concurrent modifications.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.