5 Design Principles Every Engineer Should Master (With Interview Cheat Codes)
Master five core design principles to write cleaner code and ace coding & system design interviews with confidence.
In daily coding and high-pressure interviews alike, having solid design instincts sets you apart. Instead of just churning out code, the best engineers lean on time-tested principles to guide decisions. This newsletter spotlights five such design principles that sharpen your engineering judgment and give you cheat codes for interviews. Mastering these will not only make your code cleaner but also help you articulate trade-offs and impress interviewers when it counts.
Single Responsibility Principle (SRP)
One job per component—if it does two, it’s doing too much. SRP says a module or function should have only one reason to change. If you mix salary calculation with email notification, you’ll break both when either requirement shifts. By splitting into focused units, changes stay isolated and tests stay simple.
Why It Matters: Changes to one feature shouldn’t break unrelated ones.
# ❌ Violates SRP: mixes user role update and email logic
def make_user_admin(user):
user.role = 'admin'
send_email(user.email, "You’re now an admin")
# ✅ SRP-compliant: split responsibilities
def set_admin(user):
user.role = 'admin'
def notify_admin(email):
send_email(email, "You’re now an admin") Interview Script:
“Let’s split this into two modules—updating roles and sending emails. That way, changing the email service won’t break user management.”
Don't Repeat Yourself (DRY)
Stop the copy-paste—one place for each logic. DRY means each piece of knowledge lives in just one spot. If you find the same formula in five functions, one tweak becomes five potential bugs. Extract a helper, update once, ship safely.
Why It Matters: Duplicate code = duplicate bugs.
# ❌ Repeats area calculation
print(f"Area: {width * height}")
volume = (width * height) * depth
# ✅ DRY: centralize logic
def calculate_area(w, h):
return w * h
print(f"Area: {calculate_area(width, height)}") Interview Script:
“I notice some repeated logic here – I'll refactor into a helper function to keep things DRY and maintainable.”
YAGNI (You Aren’t Gonna Need It)
No crystal ball—implement features only when needed. YAGNI warns against building for hypothetical futures. Over-engineering bloats code and slows you down. Solve today’s problem simply; you can evolve the design when new requirements arrive.
Why It Matters: Over-engineering kills agility.
# ❌ Premature discount feature (unused)
def total(price, qty, discount=0):
return price * qty * (1 - discount)
# ✅ YAGNI: keep it simple
def total(price, qty):
return price * qty Interview Script:
“Let’s skip the discount logic for now—we can add it later if needed. YAGNI keeps our MVP lean.”
CAP Theorem Tradeoffs
Consistency or availability—in a partition, pick one. In distributed systems, you can only have two of Consistency, Availability, and Partition Tolerance. Partitions happen, so choose between consistency (fresh data) or availability (always up). A social feed tolerates slight staleness (AP); a payment system probably errs out until data syncs (CP).
Why It Matters: Distributed systems require brutal prioritization.
“Given this is a payment system, I’d prioritize Consistency. During a partition, we’ll error out instead of risking bad data.”
Design for Failure
Everything fails eventually—design like you know it. Murphy’s Law rules: servers crash, networks go down, disks corrupt. Build resilience with retries, fallbacks, and redundancy. If one zone goes dark, others pick up the slack; if a config file is missing, fall back to safe defaults.
Why It Matters: Resilient systems survive chaos.
# Handle missing configs gracefully
try:
config = json.load(open('config.json'))
except FileNotFoundError:
config = {"mode": "default"} # Fail-safe default “If the database goes down, we’ll serve cached data and log the outage. No single point of failure.”
Final Thought
At the end of the day, these principles are guides, not hard laws. Great engineers (and interviewees) use judgment to decide when to apply each principle and when to bend it. It’s better to understand the trade-offs than to blindly chant “SOLID” or “DRY” at every turn. So remember: knowing the name is good, but knowing when and why to use it is the real cheat code.