Amazon's 2026 spring / summer SDE Intern OA holds its standard shape: Debugging (7 snippets) + 2 coding problems + Work Style Survey (200 questions). This article distills 1point3acres 2026 feedback into the three tracks, including Sum of Skills, Robot Coordination, and how to answer the Work Style Survey for LP alignment, with an OA assist playbook.
Amazon Intern OA Snapshot (2026)
| Dimension | Detail |
|---|---|
| Platform | HackerRank (Amazon-branded) |
| Duration | ~100 minutes (70 technical + 30 survey) |
| Quantity | 7 debug + 2 coding + 200 Work Style |
| Focus | LC Medium + debug speed + LP alignment |
| Pass rate | ~35% per 1point3acres |
| Cooldown | 6 months |
Track 1: Debugging (7 snippets)
Surface
- 7 buggy snippets (Python / Java / C++), 1–2 bugs each
- 20 minutes total → < 3 minutes per snippet
- Test-driven: every case must pass
Real Question: Buggy Fenwick Tree
# Buggy version
class Fenwick:
def __init__(self, n):
self.tree = [0] * n # should be n + 1
def update(self, i, delta):
while i < len(self.tree):
self.tree[i] += delta
i += i & (-i) # correct
def query(self, i):
s = 0
while i > 0:
s += self.tree[i]
i -= i & (-i)
return s
Tips
- Don't read top-down: diff expected vs actual output to localize
- Common bugs: off-by-one, index OOB, loop boundary, variable mix-up
- Skip after 3 minutes
Track 2: 2 Coding Problems
Real Question 1: Sum of Skills (team pairing)
"Given n employee skills skills[i], split into n/2 pairs minimizing the variance of pair-sums."
def min_variance_pairs(skills):
skills = sorted(skills)
n = len(skills)
pairs = [(skills[i] + skills[n - 1 - i]) for i in range(n // 2)]
mean = sum(pairs) / len(pairs)
return sum((p - mean) ** 2 for p in pairs)
Trap: must sort first; O(n²) brute force TLEs.
Real Question 2: Robot Coordination
"n warehouse robots at positions pos[i]. Move them all to one point with minimum total distance."
def min_total_distance(pos):
pos.sort()
median = pos[len(pos) // 2]
return sum(abs(p - median) for p in pos)
Signal: median property (not mean). Hidden case: even-length pos — lower or upper median is equivalent.
Track 3: Work Style Survey (200 questions)
Surface
- 200 scenario binaries / Likert (1–5)
- 30-minute hard cap
- Consistency check: same theme phrased differently to detect flip-flop
Amazon 16 Leadership Principles
- Customer Obsession
- Ownership
- Invent and Simplify
- Are Right, A Lot
- Learn and Be Curious
- Hire and Develop the Best
- Insist on the Highest Standards
- Think Big
- Bias for Action
- Frugality
- Earn Trust
- Dive Deep
- Have Backbone; Disagree and Commit
- Deliver Results
- Strive to be Earth's Best Employer
- Success and Scale Bring Broad Responsibility
Principles
- No middling: pick 1 or 5; 3 is a weak signal
- LP-aligned: lean toward Ownership / Bias for Action / Customer Obsession
- Consistency: don't "answer like two people" within 30 minutes
High-Frequency Scenarios
| Scenario | Recommended Lean |
|---|---|
| "You disagree with your manager but the project must ship" | Disagree and Commit |
| "A small bug, but the fix delays release by a week" | Highest Standards / fix |
| "Decide with only half the data" | Bias for Action / decide at 80% |
| "Teammate's code style differs from yours" | Earn Trust / don't push back hard |
1point3acres 2026 Frequency
| Problem | Frequency | Difficulty |
|---|---|---|
| Sum of Skills | ★★★★★ | Medium |
| Robot Coordination | ★★★★ | Medium |
| Warehouse Inspection | ★★★★ | Medium |
| Inventory Allocation | ★★★ | Medium |
| String Pattern Grouping | ★★★ | Easy-Medium |
| K-Closest Stations | ★★ | Medium |
OA Assist Playbook
What oavoservice OA assist gives you
- 7-snippet debug simulation: 20-minute timed, line-by-line review of misses
- Coding bank: 5 variants each for Sum of Skills and Robot Coordination
- Work Style Survey LP mapping book: recommended LP-aligned answers for 200 scenarios
- VO transition: same mentor for the 16-LP behavioral onsite
What's hard about Amazon Intern OA
Amazon explicitly scores survey consistency. We've seen perfect-coding candidates get weak-signaled for "too perfect" surveys (all 5s). OA assist members get a survey consistency checklist plus answer-pacing guidance.
Add WeChat Coding0201 for pricing and scope.
FAQ
What languages does Amazon Intern OA accept?
Python / Java / C++. Python is ~55% per community reports.
Do I need 7/7 debug to advance?
No. 5/7 + 2/2 coding + consistent survey advances.
What happens if I answer the survey "wrong"?
There's no wrong, but inconsistency or all-middling reads as a weak signal — and it impacts pass rate more than coding misses.
Cooldown after a fail?
6 months. Cross-role (SDE → AWS) typically uses a separate pool.
Preparing for Amazon Intern / NewGrad OA / VO?
oavoservice tracks Amazon / AWS / Amazon Robotics / Audible SDE / DA / ML Intern + NewGrad surfaces. Mentors come from live Retail / AWS / Robotics teams and provide 7-snippet debug simulation, coding variants, Work Style Survey LP mapping book, and 16-LP behavioral mocks.
👉 Add WeChat: Coding0201 for the Amazon Intern OA 2026 bank + OA assist plan.
Contact
Email: [email protected]
Telegram: @OAVOProxy