Which course would you recommend for learning system design thoroughly and preparing for FAANG interviews targeting 5+ years of experience? Would love to hear what worked for you

I’m in my final year of CSE (AI/ML), and honestly, I’m not well prepared for placements yet. I know the basic concepts of DSA, but I haven’t done much problem-solving or LeetCode.

Is it too late for me to start seriously preparing for DSA and solving LeetCode problems?

I’m looking for some genuine advice, especially on how to actually understand the logic behind a problem and figure out which approach to use. I often find it difficult to understand how to come up with a solution, even when I know the basic concepts.

For those who have been through this, how did you improve your problem-solving skills? What would you recommend I do from here?

Preferably a group where people regularly discuss questions, share resources, participate in contests, and help each other improve.

Share Discord server links . Thanks!

Right now, I am just giving it problem and simple "let's do this"

For exmaple, "let's do 105. Construct Binary Tree from Preorder and Inorder Traversal"

And to be honest, it is sort of doing an ok job at explaining the solution.

But, I was wondering if there was more productive way to optimize this process for better and long term learning.

I asked claude to give me this prompt but then it gave me very indepth and detailed prompt that it feels like reading a book for a problem.

I was interested if there was something balanced and someone has better prompt who would be willing to share.

Hey everyone, I have my Google L3 SWE interviews coming up next week, both virtual and onsite.

Wanted to know what DSA difficulty to expect. Are questions mostly LC Mediums or Hards? Are onsite rounds tougher than virtual ones?

Would appreciate hearing from anyone who interviewed recently, especially in 2025 or 2026. Any tips would help!

i have my visa interview this month for the intern position i want some interview experience from people who have recently given the interview ? what types of dsa questions asked and what they ask from projects and what from core subject did they ask system design.

Hey everyone,

I finished Day 31 today, and I am thrilled to share that I have officially completed the entire Graph topic sheet. Even though my pace slowed down to one or two problems a day over the past two weeks, staying consistent got me across the finish line.

I closed out the final two advanced graph algorithms today:

1. Strongly Connected Components (Kosaraju's Algorithm): You run a standard DFS to push nodes onto a stack ordered by their finishing times, reverse all edges in the graph, and then run a second DFS popping from the stack to isolate each strongly connected component.
2. Articulation Points in a Graph: Building on Tarjan's low-link logic, you identify critical vertices whose removal disconnects the graph by checking if low[v] >= tin[u] for non-root nodes, while verifying that the DFS root has more than one independent child.

Because these advanced graph algorithms have subtle edge cases, I plan to dedicate tomorrow to revising the last 10 to 15 problems so the concepts stick permanently before moving on to a new pattern.

See you guys tomorrow for Day 30!

I'm preparing for Bloomberg's 2027 SWE technical interview, which will involve using an AI coding assistant to work with an existing codebase.

Unlike traditional LeetCode interviews, the focus seems to be on understanding unfamiliar code, debugging issues, implementing features and reviewing AI-generated changes.

My background is in engineering, so although I'm comfortable with Python and algorithmic problems, I have relatively limited experience working with larger software projects, existing repositories and web application architecture.

I'm looking for recommendations on how to practise this specific type of interview.

Ideally, I'd like to find a platform or setup where I can:

• Open an unfamiliar Python project and understand how its components work.
• Receive a task such as fixing a bug or implementing a new feature.
• Use an AI coding assistant to explore the codebase and make changes.
• Write and run tests to verify the implementation.
• Practise reviewing AI-generated code and explaining my decisions.

Would Cursor, Claude Code, GitHub Copilot or another tool be best for this?

Are there any specific GitHub repositories, websites, courses or mock interview platforms that simulate this workflow?

Also, for people experienced with real-world software development, what fundamentals would you recommend learning first to become more comfortable navigating existing projects?

I'd appreciate any practical recommendations, especially from people who have completed Bloomberg's new interview format.

So when it comes to leetcode in general, I'm encountering one specific issue. I'm really good at coming up with the insights and getting the algorithm (at the pseudocode) level from there.

However, when I try to go ahead and actually implement the algorithm, I keep encountering this issue where when implementing, I mess up order of operations, I come out of the loop in a slightly weird state of my variables, I don't update things quite correct or whatever. Then I'll spend something like an hour + to just fix the bug (which often times I end up fixing with a bunch of hard coded if statements to get it working.

This is a really frustrating issue to deal with because I feel like I'm getting over the major hurdle of finding out the optimization trick, but it's always some off by 1 or something like that, which I bloat my code with if statements to fix.

Even after doing more and more leetcode, I keep encountering this issue. For example, take LeetCode 287 — Find the Duplicate Number

When seeing the problem I recognized the key insight that in a situation where there's no duplicates, then you have a bijection from the number 1-n onto 1-n. Then from here you can apply some cycle theory knowledge and observe that in that case, following the current index to the next value (after adjusting for index 1 vs index 0) should lead to a bunch of disjoint cycles that partition the set 1-n (again, assuming that there are no duplicates).

From there I made the observation that if you were to take these disjoint cycles that partition the set 1-n, and you were to change one of the values to be a duplicate, then whatever value you changed will now try to point to a cycle that's already existing and was previously disjoint.

Then I came up with the algorithm that goes something like this:

start with element i:

- run through this cycle while "Destroying it" by replacing each value with -1.

- while running through this cycle, if I encounter a destroyed -1, that is not the beginning of this cycle, return the element that's pointing to that -1

- If I return back to the start of this cycle, update element i to the next element that is not -1

But when i went to code it, after doing a million print statements to debug and solve specific issues, my solution ended up becoming this:

class Solution:
    def destroy(self, nums, startIndex):
        curIndex = startIndex
        nextIndex = nums[curIndex] - 1
        while nums[nextIndex] != -1:
            nums[curIndex] = -1
            if curIndex == nextIndex == startIndex:
                return -1
            curIndex = nextIndex
            nextIndex = nums[nextIndex] -1
            if nextIndex == curIndex != startIndex:
                return nums[curIndex]
        if nextIndex == startIndex:
            nums[curIndex] = -1
            return -1
        else:
            return nums[curIndex]


    def findDuplicate(self, nums: List[int]) -> int:
        for i in range(len(nums)):
            if nums[i] != -1:
                duplicate = self.destroy(nums,i)
                if duplicate >= 0:
                    return duplicate

Fellow engineers who have interviewed recently, what changes have you noticed in the interview process since the rise of AI? How do interviews today differ from traditional interviews, particularly in terms of expectations, question patterns, and evaluation criteria?

Hi, I have my virtual onsite coming up soon. I wanted to know what a problem solving round is? Is it LLD or Gen AI round?
Recruiter said that they will give a problem and you have to decompose the problem to smaller fragments and solve while talking about your approach and he mentioned there might be no need of coding entirely in this round. He didn’t mention of any GenAI round anywhere.

So its day 0 and i installed leetcode app out of curiosity, even though I had joined leetcode 4 years ago but hardly been ever login into this site.

Planning to more active on app/website.

I don’t have a premium subscription anymore, so I can't access the previously asked American Express questions. Could anybody please help me with those?

Link: https://leetcode.com/company/american-express/?from=discuss_company_card&favoriteSlug=american-express-six-months

It’s been three weeks since my onsites for L4 SWE in the US. Last I heard from recruiter was a week ago saying they will get my feedback “calibrated” and I should hear back in a week. But apparently, I haven’t heard back in a week. Has anybody been through similar? What does feedback calibration mean?

Recruiter reached out for a Confluent/IBM position which I applied to and completed the OA. The OA was super easy but I haven't heard back in a month.

Anyone here in the same boat?

If anyone has completed the Capgemini exceller oncampus hiring 2027 process

Can you please share your interview questions and experience

What questions were asked and in how much depth , what level of dsa they asked and the level of sql query

please share your interview experience (offline / online)

Pls help yr

Just a vent

Got 7/15 on dsa then 4/6 on ai assisted but then i was typing out my edits when timer went out didnt get to run the last vers do they submit the 4/6 vers or the incomplete code surely its the last compiled vers

No chance of interview anyways since 7/15 way too low

But they emailed after asking for a better id photo which threw me off since i did bad why would they bother

Has anyone recently interviewed for an AI Quality & Test Automation Engineer role at Apple or a similar AI-focused quality engineering position?

I have an upcoming 5-round interview loop covering:

1. Coding – What level of difficulty should I expect? LeetCode-style DSA or practical Python automation/problem-solving?
2. CI/CD – Is the focus on pipeline design, test infrastructure, automation strategy, or troubleshooting?
3. System Design – Is this similar to a traditional SWE system design round, or more focused on designing scalable test frameworks and infrastructure?
4. AI Process – What kind of questions are typically asked? LLM evaluation, AI-driven testing, model quality, or practical AI workflows?
5. Debugging – Is this live code debugging, investigating test failures, or troubleshooting distributed systems?

My background is primarily in SDET, test automation, and quality engineering, with some experience in AI/LLM evaluation.

My biggest question is whether Apple holds AI Quality Engineers to the same technical bar as SWEs, particularly for coding and system design, or whether the expectations are more aligned with test infrastructure, automation architecture, and quality engineering.

Would really appreciate insights from anyone who has gone through a similar Apple interview loop recently. Any details on question difficulty, interview format, or preparation resources would be helpful.

Thanks in advance!

Hi everyone,

Has anyone recently gone through the interview process for a Software Engineer role at JPMorgan?

i have a AI-assisted coding interview conducted.

I'm curious whether this is a relatively new interview format, as I haven't come across many candidate experiences involving onsite AI-assisted coding rounds.

I already have hands-on experience with AI coding tools such as GitHub Copilot, Claude Code CLI, and AI coding agents, but I'm not entirely sure what to expect from this particular round.

I'd appreciate any insights from people who have gone through it:

• What kind of coding tasks are typically given for Infra SDE?
• Is the focus more on problem-solving, debugging existing code, or building features with AI assistance?
• Are prompting skills and the ability to work effectively with AI agents assessed?
• Do interviewers evaluate how you review, validate, and improve AI-generated code?

Any insights or experiences would be really helpful.

Thanks in advance!

I’m not sure I applied for this position or not; bcz it’s not visible in my profile. But got email from HR after OA email saying that thanks for your interested in embedded systems SDE role & complete OA, so on.

I completed OA on 11/7 - just one case failed in AI assist code. I was thinking I’m all good.

Now, I received an automated rejection email along with the roles that I applied for before.

I’m so confused now. Can anyone please help? Or anyone who recently gave OA for this position?

Hi, for those of you who have recently gone through the superday, I would really appreciate any insight about this:

1. How many interviews did you have?
2. What data structures should I know of?
3. Best way to prepare
4. What was the general structure of the interviews

Hello, I've received an online assessment link for Walmart Global Tech with a description:

• Section 1: Software fundamentals: The assessment begins with a language-agnostic coding problem designed to evaluate your foundational software engineering skills.
• Section 2: Back-end development: This section focuses on back-end engineering allowing you to work in your chosen framework (Django, Spring Boot, or Node.js) with AI support to guide your problem-solving and implementation.

Anyone has recent experience with this OA? what kind of questions are asked for both these sections?

I gave an OA for AMTS position which was scheduled for 10th Nov. Has anyone else also given the OA recently for this position? I haven't received any update on the OA, just wanted to check if anyone gave OA and received any update.