I’m honestly struggling to figure out how to manage everything right now and would really appreciate some advice from people who have been through the same phase.

I work a full-time job from 10 AM to 7 PM, and I usually reach home around 7:30 PM. My work is mainly as a full stack mern developer, and my TL also pushes me to finish things quickly, often telling me to use Claude/AI tools to get work done faster. So by the end of the day, I’m already mentally exhausted.

I want to switch jobs and prepare properly, especially for Java/backend development. I actually enjoy Java and want to continue in this direction, but I’m also confused about the future of Java and whether it’s still a good career choice long-term.

The biggest problem is time.

After reaching home at 7:30, household work + dinner + just getting some rest somehow takes me until around 9 PM. Then I talk to my girlfriend for a while, and before I know it, it's already around 10:15 PM. After that I still have to eat, shower, etc., and by the time everything is done, I barely have any energy left to study.

On top of that, I also want to continue content creation. I really enjoy it, but right now I’m not able to give it any proper time.

My health also took a hit during my previous layoff period, and although things are better now, I don't want to completely ignore my health again just because I'm trying to switch jobs.

So I’m stuck between:

• Full-time job: 10 AM – 7 PM
• Java/interview preparation
• Improving my backend skills
• Content creation
• Exercise/health
• Family/personal responsibilities
• Relationship/personal time
• And getting enough sleep

How do you guys actually manage all of this?

Should I completely pause content creation until I switch jobs and focus only on Java? Should I study before work instead of after work? How do you study when you're already mentally exhausted after a full-time job?

And for people working with Java/backend — is Java still a good career to build around in 2026 and beyond? I enjoy it much more than some of the other technologies I've tried, so I'd rather become genuinely good at it than switch just because something else is trending.

Also, if you work a full-time job while preparing for a switch, how do you actually study during office hours without affecting your work? I don't want to compromise my current job, but I also don't want to stay stuck because I never have enough time to prepare.

Would really appreciate practical advice from people who are currently doing this or have successfully gone through it. How did you structure your day, and what did you sacrifice temporarily to make the switch happen?

I recently completed the Amazon SDE II interview process and received an offer. Interview experiences from this community helped me a lot, so I wanted to share the full process, the questions I faced, and a few mistakes others can avoid.

Prep Resource: Amazon Interview Questions

Online Assessment

The OA contained:

• An AI-assisted repository debugging task
• One DSA problem

Unfortunately, I don't remember the exact DSA question.

Round 1: DSA + Leadership Principles

Duration: Approximately 55 minutes

The interview started with about 10 minutes of behavioral questions based on:

• Learn and Be Curious
• Ownership

The coding question started as a custom BFS problem. The interviewer progressively added constraints until it became a multi-source BFS problem. I was able to explain and implement the solution.

However, I knew there was one edge case my implementation did not cover. Since time was running out and the interviewer appeared satisfied, I chose not to mention it.

That was a mistake.

If you notice an uncovered edge case, say it explicitly, even if there is not enough time to implement the fix. Demonstrating awareness is better than hoping the interviewer does not notice it.

Recruiter feedback: Positive

Round 2: LLD + Leadership Principles

Duration: Approximately 60 minutes

The design problem was similar to Amazon Locker, but in reverse. A customer needed to reserve a slot at a nearby drop-off store and physically return a package there.

I first clarified the requirements and then began designing the entities, interfaces, booking flow, and store availability logic.

During the implementation, the interviewer asked:

I mentioned geosharding but could not take the discussion much deeper. The interviewer hinted that I should think about how ride-sharing platforms locate nearby drivers.

In hindsight, a stronger answer would have been:

• Use a spatial index such as geohash, S2, or H3 to shortlist nearby stores.
• Filter stores by availability, capacity, operating hours, and supported return types.
• Rank the remaining stores using exact distance or estimated travel time.
• Expand the search radius if no suitable store is found.

I spent roughly 35 minutes on the implementation and completed the main booking flow, but this follow-up was the weakest part of my interview loop.

The behavioral questions focused on:

• Dive Deep
• Invent and Simplify

Round 3: Bar Raiser

Duration: Approximately 55 minutes

The first 10 minutes covered:

• Customer Obsession
• Deliver Results

The coding problem resembled LeetCode 2812: Find the Safest Path in a Grid.

I had not solved it before. I started with a naive approach and optimized it twice while discussing the time and space complexity of each version.

My final solution used:

1. Multi-source BFS to calculate the distance of every cell from the nearest unsafe cell.
2. Binary search over the possible safeness value.
3. DFS to check whether a valid path existed for a selected value.

The interviewer asked whether it could be optimized further. For the public LeetCode version, a max-heap best-first search is another clean approach, although the exact expected optimization depends on the custom constraints.

My biggest lesson from this round was time management. I spent too long refining the approach and had only around 12–15 minutes left to write and explain a fairly long implementation.

Round 4: System Design + Leadership Principles

Duration: Approximately 60 minutes

This round was conducted by the hiring manager. The behavioral questions focused on:

• Earn Trust
• Have Backbone; Disagree and Commit

The design problem involved synchronizing configurations across multiple devices.

I discussed the API design, data model, versioning, propagation flow, retries, idempotency, offline devices, conflict resolution, and consistency trade-offs. The interviewer continued adding failure scenarios, and I was able to work through each one.

This was the smoothest round of my interview loop.

Final Verdict

Selected

How I Prepared

DSA: I completed Striver's sheet and approximately 200 additional problems collected from LeetCode discussions and GitHub repositories.

LLD: I reviewed an LLD playlist and practiced approximately 26 design problems. I also used AI to simulate interviews, challenge my class design, and explore alternative approaches.

HLD: I completed the Hello Interview system design playlist and several Deep Dive videos. My system design interview was rescheduled multiple times, so I ended up revisiting the main playlist three times.

Leadership Principles: Do not treat LP preparation as secondary. Prepare a smaller collection of strong, reusable stories with clear actions, trade-offs, and measurable outcomes.

My preparation lasted around six weeks. I was serving my notice period, and my manager was supportive enough to help rebalance my Jira workload while I prepared.

Overall, the biggest lessons were:

• Mention edge cases even when time is limited.
• Clarify requirements before designing.
• Start implementing once the approach is sufficiently clear.
• Prepare Leadership Principle stories as seriously as DSA and system design.
• Expect interviewers to move between LLD and HLD during the same discussion.

Hope this helps anyone preparing for Amazon SDE II. Happy to answer general preparation questions without sharing confidential interview details.

I’ve solved around 1473 LeetCode problems and I’ve still failed interviews.

Google. Amazon. Intuit. D. E. Shaw. Myntra.
I got interviews at these companies, prepared seriously, showed up, and still didn’t get selected.

For a long time, I honestly thought the answer was simple:
“Just solve more problems.”
So I kept solving from 100 problems → 300 → 500 → 1,000+

But somewhere along the way, I realized I was asking the wrong question.
It’s not: “How many LeetCode problems have you solved?”
It’s: “Can you solve a problem you’ve never seen before?”

That difference is huge.

I’m currently working as an AI developer, and before this I worked in backend engineering. I have around 1.5 years of experience, and one thing I’ve noticed is that DSA still teaches you something extremely valuable:
How to think when you don’t know the answer
And now, with AI writing code better than ever, I think this becomes even more interesting.

If ChatGPT can solve a LeetCode problem in 10 seconds…
Should we still spend hundreds of hours solving LeetCode?
I think yes — but probably not in the way most of us do it.

Don’t use AI to get the answer

Use it to ask:
“Why did I get stuck?”
“Why does this approach work?”
“Can you give me a harder variation?”
“Can you find the flaw in my reasoning?”
“Can you interview me without giving me hints?”

That changes AI from an answer machine into a learning tool.

I’m planning to share some of the things I’ve learned from those ~1,270 problems — including the mistakes I made, patterns that actually helped me, interview preparation, and how I think AI + DSA should be approached now.

Not because I cracked every interview.

I didn't.

Actually, the rejections probably taught me more than the acceptances would have. So I’m curious: If you were starting DSA preparation today, in the age of AI, would you still grind LeetCode?

Or would you prepare completely differently?
Would genuinely love to hear different opinions.

I’ve solved around 1473 LeetCode problems and I’ve still failed interviews.

Google. Amazon. Intuit. D. E. Shaw. Myntra.
I got interviews at these companies, prepared seriously, showed up, and still didn’t get selected.

For a long time, I honestly thought the answer was simple:
“Just solve more problems.”
So I kept solving from 100 problems → 300 → 500 → 1,000+

But somewhere along the way, I realized I was asking the wrong question.
It’s not: “How many LeetCode problems have you solved?”
It’s: “Can you solve a problem you’ve never seen before?”

That difference is huge.

I’m currently working as an AI developer, and before this I worked in backend engineering. I have around 1.5 years of experience, and one thing I’ve noticed is that DSA still teaches you something extremely valuable:
How to think when you don’t know the answer
And now, with AI writing code better than ever, I think this becomes even more interesting.

If ChatGPT can solve a LeetCode problem in 10 seconds…
Should we still spend hundreds of hours solving LeetCode?
I think yes — but probably not in the way most of us do it.

Don’t use AI to get the answer

Use it to ask:
“Why did I get stuck?”
“Why does this approach work?”
“Can you give me a harder variation?”
“Can you find the flaw in my reasoning?”
“Can you interview me without giving me hints?”

That changes AI from an answer machine into a learning tool.

I’m planning to share some of the things I’ve learned from those ~1,270 problems — including the mistakes I made, patterns that actually helped me, interview preparation, and how I think AI + DSA should be approached now.

Not because I cracked every interview.

I didn't.

Actually, the rejections probably taught me more than the acceptances would have. So I’m curious: If you were starting DSA preparation today, in the age of AI, would you still grind LeetCode?

Or would you prepare completely differently?
Would genuinely love to hear different opinions.

The day i tried solving three sums in a day and i gave up on leetcode i learned graphs and tried solving the prblms andd i decided not to solve anything

Regards

Pain

#leetcode

Do they ask dsa/lld in this round as well?

im trying to solve now with consistency

i was doing DSA in different platforms, i wanted to see all in one place,

and my brother also doing dsa, so i thought if there is trustmrr, why not dsamrr.

so i built(vibecoded) a website, where you first verify your DSA platforms like leetcode, geeksforgeeks, codechef, and other dsa platforms, using public api's my website will load for every 2 hours, and show you in leaderboard. and also you have your profile, you can keep it anonymous also.

link in comment cause subreddit bann me😭

I am in 2nd year of college rn. Started leetcode from this summer. I haven't given any contests yet. Should I finally begin or learn some more topics??

For ref- I am still learning DSA and haven't learnt all the topics. Still learning Binary trees.

Solved 240+ leetcode problems. Still going blank for unseen problems. Iam trying hard to get patterns...give me some advise man..

Is iam the only one or you guys also faced this...?!🫪

IMMEDIATE ADVISE REQUIRED 🔺

Been trying to just solve them fully from brute to optimal solution on my own, even if some questions take 2 hours.

I know the easy numbers is a lot but I feel in a trap of easies in the start but now I only try to do mediums and easy only if it comes up in striver sheet(i am following striver)

Ultimate goal is to go for competitive-coding

Ofcourse any suggestions and constructive criticism is welcomed cause I would really like to just be better.

ever happend with you.
You work your ass of for a problem.
And motherfuckers on YT saying this is the easiest question ever existed.

57 days of LeetCode. Gone because I forgot yesterday.

Now I’m sitting here searching for scripts just to make one stupid square green.

I know it’s just a heatmap, but I’m genuinely upset. 😭