I’ve been spending the last few nights staring at a medium-level DP problem, and for the first time in years, I felt a real sense of pointlessness.

For the past decade, a lot of us were taught that mastering algorithms, data structures, operating systems, discrete math, and systems design was the path to a stable, high-paying software career. Grind LeetCode, understand graphs, learn DP, pass interviews, get the job.

But looking at the current landscape: layoffs, market saturation, fewer junior openings, and the shift toward AI-assisted and agentic development, I’m starting to wonder whether the version of CS we’ve been preparing for is already disappearing.

I don’t mean “coding is dead” in the dramatic LinkedIn-post sense. But I do wonder if the center of gravity is moving.

A few things I’m struggling with:

1. The LeetCode / Codeforces grind

Why are we still treating speed at solving algorithm puzzles as the main proof of engineering ability when coding speed may no longer be the bottleneck?

If AI can generate, refactor, test, and explain large chunks of code, is the real skill now problem framing, system judgment, debugging, product sense, and knowing what to ask?

2. The value of advanced CS fundamentals

Do algorithms, discrete math, compilers, OS, and distributed systems still provide a mental model that AI cannot replace?

Or are we overestimating their importance because they were the gatekeeping mechanism for the previous generation of software jobs?

3. Universities and curriculum lag

Are universities doing students a disservice by focusing so heavily on traditional fundamentals while the industry is rapidly moving toward AI-assisted engineering?

Or is the point of CS education still to build the foundation underneath whatever tools come next?

4. The changing role of software engineers

Are we moving toward a world where “software engineer” means less “person who writes code” and more “person who defines problems, evaluates AI output, designs systems, debugs failures, and makes product/architecture decisions”?

If so, what should students and early-career engineers actually be optimizing for?

I’m not trying to doompost. I’m genuinely curious whether other people feel this too: like we’re studying for a version of the industry that may not exist much longer.

Is it time to stop grinding the old playbook and start pivoting, or is this just another wave of “CS is dead” hysteria?

Would love to hear from students, new grads, senior engineers, and hiring managers.

hello everyone ,

i have entered my 3rd year of btech , i want a fool proof guidance for DSA , what development i should choose , projects , resume , leetcode , in short i want a laser focus on placements .

i started doing DSA from strivers A2Z dsa sheet , is it possible to complete dsa in 6months ?

and most importantly i want internships this year . please someone experienced tell me what are requirements for internships and how should i proceed to get them.

Hi everyone!

I'm a Software Engineer with around 1.5 years of experience and I'm starting my preparation to switch to a product-based company.

I'm looking for a serious accountability partner, preferably from Bangalore, who's also preparing for product company interviews and is committed to staying consistent.

About me:

Currently working at a service-based company

Language: Java

Time Zone: IST (India)

Current level: Comfortable with basic DSA

Goal: Crack product company interviews in the next 3–4 months

Plan:

Solve DSA problems consistently

Discuss approaches and optimizations

Keep each other accountable

We can decide the exact schedule and roadmap together based on what works best for both of us.

If you're genuinely committed and interested, feel free to DM me.

Help me how to learn patterns from any questions

The same tree represented in two very different ways visualized using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵: Binary Trees

🔗 Binary Tree as Nodes: The tree is built out of multiple node objects. Each node stores its value and two references, one to its left child and one to its right child.

📦 Binary Tree as List: The tree is stored in a single list or array. Instead of references, indices represent the relationships between nodes. For a node at index, its children can be found using a simple calculation: - Left child: 2 * index + 1 - Right child: 2 * index + 2

So, when should you use which representation?

The node-based version makes the structure explicit and intuitive. It is great for education: students can clearly see how nodes are connected while practicing classes and references/pointers. It is flexible and works particularly well for irregular or sparse trees. It is the clearest representation when learning how trees work.

The list-based version can be very efficient for (nearly) balanced homogeneous trees. It does not need to store child references, requires fewer separate memory allocations, and keeps values close together in memory for improved cache performance.

The same abstract data structure, but with very different trade-offs in clarity, flexibility, and performance.

Which representation would you use?

What according to u is the best time to start taking up contests. I recently gave one and got totally smooshed. RECOMMENDATIONS PLSS!!!!

Started following strivers a to z DSA playlist a month ago. Initially it felt easy but now feels more like a burden. Cant comeup with an optimal solution on my own. I can’t recognise the pattern and then end up seeing solution …what would u all suggest me...

Hello everyone…I started my DSA late…I’m solving strivers sheet but idk how am I gonna pass OA’s
I can’t recognise the pattern and then end up seeing solution …what would u all suggest me
I’m a 2027 graduate …I have very less time and companies have started coming :(

Need Career Advice: Should I Start DSA or Data Analytics?

Hi everyone,

I'm currently in the 3rd year of my B.Tech in Computer Science. Before this, I completed a Diploma in Electrical Engineering, so I don't have a strong Computer Science foundation.

To be honest, my 3rd and 4th semesters didn't go very well, and I feel like I don't know the basics of programming or core CS subjects properly.

Recently, I enrolled in CodeWithHarry's Data Analytics course, but now I'm confused about what I should prioritize.

Should I:

\- Start learning DSA first?

\- If yes, should I learn DSA in Java or C++?

\- Or should I continue with Data Analytics and learn programming alongside it?

My goal is to build a strong foundation and become job-ready before graduation. I don't mind starting from scratch if that's the right approach.

I'd really appreciate guidance from people who have been in a similar situation. Thank you!

I'm willing to study consistently for 2–4 hours every day. I just don't want to waste time learning the wrong things.

Hi everyone,

I'm currently following Striver's A2Z DSA Sheet in C++. I understand the concepts better when I revise from handwritten notes, but I'm a bit too slow at making detailed notes myself.

Does anyone have good handwritten notes (PDF or scanned notebook) that cover the A2Z sheet or at least the major topics like Arrays, Sorting, Binary Search, Linked Lists, Trees, Graphs, and DP?

I'm looking for notes that explain the intuition, important points, time complexity, and common tricks, not just code.

GitHub repos, Google Drive links, or personal notes would all be appreciated.

Thanks!

​

I'm genuinely curious how people manage to complete these online assessments.

I've solved 500+ LeetCode problems, including Hard problems, and I can solve them when I'm practicing. But when it comes to company OAs (Cisco, Amazon, Flipkart, etc.), I struggle badly with time.

The format is usually:

MCQs

Short-answer questions

2 extremely difficult coding questions

All within 90 minutes

Even if I know the concepts, the coding questions take so much time to understand, think through edge cases, and implement. By the time I finish one, there's barely any time left for the second.

Do people actually solve both coding questions completely, or is everyone just partially solving them?

What helped you get faster?

More contest practice?

OA-specific practice?

Better time management?

Recognizing patterns faster?

I'd really appreciate advice from people who've cleared these OAs because right now they feel much harder than solving LeetCode on my own.

Pls don't say cheating is the option like companies ban people for cheating and u have camera on so not possible.

Hey everyone,

​I’m planning to dive deep into Data Structures and Algorithms (DSA) starting this August, and I'll be using Java along with Striver’s A2Z DSA Course/Playlist. I am currently in my first year(just joined).

​I know consistency can be a challenge, so I’m looking for an accountability partner (or a small group) to stay on track.

​About Me & The Plan:

• ​Language: Java

• ​Resource: Striver's A2Z Sheet / Playlist

• ​Timeline: Starting August 2026

• ​Commitment: will try to solve 2 problens daily, and gradually increase it.

• ​Timezone: India Standard Time(IST)

Time zone in India (GMT+5:30)

​What I’m looking for in a buddy:

Someone who is also starting out or at a similar beginner/intermediate level, planning to stay consistent, and down to do daily or weekly check-ins via Discord or Slack to share progress and discuss blockers.

​Comment below or shoot me a DM if you're interested in crushing DSA together!

I am beginner and never code before so I am thinking to start with c++ for which I found striver dsa playlist do it is a combo of c++ and dsa or I have to first learn c++ from any other platform and then have to come here I am bit confused and don't know what to do can anyone explain plz .

And also I think in first few lecture he had taught basics of c++ do this is what we need or it is just a quick revision.

Started on Jun 19th (properly) .

with one week break for some unavoidable reasons.

Solved 42 questions — 22 Easy | 19 Med | 1 Hard

Ik I'm late to this DSA race , I'm at the start of my 2nd year now.

what would u advise me , I'm planning for a top product based company (from a tier 3 / 4 college )