Kabhi kabhi dsa ki jgh ye pdh leta hu...!

Passion is the ultimate fuel. Be passionate enough !

1/ Most people “prepare for interviews”. If you’re aiming for top spots like @Rippling , @databricks , @stripe , @nvidia , @Razorpay , @JioHotstar etc, you may need to rebuild yourself for that bar. Here’s the PLAYBOOK for 0–5 YOE folks in India. Save this. 🔖

Is it consistency ?

Let's talk honestly how did you aced DSA ?

If you are learning DBMS, try this playlist and you will never be disappointed. youtube.com/playlist?list=PL… All thanks to @riti2409 Didi

Have been exploring @LangChain recently and i am totally loving it !

What is the best approach to tackle DSA and CP problems ?

It's our 🏆 🇮🇳

software is still about thinking software has always been about taking ambiguous human needs and crystallizing them into precise, interlocking systems. the craft is in the breakdown: which abstractions to create, where boundaries should live, how pieces communicate. coding with ai today creates a new trap: the illusion of speed without structure. you can generate code fast, but without clear system architecture – the real boundaries, the actual invariants, the core abstractions – you end up with a pile that works until it doesn't. it's slop because there's no coherent mental model underneath. ai doesn't replace systems thinking – it amplifies the cost of not doing it. if you don't know what you want structurally, ai fills gaps with whatever pattern it's seen most. you get generic solutions to specific problems. coupled code where you needed clean boundaries. three different ways of doing the same thing because you never specified the one way. as Cursor handles longer tasks, the gap between "vaguely right direction" and "precisely understood system" compounds exponentially. when agents execute 100 steps instead of 10, your role becomes more important, not less. the skill shifts from "writing every line" to "holding the system in your head and communicating its essence": - define boundaries – what are the core abstractions? what should this component know? where does state live? - specify invariants – what must always be true? what are the constants and defaults that make the system work? - guide decomposition – how should this break down? what's the natural structure? what's stable vs likely to change? - maintain coherence – as ai generates more code, you ensure it fits the mental model, follows patterns, respects boundaries. this is what great architects and designers do: they don't write every line, but they hold the system design and guide toward coherence. agents are just very fast, very literal team members. the danger is skipping the thinking because ai makes it feel optional. people prompt their way into codebases they don't understand. can't debug because they never designed it. can't extend because there's no structure, just accumulated features. people who think deeply about systems can now move 100x faster. you spend time on the hard problem – understanding what you're building and why – and ai handles mechanical translation. you're not bogged down in syntax, so you stay in the architectural layer longer. the future isn't "ai replaces programmers" or "everyone can code now." it's "people who think clearly about systems build incredibly fast, and people who don't generate slop at scale." the skill becomes: holding complexity, breaking it down cleanly, communicating structure precisely. less syntax, more systems. less implementation, more architecture. less writing code, more designing coherence. humans are great at seeing patterns, understanding tradeoffs, making judgment calls about how things should fit together. ai can't save you from unclear thinking – it just makes unclear thinking run faster.

"In almost any subject, your passion for the subject will save you. If you care enough for a result, you will most certainly attain it. If you wish to be good, you will be good. If you wish to be rich, you will be rich. If you wish to be learned, you will be learned. Only then you must really wish these things and wish them with exclusiveness, and not wish 100 other incompatible things just as strongly. " - William James

🌈 Day 180/180 #DSA ✅ 180 days | 500 problems 🏥 Coded through health struggles 🙏 Eternal thanks @Striver_79 @takeUForward 💡 “It wasn’t about being the best. It was about being better than yesterday.” RT to inspire someone to start their journey! ❤️

🖥️ Day 179/180 #DSA ✔ OS: System calls, process mgmt, protection 🎨 DSA: Min area coverage color maximization 💡 "OS manages resources, DSA uses them wisely!" Reply with your favorite system call! 👇

🚀 Live at NIET COLLEGE, Greater Noida! EigenCloud 101 & Restaking Workshop with @Vikash_8090_b 🎯 Learn to: ✅ How EigenCloud works, About AVS. ✅ Eigen DA, Compute ✅ Get Testnet ETH ✅ Stake LSTs ✅ Restake on @eigencloud ✅ Delegate #EigenLayer #Restaking #EigenAlphaVikash

🖥️ Day 178/180 #DSA ✔ Started OS: Process scheduling 🧩 LC 1504: Matrix → Histogram magic 🗑️ LC 27: In-place removal 💡 "Efficient code needs efficient systems!" Reply with your favorite OS concept! 👇

⚔️ Day 177/180 #DSA ✔ CodeChef: 4 problems | 200 rank jump 🧩 LeetCode 1504: Count Submatrices → DP Stack 💡 "Matrix problems are just histograms in disguise!" RT if you’ve felt the contest rush! 🚀

🎮 Day 176/180 #DSA ✔ String Game → Frequency magic ➕ Add Two Numbers → LL math 🔢 Zero Subarrays → n(n 1)/2 trick 💡 "4 days left – but the real win is the mental toolkit built!" Reply with your favorite math-based problem! 👇

🔗 Day 175/180 #DSA ✔ Reversed LL → 3-pointer ballet ♻️ Deduped sorted list ⚡ Plusle/Minun array 💡 "5 days left, but the real win is the skills gained!" Reply with your favorite LL problem! 👇