Sanika jain

History created!!!!

Gukesh D, youngest player to become the world chess champion❤️🫡

#chess #champion #gukesh

12 Years of Waiting. 12 Years of Heartbreaks. And Now, We Are Champions Again! 🇮🇳🏆

Tears in our eyes. Goosebumps all over. Hearts pounding with pride. India has won the Champions Trophy! 🏏💙

CHAMPIONS ONCE AGAIN! 🏆🇮🇳💙
Let the celebrations begin! 🎉🎊

20% DSA problem-solving patterns that cover 80-90% of problems asked in every coding interview (From Infosys to Microsoft & every company in between)

1. Two Pointers 
2. Sliding Window 
3. Prefix Sums 
4. Merge Intervals 
5. Binary Search (and Variants) 
6. Sorting-Based Patterns 
7. Fast and Slow Pointers 
8. Backtracking & Recursive Search 
9. Divide and Conquer 
10. Linked List Techniques (Dummy Node, In-place Reversal) 
11. Stacks and Queues 
12. Monotonic Stack / Queue 
13. Expression Evaluation (Two Stacks) 
14. String Manipulation & Regular Expressions 
15. Hashmaps & Frequency Counting 
16. Binary Trees & BSTs (Traversal, Construction, Properties) 
17. Path Sum & Root-to-Leaf Techniques 
18. Kth Largest/Smallest Elements (Heaps / QuickSelect) 
19. Top K Frequent Elements 
20. Merge K Sorted Lists 
21. Dynamic Programming (Including Knapsack, Range DP, etc.) 
22. Greedy & Interval Partitioning 
23. Graph Traversals (BFS, DFS) 
24. Graph Algorithms (DAGs, MSTs, Shortest Paths, etc.) 
25. Design Problems (LRU Cache, Twitter, etc.)

Most students struggle with DSA because they think they have weak logic. 
But mostly, it’s because their approach is completely wrong.

If you want to solve problems fast and with solid accuracy, you need to think in patterns.

Without patterns, you can solve every problem in an interview that you’ve seen once, but once you see a new problem, you will get stuck.

That’s why I’ve come out with this amazing DSA Pattern Sheet, which helps you:
✅ identify key patterns and learn when to apply them.
✅ understand scenarios and clues that signal which approach to use.
✅ practice with 5-6 leetcode problems per pattern to solidify learning.
✅ cover 250-300 essential problems, ensuring you master every core concept.
✅ customize the sheet to track progress and adapt it to your needs.

Get the sheet here: https://bit.ly/4cP1QxC

At Google, I learned how to write scalable code.
At Oracle, I learned how to write bulletproof code.

But no matter where you work, one thing remains constant—code reviews will humble you. 😅
Back when I started, code reviews felt like a never-ending checklist:

❌ “Optimize this loop.“
❌ “Where’s the input validation?“
❌ “This could be more efficient.“

I’d spend hours fixing formatting while real issues—security flaws, performance bottlenecks, and maintainability concerns—got buried under minor suggestions. And the worst part? Every round of feedback meant more manual debugging, refactoring, and testing.

Now, imagine if Agentic AI could actually help with these things—not just answer coding questions, but proactively assist with debugging, refactoring, and test generation.

For example, Qodo (formerly Codium) Gen 1.0 takes this concept a step further by introducing Agentic Chat—instead of just giving one-shot responses, it actively analyzes project context, asks the right questions, and executes tasks autonomously.

It’s not just about suggesting optimizations—it understands intent, fetches relevant code snippets, generates test cases, and even integrates with tools like Git and Jira to provide real, actionable insights.

I’ve been experimenting with this, and it feels like the future of coding workflows is shifting towards something smarter. Instead of fixing the same things over and over, what if AI could handle the repetitive tasks, so we focus on the real problem-solving?

Maybe coding isn’t just about writing better anymore. Maybe it’s also about working smarter. 🤔

#SoftwareEngineering #AgenticAI #AIforDevelopers #CodeReviews #DevLife

AI won't take your job, but the person who knows AI will 🙃

Many people worry that AI will take away jobs.
In reality, it automates repetitive tasks, but humans are still needed for creativity, problem-solving, and decision-making.

Instead of fearing it, we should learn to work with AI tools. The more you understand AI, the more valuable you become.

Steps to Prepare for an AI-Driven Job Market:
1. Learn the basics of AI and machine learning through online courses and webinars.
2. Participate in hackathons and coding competitions for hands-on experience.
3. Intern with startups or companies working in AI or data science.
4. Build a strong LinkedIn profile and connect with professionals in the AI field.

I recently got to know about a webinar by NVIDIA and thought it would be super insightful and helpful for you all too, so I decided to share the details. It’s completely free!

🔹 Webinar: Accelerate Your AI Development with NVIDIA NIM Microservices
🔹 Date: 27th February 2025 | Time: 2:00 PM IST
🔹 Link: https://nvda.ws/40HrjF5

What’s in it for us?
1. Overcome Do It Yourself AI challenges
2. Explore cool features like Multi-LoRA Adaptor and Visual Language Models (VLMs).
3. See real-world examples like AI Virtual Assistants.

This isn’t a paid collaboration or anything—I just found it interesting and thought to share it with my network. It’s first-come, first-served, so don’t wait—do register!

Let’s learn and grow together!

#AI #CareerGrowth #Webinar #NVIDIA