tech lead asks: your database is handling 10k requests/sec. would you scale it vertically, add read replicas, or introduce sharding? your answer reveals how much you actually understand system design.

have you ever wondered why RAM comes in 8, 16, 32, 64, 128 GB... but rarely 10, 20, or 100 GB? there's a computer science reason behind this. do you know why?

List of Companies hiring for SDE-1 roles Entry-level hiring is not closed. It is just more selective than it used to be. check this practical list of companies that regularly hire SDE-1 / Associate Software Engineers in India (as of late 2026): 1. Amazon • Actively hiring SDE-1 through University Talent Acquisition • Locations: Hyderabad, Bengaluru, Chennai, others • Focus: DSA, problem-solving, Leadership Principles • Strongest structured path for freshers right now 2. Microsoft • Regular SDE-1 / Software Engineer hiring for India Development Centers • Focus: Coding + fundamentals • Off-campus and campus both possible 3. Google • Hiring exists, but volume is lower for pure freshers • Stronger path is intern → return offer or strong OA performance • High bar on coding and problem-solving 4. Flipkart, Swiggy, Zomato, PhonePe • Product companies that hire SDE-1 • Focus: Backend, scalability basics, ownership • Good for people who want real product experience early 5. Startups (Series A–C) • Abstrabit, various AI and SaaS startups • Often open to 0–1 year experience • Skills: Full-stack or backend with ability to ship features 6. Banks and fintech • Citi, Mastercard, and similar • SDE-1 / Associate roles in engineering teams • Focus: Java, SQL, system basics 7. Product companies (Salesforce, Adobe, Atlassian-style) • Hire Associate / SDE-1 roles in India • Usually prefer some internship or project experience What actually gets you shortlisted for SDE-1: • Clean DSA (medium problems under time pressure) • One or two solid projects with code on GitHub • Ability to explain your code and trade-offs • Basic system design awareness (even at entry level) Amazon is currently the most consistent structured option for pure freshers in India. Other companies hire, but the volume and process vary a lot. Are you targeting Amazon-style structured hiring, or product startups for your first role?

if you think you're good at system design, design an AI agent that can remember, reason, and call APIs. which architecture would you choose?

AI might be the fastest-growing industry in history and still one of the hardest ways to make money. Why are AI companies burning billions despite explosive user growth? A) GPU and infrastructure costs B) Free users consuming expensive compute C) Price wars killing profit margins D) Users love AI but won't pay enough

Companies are still hiring Software Engineers every single day The market is not dead, The numbers are just different from what most people see on LinkedIn. See what top companies are paying in 2026 (US total compensation): 1. Anthropic • Role: Software Engineer / Member of Technical Staff • Median TC: ~$880K+ • Skills: Production systems, LLM infrastructure, reliability, strong CS fundamentals 2. OpenAI • Role: Software Engineer / Research Engineer • Median TC: ~$875K • Skills: Distributed systems, model serving, evaluation, shipping under ambiguity 3. xAI • Role: Software Engineer • Median TC: ~$620K • Skills: Large-scale infrastructure, training systems, backend performance 4. Meta • Role: E5 Senior Software Engineer • TC range: ~$400K–$450K+ • Skills: System design, product sense, high-scale backend, coding interviews 5. Google • Role: L5 Senior Software Engineer • TC range: ~$400K–$430K • Skills: Algorithms, system design, distributed systems, ownership 6. Netflix • Role: Senior Software Engineer • TC range: ~$400K–$550K (high base, low equity) • Skills: Full ownership, strong judgment, production reliability 7. Stripe / Databricks • Role: Senior / Staff Engineer • TC range: ~$400K–$700K+ at senior+ levels • Skills: Payments / data systems, API design, reliability at scale Key reality: • Most of the extreme numbers are total compensation (base + equity + bonus), not cash in hand. • AI labs and infrastructure companies are currently paying the highest premiums. • Traditional FAANG still pays very well, especially at senior levels. • The skill that separates candidates is not “I know Python” It is system design + production experience + ability to ship. The race is still on. The companies that pay the most are looking for people who can build and run real systems, not just solve LeetCode. Which company are you targeting right now, and what skill are you weakest in for that level?

Seriously job market is cooked for us, I applied a year ago, Today's received someone viewed my application.

That's the reason, I'm always saying avoid noise and focus on learning.

if AI adoption is exploding and millions of users are paying for AI tools, why are AI companies still burning billions? are we witnessing the biggest tech gold rush or the most expensive bubble in history?