Inosuke

@PhantomPetalss Fr.

@Inosukeei_coder Too much compitition 🤣

What’s stopping more people from getting software jobs? - too much competition. - poor guidance. - inconsistency. - weak projects. Choose one.

@_Chandan_17 Idk

Interviewer: Your API works perfectly with 1K users. It falls apart at 100K. You can't change the infrastructure. What would you use to fix it?

@Owais_ez 🤌🏻

How does an argument feel when you know you're right

@ram_t3ch Vs code + intellj ide

be honest, as a dev which AI code editor do you prefer?

@harsh567_8 Almost I can buy 5 times X premium

Select one .

@PhantomPetalss Luck always 👑

@Inosukeei_coder For me luck beats hardwork 🤣

Tech truth: Learning is easy. Building is hard. Explaining is harder. Repeating for months is hardest. That’s why consistency beats motivation.

@droidbuilds @Hiteshdotcom 7

Had to buy this React Native Cohort because of the pricing 💀 Got a special discount… Used code THALA FOR A REASON 🫡 @Hiteshdotcom sir, see you soon.

@droidbuilds Yeah

@Inosukeei_coder Too much competition even for unpaid internship

@Saanvi_dhillon There is no compitition, just everyone doing same - mern stack, same projects

@Inosukeei_coder Poor guidance and too much competition

@droidbuilds Reply krte hie app close kiya hoga

@Inosukeei_coder Ye reply kabka kra tha abhi ghr aaya toh gaya hai 😂

30 tech companies with massive workforce + strong engineer pay.. - Amazon — 1,576,000 employees — SWE avg pay: ~$190k–$230k . - IBM — ~270,000 employees — SWE avg pay: ~$150k–$190k. - Microsoft — 228,000 employees — SWE avg pay: ~$220k–$250k . - Accenture — ~210,000 tech total company is far bigger — SWE avg pay: ~$120k–$170k. - Alphabet (Google) — 190,820 employees — SWE avg pay: ~$250k–$340k . - Apple — 166,000 employees — SWE avg pay: ~$230k–$280k. - Oracle — 162,000 employees — SWE avg pay: ~$180k–$230k. - Cisco — ~90,000 employees — SWE avg pay: ~$190k–$230k. - Salesforce — 76,453 employees — SWE avg pay: ~$210k–$260k . - Lenovo — 72,000 employees — SWE avg pay: ~$120k–$170k . - HP — 55,000 employees — SWE avg pay: ~$140k–$180k. - Intel — ~124,800 employees — SWE avg pay: ~$180k–$230k. - Dell — ~97,000 employees — SWE avg pay: ~$140k–$180k . - SAP — 109,973 employees — SWE avg pay: ~$160k–$210k . - Meta — ~74,000 employees — SWE avg pay: ~$280k–$380k . - Adobe — 31,360 employees — SWE avg pay: ~$210k–$260k . - NVIDIA — ~36,000 employees — SWE avg pay: ~$240k–$320k. -Uber — ~31,000 employees — SWE avg pay: ~$220k–$300k. LinkedIn — ~18,000 employees — SWE avg pay: ~$316k. - Intuit — 18,200 employees — SWE avg pay: ~$210k–$260k . - Airbnb — ~7,300 employees — SWE avg pay: ~$250k–$330k. - Atlassian — ~14,400 after recent layoffs — SWE avg pay: ~$180k–$240k . - ServiceNow — ~26,000 employees — SWE avg pay: ~$210k–$270k. - Workday — ~20,400 employees — SWE avg pay: ~$190k–$240k. - PayPal — ~27,000 employees — SWE avg pay: ~$170k–$220k. - Shopify — ~8,100 employees — SWE avg pay: ~$170k–$230k . - Expedia — 16,000 employees — SWE avg pay: ~$160k–$210k . - Block — ~12,000 employees — SWE avg pay: ~$200k–$270k. - Pinterest — ~4,200 employees — SWE avg pay: ~$220k–$300k. - Dropbox — ~2,300 employees — SWE avg pay: ~$210k–$280k.

@redlaysdedo Desktop

Be honest, which device is better for students? Desktop or Laptop

@droidbuilds Glad 🙌🏻

@Inosukeei_coder Thanks for sharing.. Helpful 🙌

@_Chandan_17 Fr.

@Inosukeei_coder Most people don’t know what to build or how to stand out.

@devXritesh Fr bro 🥀

@Inosukeei_coder Poor guidance with weak projects.

@devXritesh 🙌🏻

@Inosukeei_coder These types of DSA problems asked in Big tech. Just need practice and get the job .

🧠 Google autocomplete is straight-up sorcery. You type just "how to..." And it instantly drops: • how to make money • how to cook pasta • how to tie a tie This happens across 16.4 BILLION searches every single day in 2026. How the hell does it return perfect suggestions in under 100ms at this scale? Deep technical breakdown 👇 1. Trie (Prefix Tree) - The Magic Data Structure Every character is a node in a tree. Typing “h-o-w- -t-o” walks straight to the exact prefix node in O(K) time (K = length of input). No scanning billions of queries just instant pointer to all completions. 2. Precomputed + Smart Ranking Offline pipelines crunch trillions of past searches daily. Each trie node stores top-K suggestions pre-ranked by: • Frequency & trends • Click-through rate • Personalization (your history) + location + freshness ML models keep everything updated in real-time. 3. Production-Grade Scaling • Sharded & replicated across global data centers • In-memory layers (custom + Redis-style caching) for hottest prefixes • Edge/CDN caching + microservices load balancing • Handles 100,000+ queries per second with p99 latency <100ms This exact pattern powers autocomplete on LinkedIn, Amazon, YouTube anywhere you see instant suggestions. Backend & system design devs: this is the gold standard. Saved this thread? Drop 🔥 below. What Google feature should I break down next?

@iamMayurChouhan Build kro kuch, game khelo, chill maro

I got 4 days off and i have no plans, what to do in pune? 😭

@PhantomPetalss 🫠

I thought I was working hard in silence… turns out my mom is running a full PR agency behind my back 😭 At this point the neighborhood knows my study schedule better than I do 🤡