CodeLooma

🚀 Ultimate System Design Case Studies — Learn How Top Products Work 🚀
Level up your understanding of how the world’s biggest tech systems are built and scaled. Amazing long-form case studies 👇
📺 YouTube – How YouTube Was Able to Support 2.49B Users With MySQL
👉 lnkd.in/efmJw4Dx �
LinkedIn
🚕 Uber – How Uber Finds Nearby Drivers at 1M Requests/sec
👉 lnkd.in/eeqH9Hjh �
LinkedIn
💬 WhatsApp – How WhatsApp Works (System Design)
👉 lnkd.in/eU2fswMi �
LinkedIn
🤖 ChatGPT – How LLMs Like ChatGPT Actually Work
👉 lnkd.in/eSd6fS7n �
LinkedIn
🏡 Airbnb – How Airbnb Works (System Design)
👉 lnkd.in/dGVfstQM �
LinkedIn
📄 Google Docs – How Google Docs Works
👉 lnkd.in/ehPNA7Az �
LinkedIn
🐦 Twitter – How Twitter Timeline Works
👉 lnkd.in/eniXMPfU �
LinkedIn
📦 Apache Kafka – How Kafka Works
👉 lnkd.in/eTtVAjTg �
LinkedIn
🎧 Spotify – How Spotify Works (System Design)
👉 lnkd.in/eGbWVeNW �
LinkedIn
💼 Slack – How Slack Works (Scalable Architecture)
👉 lnkd.in/eATMDjrK �
LinkedIn
👽 Reddit – How Reddit Works
👉 lnkd.in/egmm_P7a �
LinkedIn
🦋 Bluesky – How Bluesky Works
👉 lnkd.in/eEhB8V_k �

3 days ago | [YT] | 1

CodeLooma

🚨 CRITICAL SECURITY ALERT for React & Next.js Developers! 🚨
Heads up, web developers! 🚨 There's a CRITICAL security vulnerability (React2Shell) affecting React Server Components (RSC) and heavily impacting Next.js applications using the App Router.
This isn't just a minor bug – it's an unauthenticated Remote Code Execution (RCE) with a severity score of 10.0. An attacker could potentially run code on your servers!
What you need to do RIGHT NOW:
Update Next.js: Use npx fix-react2shell-next
Update React: Ensure your react-server-dom-* packages are on the latest patched versions (React 19.0.3+ recommended).
Redeploy your applications. A server restart is NOT enough.
Rotate ALL secrets (API keys, database passwords, env vars) if your app was publicly accessible and vulnerable. Assume compromise.
Vercel has sent out urgent notifications. Please check your projects and act fast. Stay safe out there!
#React #Nextjs #WebDevelopment #SecurityVulnerability #React2Shell #CVE #DeveloperAlert

1 month ago (edited) | [YT] | 1

CodeLooma

The numbers don’t lie: A 6% drop in web traffic from its peak. That is millions of users leaving the platform.
The timing? Not a coincidence. It correlates exactly with the launch of Google’s Gemini 3.
The situation inside OpenAI is reportedly tense. According to a leaked internal memo from December 1st, 2025, Sam Altman has declared a “Code Red,” stating:
“We are at a critical time for ChatGPT. We have more work to do to improve the day-to-day experience.”
I feel the exact same way.
Over the last few months, my workflow has shifted. The "King of AI" is becoming a jack-of-all-trades, master of none.
✦ I use ChatGPT less to write (It sounds too robotic).
✦ I use ChatGPT less to search (The knowledge cutoff is frustrating).
✦ I use ChatGPT less for visuals (The aesthetic is too generic).
If you are still relying on a single chat bot for everything, you are falling behind.
Here is the new "Holy Trinity" of AI tools—and the exact prompts I use to master them.
1. The Writer: Claude (Anthropic)
While ChatGPT focuses on logic, Claude has mastered nuance. It captures "voice" and "tone" significantly better than GPT-4 or 5, making it the superior choice for newsletters, essays, and creative copy.
The Strategy: Don't just ask it to write; ask it to mimic.
📂 My "Ghostwriter" Prompt:
"I am pasting three examples of my previous writing below. Analyze them for sentence structure, tone, vocabulary complexity, and rhythm. Then, write a [topic] post about [subject] strictly adhering to that identified style. Do not be flowery. Be punchy."
2. The Researcher: Perplexity (or Gemini Advanced)
ChatGPT is a reasoning engine; it is not a search engine. For deep dives, citations, and real-time fact-checking, you need a tool built on live data.
The Strategy: Use "Chain of Verification" to ensure accuracy.
📂 My "Deep Dive" Prompt:
"Search the web for the latest developments in [Industry/Topic] from the last 4 weeks. Synthesize the top 5 trends into a bulleted list. For each trend, cite the primary source and provide a contrarian viewpoint or potential risk associated with it."
3. The Creator: Midjourney v6 / Sora
DALL-E 3 is easy, but it looks like... AI. For visuals that stop the scroll, Midjourney remains the king of texture and lighting, while Sora has taken over for motion.
The Strategy: Focus on lighting and camera angles, not just the subject.
📂 My "Cinematic" Prompt:
"Editorial photography of [Subject], shot on 35mm Kodak Portra 400, natural volumetric lighting, cinematic composition, depth of field, hyper-realistic textures --ar 16:9 --v 6.0 --style raw"
The Takeaway:
Loyalty to one tool is an efficiency killer. The market has fragmented. To stay ahead in late 2025, you don't need one AI—you need a team of them.
Which tool have you switched to recently? Let me know in the comments.

1 month ago | [YT] | 0

CodeLooma

Happy Children's Day! 🚀 Let's inspire the next generation of innovators, coders, and AI developers. They are the ones who will build the future!

#ChildrensDay #FutureOfTech #AICoding #Innovation #InspireGenZ

2 months ago | [YT] | 0

CodeLooma

Who is known as the "father of Artificial Intelligence"?

2 months ago | [YT] | 0

CodeLooma

In which year was ES6 officially released?

3 months ago | [YT] | 0

CodeLooma

🎥 YouTube Video Playback — System Design (for Devs)

When you hit Play on YouTube, this is what happens under the hood

Request Routing → DNS + load balancers send you to the nearest CDN edge for low latency.

Manifest Fetch → Player downloads a DASH/HLS manifest listing video chunks at multiple bitrates.

Adaptive Bitrate (ABR) → Player picks resolution dynamically based on bandwidth + buffer health.

Chunk Streaming → Small 2–4 s segments stream over HTTP/3 (QUIC) for fast startup & smooth playback.

Edge Caching → Popular videos are cached at edge nodes; cache misses pull from origin (Colossus).

Resilience → Multi-region failover, retry logic, and health-based load balancing keep playback steady.

Telemetry & ML Feedback → Playback metrics train ML models that optimize caching + ABR thresholds.

Key tech: DASH, HLS, QUIC, VP9/AV1, Colossus, Spanner, ML-driven optimization.
Core ideas: Edge-first delivery, adaptive bitrate streaming, continuous feedback loops.

A single click triggers a globally distributed, self-optimizing system — designed for reliability at scale.

#SystemDesign #YouTube #Streaming #Backend #CDN #ABR #DistributedSystems

3 months ago | [YT] | 0

CodeLooma

Which programming language is best for learning and practicing Data Structures & Algorithms (DSA)?

3 months ago | [YT] | 0

CodeLooma

What is 2+ "3"

3 months ago | [YT] | 0

CodeLooma

npm create vite@latest my-react-app -- --template react

3 months ago | [YT] | 0