avrl ☘

Announcing 30 Days of Real Scale: Applied System Design! Thanks for Showing so much support on "System Design Talks Series", means a lot to me! It's officially done! Now it's time to move one step ahead, to see how these concepts are applied at scale! What will you get: 0. Daily one post on how to orgs scaled their services from 1K RPS to 1M RPS. 1. Visual Diagrams and Step by step explainations. 2. How engineers thought of tradeoffs. 3. Pure system design concepts applied on real problems. 4. Resources you can research on your own. 5. Articles on what problems companies faced at scale and how they solved it. This is for anyone who is in tech, preparing for interviews & studying in college, or just wants to learn. Day 1 Starts Monday 20th April afternoon! Be Ready Guys, It's gonna be fun!

@ConsciousRide Nice list bro

10 Terms Every AI Engineer Should Know in 2026: 1. LLM Large Language Models are massive neural networks trained on enormous datasets to predict, generate, and reason with text, code, and other sequences at human-level fluency. 2. RAG Retrieval Augmented Generation means fetching relevant external documents or data at inference time and feeding them into the LLM so responses are grounded, up-to-date, and less prone to hallucination. 3. AI Agents AI Agents are autonomous systems that can plan, use tools, call APIs, remember context across steps, and execute multi-step workflows with minimal human intervention. 4. Multimodal Models Multimodal models process and generate across multiple data types - text, images, audio, video - within a single unified architecture, enabling richer understanding and creation. 5. Fine-Tuning Fine-Tuning is the process of further training a pre-trained LLM on domain-specific data to specialize its behavior, improve accuracy, or adapt it to custom tasks and styles. 6. Vector Databases Vector databases store and query high-dimensional embeddings at scale, powering fast semantic search, similarity matching, and memory systems for RAG and agent applications. 7. Prompt Engineering Prompt Engineering is the craft of designing precise, structured inputs, instructions, and examples to reliably steer LLMs toward desired outputs without changing model weights. 8. Quantization
Quantization reduces model precision (e.g., from 32-bit to 4-bit or 8-bit) to cut memory usage and speed up inference while preserving most of the original performance. 9. MLOps
MLOps brings DevOps practices to machine learning - covering versioning of models and data, automated pipelines, monitoring drift, and continuous deployment of AI systems in production. 10. Chain-of-Thought Reasoning
Chain-of-Thought Reasoning prompts models to break problems into explicit intermediate steps, dramatically improving performance on complex logic, math, and multi-hop tasks.

@neogoose_btw Let them download from releases section.

if you understand something in powershell scripting can you please review this PR I'll give you fff contributor achievement shield via co-authored-by github.com/dmtrKovalenko/…

@rambuilds_ Nice list bro

Programming Languages & Their Uses ✅ PYTHON 1. Data Science 2. Machine Learning 3. Web Development 4. Automation 5. Game Development 6. Data Analysis 7. Data Visualization 8. Artificial Intelligence ☕ JAVA 1. Android Apps 2. Server-Side Apps 3. Enterprise Apps 4. Web-Based Apps 5. Big Data 6. Game Development 7. Internet of Things 8. Cloud Computing 💻 C++ 1. Game Development 2. GUI Apps 3. Operating Systems 4. Database Systems 5. Embedded Systems 6. Networking 7. Virtual Reality 8. Computer Vision 🟨 JAVASCRIPT 1. Server-side Development 2. Web Dev & Apps 3. Mobile Apps 4. Machine Learning 5. IoT 6. Automation 7. Embedded Systems 8. Chatbot Development 🟥 SWIFT 1. iOS App Development 2. Deep Learning 3. IoT 4. Server-side Development 5. Open-source Projects 6. macOS App Dev 7. Machine Learning 8. Automation 🟩 C# 1. Game Development 2. Web Dev & Apps 3. IoT 4. Backend Services 5. Windows App Dev 6. Robotics 7. Cloud Computing 8. Database Programming

This is the recurring trend, the opposition is shit that they cannot unite & bring out the facts, all they do is fight among themselves & cut each other & benefit bjp. Ill just say, look at meghalya border issues where bip is ruling (no security & open borders with illegal trade happening) & i cant digest that the home minister canmot use military to fastrack the border strenghting coz its a center topic.

@avrldotdev man, I sure hope you are wrong this time!

Well, it indeed looks like BJP is in power in West Bengal. TMC has been thrown out, and rightfully so in my opinion. Now, with the public mandate firmly behind BJP, we all expect a drastic reduction in illegal cross-border immigration, modernization, crime reduction, and a whole lot of acceleration in West Bengal. Right????????????? (please prove me right BJP, do NOT make it any harder for us right wingers)

@RishabhSri0505 @VazeKshitij How misleading? Its from MHA though (if its misleading, give us the correct figures & take credit no?) and they cite it, and they did nrc in Assam and found 5L Hindus with forged docs against 7L Muslims, so the base they talk on is shaky & not strong enough for me support them

@avrldotdev @VazeKshitij Actually it's misleading figure but yes the government should nrc and carry out drives if they really want stability in this nation

@MaheshPawaar Nice list ngl

made this checklist for my own prep. didn't expect 20k people to find it useful. if something's missing, add it. it's meant to be customized.

@MaheshPawaar Nice list bro, will check it out

made a backend engineering checklist for myself. 5 pillars, 45+ topics, only the stuff that actually matters on the job. check it out. link in reply.

@wahab_twts Yes, it matters alot

@avrldotdev good list but how they work together matters more

10 Data Storage concepts on a weekend: 0. File-based storage 1. Page cache 2. B+ tree index 3. Compaction (LSM) 4. Compression (basic) 5. Checkpointing 6. Snapshotting 7. MVCC (version concurrency) 8. Garbage collection 9. Disk & Memory levels

@wahab_twts Nice bro, congratulations

I started my X journey just 41 days ago. Today we got monetized!! 🎉 I’m genuinely shocked and so happy. Thank you all for the support. 2026 is going to be an amazing year. 🫶

@themishra4402 Thanks bro do read about these

@avrldotdev i bookmarked this post brother

@ash_twtz Then save it :)

@avrldotdev Wow 😧 never knew

@ravikiran_dev7 Thanks bro save it pleae

@avrldotdev Great share 🙌🏻

@devXritesh Thanks vro do save it

@avrldotdev Helpful topics

@devXritesh Using them

USA has: ChatGPT, Grok, Claude, Gemini, Copilot. China has: DeepSeek, Qwen, GLM, Kimi, MiniMax. India has: Krutrim, Sarvam, Hanooman, OpenHathi. Rest of the world, What are y’all even doing?

@VazeKshitij @Palak3312 x.com/i/status/20498…

be laude, thodi sharam toh rakh le. This catfishing MF is literally stealing robotics tweets and posting as if it's their own. If @Palak3312 can name the MCU, the motor driver, and the type of wheel on the robot in this picture without googling, I'll gladly shut the hell up.

@mvrckgmi Welcome

@avrldotdev Thanks for the list

10 API design concepts to learn for backend: 0. Idempotency 1. Pagination (cursor/offset) 2. Rate limiting (DDoS protection) 3. Versioning (backwards compatibility) 4. Filtering/Sorting (query flexibility) 5. Timeouts & Retries 6. HATEOAS 7. API Gateway 8. Partial Responses (field selection) 9. Error modeling (consistency)

@mvrckgmi Thanks

@avrldotdev Thanks for sharing. Always good to see your posts

10 API design topics to learn for backend: 0. REST API with versioning 1. Pagination (cursor/offset) 2. Filtering & sorting 3. Idempotent endpoints 4. OpenAPI Spec 5. API gateway 6. Rate limiting per user 7. Request validation 8. Error standardisation 9. Metrics & tracing

@clumsyaf222 Its gonna happen many times in future, just remember, its not permanent & just in your head

@avrldotdev sure :)