Subash @subashtalks

I am going to teach everything about Linux in 30 days in this new month of June. It will be a tutorial per day. If interested say hi 👋

Nano Banana Is FREE. OpenClaw is FREE. SkySnail is FREE (limited). ViralityAI is FREE. Claude AI is FREE. Microsoft Copilot is FREE. Perplexity AI is FREE. Bing Image Creator is FREE. Grok is FREE. Playground AI is FREE. Runway ML is FREE (limited). Pika Labs is FREE. ElevenLabs is FREE. Audacity is FREE. DaVinci Resolve is FREE. OBS Studio is FREE. Blender is FREE. Figma is FREE. Photopea is FREE. Deepseek is FREE. QuillBot is FREE. DeepL is FREE. Tome is FREE. Gamma is FREE (limited). Notion is FREE. Zapier is FREE. HuggingFace Spaces is FREE. The internet is your free university. Stop looking for excuses. 🔖 BOOKMARK NOW

40 techniques that'll help you scale a system 40x: 1 Horizontal Scaling 2 Vertical Scaling 3 Caching 4 Load Balance 5 Sharding 6 Replication 7 Partition 8 Autoscale 9 Microservices 10 Event Driven 11 Queueing 12 Stateless 13 Indexing 14 Timeouts 15 Retries 16 Rate Limit 17 Circuit Breaker 18 Backpressure 19 GeoDNS 20 Multi-Region 21 Container 22 Orchestration 23 Service Mesh 24 Diagonal Scale 25 CDN 26 Monitoring 27 Tracing 28 Failover 29 High Availability 30 Graceful Degradation 31 Consistent Hashing 32 CAP Tradeoff 33 Modularity 34 Bulkhead 35 Prefetching 36 Lazy Load 37 Capacity Planning 38 Hot Standby 39 Read Replica 40 Write Batching There are different ways to scale. The best solution & numbers depend on your needs. Remember, everything is a tradeoff. What else would you add?

If you want to master RAG in 2026. Build these projects. Project 1: PDF Chat Application Upload PDFs, ask questions, retrieve context-aware answers, citations, semantic search. Project 2: AI Research Assistant Search across multiple documents, summarize findings, generate references, compare sources. Project 3: YouTube Q&A Engine Convert videos into searchable knowledge bases with transcript retrieval and timestamp citations. Project 4: AI Customer Support Bot Connect company docs, FAQs and support history with contextual responses and memory. Project 5: GitHub Codebase Assistant Ask questions across repositories, retrieve relevant code snippets, explain architecture. Project 6: Multi-Modal RAG System Combine PDFs, images, audio and databases into one unified retrieval pipeline. Project 7: Personal Knowledge OS Build your own second brain with notes, bookmarks, search and AI memory retrieval. Project 8: Agentic RAG Workflow Create autonomous agents that search, retrieve, reason and execute multi-step tasks. Project 9: Enterprise Search Engine Slack, Notion, Google Drive, Confluence retrieval with permission-aware search systems. Project 10: Medical/Legal RAG Assistant Domain-specific retrieval with hallucination reduction, citations and verification pipelines. Most people consume AI content. Builders ship systems.

As a Principal Backend Engineer with over 12 years of experience, I can tell you quite certainly that if you're still getting rejections in system design interviews after good efforts, I think your fundamentals are not strong... Dedicate 2-3 months to mastering these design fundamentals, then practice designing a few systems(and do plenty of mock interviews). Scaling & Architecture ↬ CDN ↬ Caching ↬ Sharding ↬ Queueing ↬ Replication ↬ Partitioning ↬ API Gateway ↬ Rate Limiting ↬ CAP Theorem ↬ Microservices ↬ Load Balancing ↬ Fault Tolerance ↬ Database Scaling ↬ Service Discovery ↬ Consistency Models ↬ Eventual Consistency ↬ Distributed Transactions ↬ Monolith vs Microservices ↬ Leader Election Databases & Storage ↬ Leader-Follower Replication ↬ WAL (Write Ahead Log) ↬ Asynchronous Processing ↬ Transaction Isolation ↬ Read/Write Patterns ↬ Consistent Hashing ↬ Redis/Memcached ↬ Backup & Restore ↬ Hot/Cold Storage ↬ Data Partitioning ↬ Object Storage ↬ SQL vs NoSQL ↬ Data Retention ↬ Data Modeling ↬ OLAP vs OLTP ↬ ACID & BASE ↬ Bloom Filters ↬ File Systems ↬ S3 Basics ↬ B+ Trees ↬ Indexing Communication & APIs ↬ JWT ↬ CORS ↬ OAuth ↬ Throttling ↬ Serialization ↬ API Security ↬ Long Polling ↬ WebSockets ↬ API Gateway ↬ Idempotency ↬ Service Mesh ↬ Retry Patterns ↬ REST vs gRPC ↬ API Versioning ↬ Circuit Breaker ↬ API Rate Limits ↬ Fan-out/Fan-in ↬ Protocol Buffers ↬ Message Queues ↬ Dead Letter Queue Reliability & Observability ↬ Metrics ↬ Alerting ↬ Failover ↬ Logging ↬ Rollbacks ↬ Monitoring ↬ Heartbeats ↬ Retry Logic ↬ Autoscaling ↬ SLO/SLI/SLA ↬ Load Testing ↬ Error Budgets ↬ Health Checks ↬ Circuit Breaker ↬ Incident Response ↬ Chaos Engineering ↬ Distributed Tracing ↬ Canary Deployments ↬ Graceful Degradation ↬ Blue-Green Deployment

As an AI Engineer. Please learn: - Harness engineering, not just prompt engineering - Prompt caching vs. semantic caching tradeoffs - KV cache management at scale - Speculative decoding vs quantization - Structured output failures & fallback chains - Evals (LLM-as-judge + human evals) - Cost attribution per feature, not just per model - Agent guardrails & loop budgets - LLM observability as a first-class discipline - Model routing & graceful fallback logic - Knowing when to fine-tune vs. in-context learning

So true.

நம்ம ஏற்கனவே character sheet, environment sheet, item sheet வச்சு எப்படி consistency கொண்டு வர்றதுன்னு பார்த்தோம். ஆனா, வீடியோன்னு வரும்போது "scene by scene" என்ன நடக்கணும்னு ஒரு பிளான் வேணும்ல? அதுக்குதான் storyboard! AI video-ல random cuts, awkward transitions வராம smooth cinematic flow கிடைக்க storyboard ரொம்ப useful 🔥 முக்கியமா action scene, emotional scene, dialogue scene மாதிரி videos-ல storyboard இருந்தா output இன்னும் professional feel கொடுக்கும். “இந்த frame அப்புறம் இந்த frame”ன்னு AI-க்கு clear visual direction கிடைக்குறதால storytelling strong-ஆ இருக்கும் 🚀 அதுமட்டுமில்லாம ai video உருவாக்கும்போது பல தடவை சொதப்பலா இருக்கும். அதனால உங்க credits தான் வேஸ்ட் ஆகும். அதுவே storyboard image கிரியேட் பண்ணி preview பார்த்துகிட்டா உங்க credits-ஐ மிச்சம் பண்ணலாம். எப்படி storyboard image create பண்றது? ரொம்ப சிம்பிள். இந்த வீடியோவுக்கு நான் கொடுத்த prompt: create storyboard image for below story, A rusty cleaning robot works alone in a futuristic abandoned city. One day it finds a tiny flower growing through concrete. It protects the flower from storms, birds, and machines. Final scene reveals the flower field slowly spreading across the city while the robot watches peacefully. ஆக்ட்சுவலா இந்த வீடியோ 30 seconds வேணும்னு ரெண்டு பார்டா கிரியேட் பண்ணுனேன். video prompt: Create video based on attached image. no text on video. use voice over.

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50 CHROME EXTENSIONS THAT ARE ACTUALLY USEFUL 1. uBlock Origin — block every ad 2. Ghostery — see who tracks you 3. Privacy Badger — auto block trackers 4. ClearURLs — remove tracking from links 5. HTTPS Everywhere — force secure browsing 6. OneTab — collapse all tabs instantly 7. Toby — organize tabs in groups 8. Momentum — focused new tab page 9. Workona — workspaces for tabs 10. Session Buddy — save tab sessions 11. Grammarly — fix writing anywhere 12. LanguageTool — grammar in 30+ languages 13. Mailtrack — email open tracking 14. Simplify Gmail — cleaner inbox 15. Boomerang — schedule emails smartly 16. ColorZilla — pick colors from pages 17. WhatFont — identify any font 18. Wappalyzer — see any site's tech 19. Pesticide — outline CSS elements 20. Window Resizer — test responsive design 21. GoFullPage — full page screenshots 22. Nimbus — annotate screenshots fast 23. Loom — record your screen fast 24. Awesome Screenshot — capture and edit 25. Screenity — open source recorder 26. Raindrop — bookmarks that work 27. Save to Pocket — read articles later 28. Speechify — read pages out loud 29. Mercury Reader — distraction free reading 30. Zotero — organize research sources 31. Dark Reader — dark mode every site 32. Bitwarden — free password manager 33. Video Speed Controller — speed up videos 34. Unhook — remove YouTube clutter 35. News Feed Eradicator — kill social feeds 36. SimilarWeb — check site traffic 37. Tampermonkey — run custom scripts 38. ChatGPT for Chrome — AI in every tab 39. Merlin AI — GPT on any website 40. Compose AI — autocomplete your writing 41. Wordtune — rewrite sentences with AI 42. DeepL — AI powered translations 43. Perplexity — AI search assistant 44. Monica AI — AI copilot for browsing 45. Sider AI — ChatGPT sidebar for pages 46. MaxAI — summarize any page with AI 47. Harpa AI — automate web tasks 48. Tactiq — AI meeting transcripts 49. tl;dv — record and summarize meetings 50. SciSpace — understand research papers Your browser can do 10x more than you think. Most people never install a single one.

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NotebookLM + Google Gemini FULL COURSE 3 HOURS (Build & Automate Anything)

I canceled Spotify. I canceled Disney+. I canceled Apple TV+. No more monthly payments. Claude turned my laptop into a free entertainment hub that’s better than all of them *combined*. Here are 9 prompts that rebuild the whole system for free (Save this).

As an AI Engineer. Please learn: -Prompt caching & semantic caching tradeoffs -KV cache management at scale -Speculative decoding vs quantization -RAG evaluation (RAGAS + human evals) -Cost monitoring & hidden token leaks -Agent guardrails & infinite loop detection

Java + Spring Boot → Backend APIs Java + Hibernate → ORM / DB Access Java + JDBC → Database Connectivity Java + JPA → Data Persistence Java + Microservices → Scalable Systems Java + Kafka → Event Streaming Java + Redis → Caching Java + Android SDK → Mobile Apps Java + JavaFX → Desktop Apps Java + Maven / Gradle → Build Tools Java + JUnit → Testing Java + AWS SDK → Cloud Apps Java + Docker → Containerization Java + Spark → Big Data Processing one language....multiple usecase still people say “java is outdated” 🫩

Nano Banana Is FREE. OpenClaw is FREE. SkySnail is FREE (limited). ViralityAI is FREE. Claude AI is FREE. Microsoft Copilot is FREE. Perplexity AI is FREE. Bing Image Creator is FREE. Grok is FREE. Playground AI is FREE. Runway ML is FREE (limited). Pika Labs is FREE. ElevenLabs is FREE. Audacity is FREE. DaVinci Resolve is FREE. OBS Studio is FREE. Blender is FREE. Figma is FREE. Photopea is FREE. Deepseek is FREE. QuillBot is FREE. DeepL is FREE. Tome is FREE. Gamma is FREE (limited). Notion is FREE. Zapier is FREE. HuggingFace Spaces is FREE. The internet is your free university. Stop looking for excuses.

MASTER CLOUD ENGINEERING CLOUD ENGINEERING MASTER TREE │ ├── 1. Cloud Fundamentals │ ├── What is Cloud Computing │ ├── Cloud Models │ │ ├── IaaS │ │ ├── PaaS │ │ └── SaaS │ ├── Deployment Models │ │ ├── Public Cloud │ │ ├── Private Cloud │ │ └── Hybrid Cloud │ └── Benefits (Scalability, Cost, Flexibility) │ ├── 2. Core Cloud Providers │ ├── AWS │ ├── Microsoft Azure │ ├── Google Cloud (GCP) │ └── Multi-Cloud Strategy │ ├── 3. Compute Services │ ├── Virtual Machines (EC2, Azure VM) │ ├── Containers │ ├── Serverless (Lambda, Azure Functions) │ └── Auto Scaling │ ├── 4. Storage Services │ ├── Object Storage (S3, Blob) │ ├── Block Storage │ ├── File Storage │ └── Storage Classes & Lifecycle │ ├── 5. Networking │ ├── VPC / Virtual Network │ ├── Subnets │ ├── DNS │ ├── Load Balancers │ └── CDN (CloudFront, Azure CDN) │ ├── 6. Databases │ ├── Relational (RDS, Azure SQL) │ ├── NoSQL (DynamoDB, Cosmos DB) │ ├── Data Warehouses │ └── Database Scaling │ ├── 7. Security │ ├── IAM (Users, Roles, Policies) │ ├── Authentication & Authorization │ ├── Encryption (At Rest / In Transit) │ ├── Firewalls & Security Groups │ └── Compliance & Auditing │ ├── 8. DevOps in Cloud │ ├── CI/CD Pipelines │ ├── GitHub Actions / Jenkins │ ├── Infrastructure as Code │ │ ├── Terraform │ │ └── CloudFormation │ └── Automation │ ├── 9. Containers & Orchestration │ ├── Docker │ ├── Kubernetes (EKS, AKS, GKE) │ ├── Container Registry │ └── Microservices Architecture │ ├── 10. Monitoring & Logging │ ├── CloudWatch / Azure Monitor │ ├── Logging Systems │ ├── Alerts & Notifications │ └── Observability │ ├── 11. Serverless Architecture │ ├── Event-driven Systems │ ├── Functions (Lambda, Azure Functions) │ ├── API Gateway │ └── Cost Optimization │ ├── 12. Cost Management │ ├── Pay-as-you-go Model │ ├── Cost Optimization Strategies │ ├── Reserved Instances │ └── Billing Monitoring │ ├── 13. High Availability & Scaling │ ├── Load Balancing │ ├── Auto Scaling │ ├── Multi-region Deployment │ └── Fault Tolerance │ ├── 14. Cloud Architecture │ ├── 3-Tier Architecture │ ├── Microservices Architecture │ ├── Serverless Architecture │ └── Event-driven Architecture │ ├── 15. Real-World Use Cases │ ├── Web Hosting │ ├── SaaS Applications │ ├── Data Pipelines │ ├── AI/ML Deployment │ └── Streaming Systems │ └── 16. Career Path ├── Cloud Engineer ├── DevOps Engineer ├── Cloud Architect ├── Site Reliability Engineer (SRE) └── Platform Engineer

Learn AI for free directly from top companies. 1 - Anthropic: anthropic.skilljar.com 2 - Google: grow.google/ai 3 - Meta: ai.meta.com/resources/ 4 - NVIDIA: developer.nvidia.com/cuda 5 - Microsoft: learn.microsoft.com/en-us/training/ 6 - OpenAI: academy.openai.com 7 - IBM: skillsbuild.org 8 - AWS: skillbuilder.aws 9 - DeepLearning.AI: deeplearning.ai 10 - Hugging Face: huggingface.co/learn 👇Comment "Learning" if you find this helpful. Repost so others can take help. Must bookmark for future reference.

Leonard Rodman @RodmanAi

a month ago

Uni-1 being an API is the part that matters. Not another model to prompt. Infrastructure you can build on. Products, production pipelines, bespoke tools, creative workflows at scale. One API call, anywhere code runs. The model serious teams were already using is now part of

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You’re not an AI Engineer until you understand these: - Embeddings → meaning as numbers - Vector DB → similarity search - RAG → fetch + generate - Fine-tuning → task-specific training - LoRA → lightweight tuning - Quantization → smaller, faster models - Context window → memory limit - Function calling → structured tool use - Guardrails → safety + constraints - Eval frameworks → measure quality - Tokenization → text → tokens - KV cache → faster inference - Hallucination → confident mistakes - Prompt chaining → multi-step flows Building demos is easy. Production AI is hard.

Claude FULL COURSE 1 HOUR (Build & Automate Anything)

Claude FULL COURSE 1 HOUR (Build & Automate Anything)

AI video பண்ணும்போது பெரிய பிரச்சனை என்னனா—consistency தான். ஒரு character, place, item… first shotல எப்படி இருக்குதோ, next shotல அதே மாதிரி வராது. Single image reference குடுத்தா போதும் நெனச்சா… camera angle change ஆனவுடனே face, body, lighting எல்லாம் வேற மாதிரி போயிடும். அதுக்குதான் reference sheet use பண்ணணும் 🔥 Simple-ஆ சொல்லணும்னா—AIக்கு “இதே தான் correct look, இதையே follow பண்ணு”ன்னு strict-aa சொல்லுற master guide தான் இது 💯 Character sheet-ல face, hairstyle, beard, outfit, body proportions எல்லாம் lock பண்ணிடலாம்… அப்போ video முழுக்க same character தான் வரும் 😎 Environment sheet use பண்ணினா location, lighting, color tone எல்லாம் fix… scene change ஆனாலும் same vibe Item sheet-ல props details set பண்ணினா… design change ஆகாது Short-ஆ சொல்லணும்னா, Reference sheet = full control 🔥 இது இல்லனா AI ஒவ்வொரு shot-லும் new story create பண்ணிடும் 😅 இந்த வீடியோக்கான workflow கீழ இருக்கு..