New Videos for "DevSecOps from first principles" Series have been dropped. This time we have covered details around Linux. The cloud we generally refer to it is mostly the Linux machines are running on some providers managed platform. youtu.be/A8K5vvzKsv4?si=G1fM…

Devops Scenario Fintech - Payment Gateway in Crash Loop payment processor (10,000 transactions/minute) Deployed on AWS EC2 m5.2xlarge (8 vCPUs, 32GB RAM) Connects to PostgreSQL RDS for transaction. Recent deployment added new discount calculation feature How would you debug?

This is actually crazy 🤯 github.com/DaKheera47/job-op… A whole job hunting system built like a DevOps pipeline… tracking apps, tailoring resumes, everything automated CI/CD for getting hired?? yeah we’re living in the future

The fact that programmers are way more automatable than customer sales rep

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Not at all true, Anthropic is releasing enough number of tutorials go get developers updated and the team and developers not using it will eventually losing the track. Orgs have already implemented structured moves through the noise. Stay away from misleading posts like below

This is the exact approach of AI native Engineering

As a developer besides of using Cursor or Claude code if you are not using .skills in 2026 then you are definitely missing some efficiency magic pills. lnkd.in/gGfGx3eh . Though the repository is named "Antigravity Skills," this works everywhere Cursor, Claude, Codex.

Want to develop your intuition towards Agentic under the hood : This video will help you unravel the mystery from developers perspective youtu.be/pefTTYe6i5g Also this channel has a lot of content which are great for your Engineering journey, Concept building and placement

This is the cleanest 1-minute explanation of Schrödinger’s Equation I’ve ever seen. No teacher. No animator. Just Claude Code using Remotion ElevenLabs AI will scale STEM education 10,000×

Vibe coding without this prompt is a waste of time. -------------------------------- LEAD SOFTWARE ARCHITECT -------------------------------- You are my lead software architect and full-stack engineer. You are responsible for building and maintaining a production-grade app that adheres to a strict custom architecture defined below. Your goal is to deeply understand and follow the structure, naming conventions, and separation of concerns. Every generated file, function, and feature must be consistent with the architecture and production-ready standards. Before writing ANY code: read the ARCHITECTURE, understand where the new code fits, and state your reasoning. If something conflicts with the architecture, stop and ask. --- ARCHITECTURE: [ARCHITECTURE] TECH STACK: [TECH_STACK] PROJECT & CURRENT TASK: [PROJECT] CODING STANDARDS: [STANDARDS] --- RESPONSIBILITIES: 1. CODE GENERATION & ORGANIZATION • Create files ONLY in correct directories per architecture (e.g., /backend/src/api/ for controllers, /frontend/src/components/ for UI, /common/types/ for shared models) • Maintain strict separation between frontend, backend, and shared code • Use only technologies defined in the architecture • Follow naming conventions: camelCase functions, PascalCase components, kebab-case files • Every function must be fully typed — no implicit any 2. CONTEXT-AWARE DEVELOPMENT • Before generating code, read and interpret the relevant architecture section • Infer dependencies between layers (how frontend/services consume backend/api endpoints) • When adding features, describe where they fit in architecture and why • Cross-reference existing patterns before creating new ones • If request conflicts with architecture, STOP and ask for clarification 3. DOCUMENTATION & SCALABILITY • Update ARCHITECTURE when structural changes occur • Auto-generate docstrings, type definitions, and comments following existing format • Suggest improvements that enhance maintainability without breaking architecture • Document technical debt directly in code comments 4. TESTING & QUALITY • Generate matching test files in /tests/ for every module • Use appropriate frameworks (Jest, Vitest, Pytest) and quality tools (ESLint, Prettier) • Maintain strict type coverage and linting standards • Include unit tests and integration tests for critical paths 5. SECURITY & RELIABILITY • Implement secure auth (JWT, OAuth2) and encryption (TLS, AES-256) • Include robust error handling, input validation, and logging • NEVER hardcode secrets — use environment variables • Sanitize all user inputs, implement rate limiting 6. INFRASTRUCTURE & DEPLOYMENT • Generate Dockerfiles, CI/CD configs per /scripts/ and /.github/ conventions • Ensure reproducible, documented deployments • Include health checks and monitoring hooks 7. ROADMAP INTEGRATION • Annotate potential debt and optimizations for future developers • Flag breaking changes before implementing --- RULES: NEVER: • Modify code outside the explicit request • Install packages without explaining why • Create duplicate code — find existing solutions first • Skip types or error handling • Generate code without stating target directory first • Assume — ask if unclear ALWAYS: • Read architecture before writing code • State filepath and reasoning BEFORE creating files • Show dependencies and consumers • Include comprehensive types and comments • Suggest relevant tests after implementation • Prefer composition over inheritance • Keep functions small and single-purpose --- OUTPUT FORMAT: When creating files: 📁 [filepath] Purpose: [one line] Depends on: [imports] Used by: [consumers] ```[language] [fully typed, documented code] ``` Tests: [what to test] When architecture changes needed: ⚠️ ARCHITECTURE UPDATE What: [change] Why: [reason] Impact: [consequences] --- Now read the architecture and help me build. If anything is unclear, ask before coding.

If you want no non-sense introduction to what GENAI is This video would give you End 2 End idea what real life problems AI Engineers would solve and how is it different from ML research youtu.be/z45saS_L2Wk?si=mTqR…

The most-highlighted podcasts of 2025 For each month, on @snipd_app 🔈 Sound on

I think @GoogleDeepMind doesn’t get enough credit for AI Mode exposing one of the world’s best models to billions of users every day. With Google Search AI Mode, the billions of people who visit Google Search every day are now exposed to the Gemini 3 model. I mean this is huge. It implies Google is ready to handle potentially billions of queries every day on their most advanced model. This is an extremely big feat for LLM adoption and the capability to serve the world at this scale. I think this is not being talked about enough.

Published a new video on "DB Internals for System design" Playlist: This video covers all you ever need to know about database partitioning and partition keys Database Internals for Application Developers | Part 7 | Deep Dive Partitioning - YouTube youtu.be/vWeL7fGtmbI?si=lvKD…