Want to get into backend development? - Build your own DNS - Build your own BitTorrent - Build your own Decentralized file system - Build your own Interpreter - Build your own kafka - Build your won web scraper - Build your own Redis - Build your own Database Engine - Build your own Distributed Job Queue - Build your own Search Engine - Build your own web server - Build your own Reverse Proxy - Build your own API gateway - Build your own Load Balancer - Build your own URL Shortener - Build your own CDN - Build your own Pub/Sub System - Build your own Task Scheduler - Build your own Email Service - Build your own File Storage Service - Build your own Logging System - Build your own Metrics/Monitoring System - Build your own Feature Flag System - Build your own Payment Gateway Mock - Build your own Rate Limiter - Build your own Notification System - Build your own WebSocket Server - Build your own OAuth Server - Build your own CI/CD Pipeline System

Python Full Stack Developer Roadmap 2026 1. Internet Web Basics • How internet works • DNS • HTTP/HTTPS • Request/response cycle • Status codes • Cookies • Sessions • CORS • REST APIs • JSON 2. HTML • Semantic HTML • Forms • Tables • Inputs • Buttons • Links • Images • SEO basics • Accessibility basics 3. CSS • Selectors • Box model • Flexbox • Grid • Positioning • Responsive design • Media queries • CSS variables • Tailwind CSS • Shadcn/UI basics 4. JavaScript • Variables • Functions • Arrays • Objects • DOM manipulation • Events • Promises • Async/await • Fetch API • ES6 modules • Error handling • Local storage 5. TypeScript • Basic types • Interfaces • Type aliases • Generics basics • Props typing • API response typing • Form typing 6. React • Components • Props • State • Hooks • useEffect • Forms • Controlled components • React Router • API calls • Error/loading states • Context API • Zustand or Redux Toolkit • React Query / TanStack Query • Component libraries • Authentication flow 7. Next.js • App Router • Pages and layouts • Server components basics • Client components • API integration • Dynamic routes • Middleware basics • Auth flow • Deployment on Vercel 8. Core Python • Variables • Data types • Loops • Functions • Lists • Tuples • Sets • Dictionaries • File handling • Exception handling • Modules • Packages • Virtual environments • OOP • Decorators • Generators • Context managers • Type hints 9. Backend Framework • Django • Django REST Framework • FastAPI • Flask basics 10. Django • Project structure • Apps • Models • Views • Templates • URLs • Forms • Admin panel • Static files • Media files • Authentication • Authorization • Middleware • Signals • Class-based views • Django settings • Environment variables • Deployment settings 11. Django REST Framework • Serializers • Model serializers • API views • ViewSets • Routers • Permissions • Authentication • JWT auth • Pagination • Filtering • Searching • Ordering • Throttling • API versioning • Error handling 12. FastAPI • Routes • Path/query params • Pydantic models • Dependency injection • Auth • JWT • Middleware • Background tasks • Async endpoints • OpenAPI docs • SQLAlchemy integration • Testing APIs 13. Databases • SQL basics • PostgreSQL • MySQL basics • SQLite • Joins • Aggregations • Indexes • Transactions • Constraints • Normalization • Migrations • Query optimization basics 14. ORMs • Django ORM • SQLAlchemy • Alembic migrations • Query filtering • Relationships • Transactions • N 1 query problem • Eager loading 15. Authentication Security • Password hashing • Sessions • JWT • OAuth basics • Role-based access control • CSRF • XSS • SQL injection • CORS • Rate limiting • Secure cookies • Environment secrets 16. Testing • pytest • Django tests • DRF API tests • FastAPI tests • Unit tests • Integration tests • Mocking • Test database • Coverage • Postman/Bruno API testing 17. Background Jobs • Celery • Redis • RabbitMQ basics • Scheduled tasks • Email sending • File processing • Web scraping jobs • Async task status 18. DevOps Basics • Git • GitHub • Linux commands • Docker • Docker Compose • Nginx • Gunicorn • Uvicorn • CI/CD with GitHub Actions • Environment variables • Logs • Monitoring basics 19. Cloud Deployment • AWS EC2 • AWS S3 • AWS RDS • IAM basics • CloudWatch basics • Vercel for frontend • Render/Fly/Railway for simple deployment • Nginx reverse proxy • Domain setup • HTTPS/SSL 20. Full Stack Integration • Connect React frontend to Django/FastAPI backend • Login/register flow • Protected routes • Refresh tokens • File uploads • Form validation • Error handling • Loading states • Pagination • Search/filter/sort • Admin dashboard • Payment integration basics • Email notifications • WebSockets basics

The Best Open Source Repos to Start Contributing Today A. Python 1. github/fastapi/fastapi 2. github/pandas-dev/pandas 3. github/scikit-learn/scikit-learn 4. github/matplotlib/matplotlib 5. github/scrapy/scrapy 6. github/pytest-dev/pytest 7. github/cookiecutter/cookiecutter 8. github/zulip/zulip B. Java 1. github/JabRef/jabref 2. github/trinodb/trino 3. github/open-metadata/OpenMetadata 4. github/questdb/questdb 5. github/elastic/elasticsearch 6. github/TEAMMATES/teammates 7. github/commons-app/apps-android-commons 8. github/zaproxy/zaproxy C. JavaScript / TypeScript 1. github/freeCodeCamp/freeCodeCamp 2. github/storybookjs/storybook 3. github/vitejs/vite 4. github/vitest-dev/vitest 5. github/microsoft/TypeScript 6. github/microsoft/vscode 7. github/eslint/eslint 8. github/fastify/fastify 9. github/hoppscotch/hoppscotch 10. github/appsmithorg/appsmith D. Go 1. github/kubernetes/kubernetes 2. github/helm/helm 3. github/docker/cli 4. github/containerd/containerd 5. github/moby/moby 6. github/gohugoio/hugo 7. github/mattermost/mattermost 8. github/pingcap/tidb 9. github/hashicorp/terraform 10. github/SigNoz/signoz E. Rust 1. github/rust-lang/rust-clippy 2. github/rust-lang/rustfmt 3. github/nushell/nushell 4. github/hyperium/hyper 5. github/servo/servo 6. github/tikv/tikv 7. github/GyulyVGC/sniffnet 8. github/tensorzero/tensorzero F. Cloud / DevOps / Infrastructure 1. github/kubernetes/kubernetes 2. github/helm/helm 3. github/argoproj/argo-cd 4. github/prometheus/prometheus 5. github/grafana/grafana 6. github/open-telemetry/opentelemetry-collector 7. github/hashicorp/terraform 8. github/crossplane/crossplane 9. github/backstage/backstage 10. github/meshery/meshery G. AI / ML / Data 1. github/pytorch/pytorch 2. github/scikit-learn/scikit-learn 3. github/pandas-dev/pandas 4. github/jupyter/notebook 5. github/ray-project/ray 6. github/mlflow/mlflow 7. github/apache/airflow 8. github/apache/superset 9. github/bokeh/bokeh 10. github/pymc-devs/pymc H. Backend / API / Databases 1. github/fastapi/fastapi 2. github/fastify/fastify 3. github/supabase/supabase 4. github/appwrite/appwrite 5. github/hasura/graphql-engine 6. github/PostgREST/postgrest 7. github/trinodb/trino 8. github/questdb/questdb 9. github/pingcap/tidb 10. github/open-metadata/OpenMetadata I. Frontend / UI 1. github/storybookjs/storybook 2. github/vitejs/vite 3. github/vuejs/core 4. github/mui/material-ui 5. github/gatsbyjs/gatsby 6. github/electron/electron 7. github/Leaflet/Leaflet 8. github/webdriverio/webdriverio

Okay youtube is bringing back DMs within its app. Now brainrot's gonna multiply.

Is it just me, or do you all also like Lotus Biscoff?

Incorrect analogy. Farming is not a high impact profession. I’d still stay in tech because the distribution, need and people are all here. In the age of internet, you want to go away from internet? Wtf?

Imagine this setup Late night AC chilled room Headphones No one in the house to disturb Weekends No one from work to bother you Doordash with your food on the way Your favorite series just released = I'd pay for this

I have entrepreneurial ventures down the line that I'll work on. I'll compensate my engineers irrespective of gender, race, etc. for what they deserve, not what their "market value" is. Our employees are as important as the customers because they make the company possible.

Getting started with Python? 1. Learn variables 2. Learn data types 3. Learn strings 4. Learn lists 5. Learn tuples 6. Learn dictionaries 7. Learn sets 8. Learn conditionals 9. Learn loops 10. Learn functions 11. Learn modules 12. Learn file handling 13. Learn error handling 14. Learn list comprehensions 15. Learn object-oriented programming 16. Learn virtual environments 17. Learn pip 18. Learn working with APIs 19. Learn basic automation 20. Learn building small projects

As a Machine Learning Engineer, slap yourself if you cannot clearly explain at least 10 of the following: Bias-variance tradeoff Overfitting vs underfitting Train/validation/test split strategy Cross-validation pitfalls Data leakage Feature scaling and normalization One-hot encoding vs ordinal encoding Target encoding leakage Missing value imputation strategies Outlier handling Class imbalance techniques Precision vs recall vs F1-score ROC-AUC vs PR-AUC Confusion matrix interpretation Calibration of probabilities Logistic regression internals Linear regression assumptions Ridge vs Lasso regularization ElasticNet trade-offs Gradient descent vs stochastic gradient descent Learning rate scheduling Batch size effects Loss functions: MSE, MAE, cross-entropy Convex vs non-convex optimization Vanishing and exploding gradients Backpropagation internals Activation functions: ReLU, GELU, sigmoid, tanh Batch normalization vs layer normalization Dropout regularization Weight initialization strategies CNNs and convolution internals RNNs, LSTMs, and GRUs Attention mechanism Transformers architecture Positional encoding Self-attention vs cross-attention Embedding spaces Tokenization: BPE, WordPiece, SentencePiece Fine-tuning vs feature extraction Transfer learning Prompt engineering basics LoRA and parameter-efficient fine-tuning RLHF basics Retrieval-Augmented Generation Vector databases and similarity search Cosine similarity vs dot product ANN search: HNSW, IVF, PQ Hallucination causes in LLMs Model quantization Knowledge distillation Pruning neural networks Hyperparameter tuning Grid search vs random search vs Bayesian optimization Early stopping Ensemble methods Bagging vs boosting Random Forest internals XGBoost / LightGBM / CatBoost trade-offs SHAP and feature importance Permutation importance Model interpretability vs explainability PCA and dimensionality reduction t-SNE vs UMAP K-means clustering DBSCAN clustering Anomaly detection Recommendation systems: collaborative vs content-based filtering Matrix factorization Cold-start problem Time-series forecasting basics ARIMA vs Prophet vs deep learning models Stationarity in time series Data drift vs concept drift Model monitoring Model retraining strategies A/B testing ML models Offline metrics vs online metrics MLOps pipelines Feature stores Model registries Experiment tracking MLflow basics Dockerizing ML models Batch inference vs real-time inference Shadow deployment Canary deployment for ML models Model latency optimization GPU vs CPU inference Distributed training basics Data parallelism vs model parallelism Reproducibility with random seeds Ethical ML and fairness metrics Adversarial examples Privacy-preserving ML Federated learning basics And if you only know 10, kindly return the “Senior Machine Learning Engineer” title. 😄

10 system design concepts your interviews are secretly based on. (7th one is asked everywhere.) 1. Scalability: QPS, throughput, latency, storage 2. Load balancing: diverting traffic based on load 3. Database design: SQL vs NoSQL, schemas, indexes 4. Caching: Redis, cache invalidation, cache-aside, ttl 5. Sharding: partitioning data across machines 6. Replication: leader/follower, failover, read replicas 7. Rate limiting: token bucket, sliding window etc. 8. Message queues: Kafka, RabbitMQ, async 9. Consistency tradeoffs: CAP, eventual consistency 10. Reliability patterns: retries, idempotency, backpressure, circuit breakers

Everyone on X should read this case study on @elonmusk.

Copying someone’s post is one thing. Copying someone’s comment is another tier of slopers.

Minimum requirement to get a job.