Channels
- Hussein Nasser — databases & backend systems (YouTube)
- Jordan has no life — engineering & dev workflow (YouTube)
System design books
- Designing Data‑Intensive Applications — Martin Kleppmann
- Acing the System Design Interview — Alex Xu
- Educative.io System Design Courses — https://www.educative.io
Pair watch/read sessions with short notes and diagrams you can revisit before interviews.
Weekly Engineering Articles - Curated Learning Resources
React & Frontend Development
React Suspense and Data Fetching
Link: https://blog.logrocket.com/react-suspense-data-fetching/ React Suspense enables components to pause rendering while waiting for asynchronous data, providing a declarative way to handle loading states. It supports the render-as-you-fetch pattern, which begins rendering immediately after a network request is triggered, eliminating manual state management for async operations. With React 19 updates, Suspense now offers native support for data fetching, improved error handling, and better integration with server components. The article covers practical implementation including integration with React Query, lazy loading with React.lazy(), and error boundary patterns for robust error handling.React Higher-Order Components (HOC)
Link: https://blog.logrocket.com/react-higher-order-components/ Higher-Order Components are functions that take a component and return an enhanced version with additional functionality, enabling code reuse for cross-cutting concerns like authentication and data fetching. While Hooks have largely replaced HOCs for logic reuse, HOCs remain valuable for complex component transformations and working with legacy codebases. The article demonstrates practical patterns including prop sharing, state management with Hooks inside HOCs, and performance optimization using memoization. It also covers HOC composition, TypeScript type safety, and debugging strategies for production applications.React State Management in 2025
Link: https://www.developerway.com/posts/react-state-management-2025 Modern React applications don’t need traditional state management libraries for most use cases—breaking state into specific concerns reveals better specialized solutions. Remote data should be handled by data-fetching libraries like TanStack Query or SWR, which solve caching, deduplication, and invalidation automatically. URL query parameters can be managed with nuqs library, eliminating manual syncing pain, while local component state works perfectly with useState and useReducer. Only when sharing complex state between loosely-related components do external libraries like Zustand become necessary, chosen for their simplicity and alignment with React’s declarative patterns.React Performance and Extra Layers
Link: https://dev.to/im-shafiqurehman/how-react-achieves-high-performance-even-with-extra-layers-339j React maintains high performance despite its virtual DOM abstraction layer through intelligent reconciliation and batching mechanisms. The virtual DOM acts as a lightweight representation, allowing React to compute minimal DOM changes before applying them to the actual browser DOM. React’s fiber architecture enables concurrent rendering, allowing the framework to pause, resume, and prioritize updates for optimal user experience. Understanding these internal mechanisms helps developers write more performant components by leveraging React’s optimization strategies effectively.React Rendering Behavior Guide
Link: https://blog.isquaredsoftware.com/2020/05/blogged-answers-a-mostly-complete-guide-to-react-rendering-behavior/ React’s rendering process involves queuing renders, reconciliation, and committing changes to the DOM in a carefully orchestrated sequence. The article explains when and why components re-render, covering parent-child render relationships and how state changes propagate through the component tree. It details optimization techniques including React.memo, useMemo, useCallback, and component structure patterns that minimize unnecessary renders. Understanding render behavior is crucial for building performant React applications, especially as component trees grow in complexity.React Design System Guide
Link: https://www.designsystemscollective.com/react-design-system-comprehensive-guide-1e224d2c23ff A comprehensive React design system provides consistency, reusability, and scalability across an application by establishing standardized components and patterns. The guide covers setting up a component library with proper documentation, theming systems, and accessibility considerations baked into every element. It explores tools like Storybook for component development and testing, TypeScript for type safety, and strategies for versioning and distributing your design system. Building a design system upfront saves development time long-term by reducing duplication and ensuring visual and functional consistency.The Tao of React - Best Practices
Link: https://alexkondov.com/tao-of-react/ This comprehensive guide presents proven principles for building maintainable React applications, covering components, state management, testing, and architecture patterns. Key recommendations include favoring functional components, organizing code by modules rather than technical layers, and using data-fetching libraries instead of manual state management. The article advocates for keeping components focused with single responsibilities, extracting helper functions, using reducers for complex state, and preferring hooks over HOCs. It emphasizes writing testable code, avoiding premature optimization, and structuring applications to support growth without requiring architectural rewrites.One Roundtrip Per Navigation (by Dan Abramov)
Link: https://overreacted.io/one-roundtrip-per-navigation/ Modern web applications should aim to load each page with a single network roundtrip, avoiding the common pattern of loading JavaScript before fetching data. This approach improves perceived performance by starting data requests simultaneously with page load rather than sequentially after JavaScript execution. React Server Components and frameworks like Next.js enable this pattern by allowing data fetching on the server before hydration. The article explains waterfall problems in client-side rendering and how streaming server rendering can progressively deliver content as it becomes available.JavaScript Fundamentals
JavaScript Execution Context
Link: https://dev.to/im-shafiqurehman/javascript-execution-context-made-simple-5gk0 JavaScript execution context is the environment where code is evaluated and executed, consisting of the Global Execution Context and Function Execution Contexts. Each context has two phases: the creation phase (memory allocation, hoisting) and the execution phase (code execution line by line). The call stack manages execution contexts in LIFO order, and understanding this mechanism clarifies hoisting, scope, closures, and the ‘this’ keyword behavior. Mastering execution contexts is fundamental to debugging JavaScript and writing predictable, maintainable code.System Design & Architecture
MERN Stack Survey Data
Link: https://www.linkedin.com/posts/supabase_we-surveyed-over-2000-startup-founders-activity-7374464790049624066-ydzZ Survey data from over 2000 startup founders reveals real-world technology stack choices and trends in the startup ecosystem. The data shows how MERN (MongoDB, Express, React, Node.js) compares to other popular tech stacks in terms of adoption, scalability concerns, and founder satisfaction. Understanding these patterns helps developers make informed decisions about technology choices based on actual usage data rather than hype. The survey insights reveal which combinations work well for different types of applications and company stages.Monoliths and Microservices
Link: https://medium.com/@SkyscannerEng/monoliths-and-microservices-8c65708c3dbf The choice between monolithic and microservices architecture depends on team size, organizational complexity, and deployment requirements rather than being universally better. Monoliths offer simpler development, testing, and deployment for small teams, with all code in one place enabling easier refactoring and debugging. Microservices excel when you need independent scaling, team autonomy, and polyglot technology choices but introduce complexity in distributed systems, data consistency, and debugging. Most companies should start with a well-structured monolith and extract microservices only when specific scaling or organizational needs justify the operational overhead.NoSQL Databases: Survey and Decision Guidance
Link: https://medium.baqend.com/nosql-databases-a-survey-and-decision-guidance-ea7823a822d NoSQL databases offer diverse data models (document, key-value, column-family, graph) optimized for specific use cases beyond relational databases. The survey covers major NoSQL systems like MongoDB, Cassandra, Redis, and Neo4j, comparing performance characteristics, consistency models, and scalability patterns. Decision guidance includes when to choose NoSQL over SQL, which type fits your data access patterns, and how to evaluate trade-offs in the CAP theorem. Understanding these options prevents costly architecture mistakes and ensures your database choice aligns with application requirements.How Sharding Works
Link: https://medium.com/@jeeyoungk/how-sharding-works-b4dec46b3f6 Database sharding distributes data across multiple machines by partitioning based on a shard key, enabling horizontal scaling beyond single-server limits. The article explains sharding strategies including range-based, hash-based, and geographic sharding, along with their trade-offs in data distribution and query complexity. Key challenges include maintaining data consistency across shards, handling transactions that span multiple shards, and rebalancing as data grows unevenly. Proper shard key selection is critical—choose based on query patterns to minimize cross-shard queries while ensuring even data distribution.Load Balancing Fundamentals
Link: https://youtu.be/K0Ta65OqQkY Load balancing distributes incoming network traffic across multiple servers to ensure no single server becomes overwhelmed, improving availability and reliability. Common algorithms include round-robin, least connections, IP hash, and weighted distribution, each suited for different traffic patterns and server capabilities. Layer 4 (transport layer) load balancers operate at the TCP/UDP level while Layer 7 (application layer) balancers can make decisions based on HTTP content. Modern load balancers provide health checking, SSL termination, session persistence, and DDoS protection as core features.Consistent Hashing Explained
Link: https://blog.algomaster.io/p/consistent-hashing-explained Consistent hashing solves the problem of efficiently distributing data across changing numbers of servers while minimizing data movement during scaling. Traditional hashing requires remapping most keys when adding/removing servers, but consistent hashing only affects keys adjacent to the changed server. Virtual nodes improve load distribution by mapping each physical server to multiple points on the hash ring, preventing hotspots. This technique powers distributed caches like Memcached, databases like DynamoDB, and CDNs, making it essential knowledge for building scalable distributed systems.Scaling Uber - Brief History
Link: https://highscalability.com/brief-history-of-scaling-uber/ Uber’s evolution from a monolithic Python application to a distributed microservices architecture demonstrates real-world scaling challenges and solutions. Early growth focused on geographic expansion using city-based database sharding, while later stages addressed technical debt and service reliability. The company adopted microservices to enable team autonomy, built sophisticated routing and matching systems for real-time operations, and developed custom infrastructure for handling millions of concurrent rides. Key lessons include the importance of monitoring, gradual migration strategies, and balancing speed of iteration with architectural sustainability.Server-Side vs Client-Side Rendering Benefits
Link: https://medium.com/walmartglobaltech/the-benefits-of-server-side-rendering-over-client-side-rendering-5d07ff2cefe8 Server-Side Rendering (SSR) delivers fully rendered HTML from the server, improving initial page load speed, SEO, and perceived performance compared to client-side rendering. SSR enables search engines to crawl content immediately without executing JavaScript and provides faster First Contentful Paint for users on slow connections or devices. Trade-offs include increased server load, more complex deployment, and potential Time to Interactive delays as JavaScript hydrates the page. Modern frameworks like Next.js enable hybrid approaches, allowing developers to choose rendering strategies per route based on content type and performance requirements.Avoid Over-Engineering
Link: https://github.com/binhnguyennus/awesome-scalability (Principles section) Over-engineering introduces unnecessary complexity by solving problems you don’t have yet, wasting time and making codebases harder to maintain. Start with the simplest solution that meets current requirements, then refactor when actual needs emerge with better understanding of the problem. Premature abstraction and optimization often guess wrong about future needs, creating inflexible code that must be rewritten anyway. The rule: solve today’s problems today, but structure code for easy modification when tomorrow’s problems reveal themselves.Backend & Infrastructure
Ideal Node.js Project Structure
Link: https://softwareontheroad.com/ideal-nodejs-project-structure A well-organized Node.js project separates concerns into layers: routes handle HTTP, controllers process requests, services contain business logic, and data access objects manage database operations. The 3-layer architecture (Controller → Service → Data Access) keeps code maintainable by preventing business logic from leaking into routes or database code. Additional recommendations include separating configuration from code, using dependency injection for testability, and organizing files by feature rather than technical role. This structure scales from small APIs to enterprise applications by maintaining clear boundaries and responsibilities.CQRS Pattern with Job Queues
Link: https://softwareontheroad.com/job-queues-cqrs-nodejs-mongodb-agenda/ Command Query Responsibility Segregation (CQRS) separates read and write operations into different models, optimizing each for its specific purpose. Integrating job queues with CQRS enables asynchronous command processing, improving response times and system resilience by decoupling request handling from execution. The article demonstrates implementation using MongoDB and Agenda for job scheduling, showing how commands become queued jobs processed in the background. This pattern excels in systems with high write loads, complex business logic, or differing performance requirements between reads and writes.Long Polling vs SSE vs WebSockets
Link: https://medium.com/@asharsaleem4/long-polling-vs-server-sent-events-vs-websockets-a-comprehensive-guide-fb27c8e610d0 Real-time communication requires choosing between long polling (HTTP requests held open), Server-Sent Events (SSE, server-to-client streaming), and WebSockets (bidirectional communication). Long polling works everywhere but creates high server overhead and latency; SSE provides efficient unidirectional updates over HTTP with automatic reconnection. WebSockets enable full-duplex communication with minimal overhead, ideal for chat and gaming, but require special infrastructure and don’t work through all proxies. Choose based on directionality needs, browser support requirements, and existing infrastructure—SSE for simple server updates, WebSockets for interactive applications.Load Balancer Use Cases
Link: https://www.geeksforgeeks.org/system-design/load-balancer-use-cases/ Load balancers solve multiple problems beyond traffic distribution: horizontal scaling, zero-downtime deployments, geographic traffic routing, and DDoS mitigation. They enable A/B testing by routing percentage of traffic to experimental servers, implement rate limiting to protect backends, and provide SSL offloading to reduce compute burden on application servers. Use cases span web applications, API gateways, database read replicas, and microservices meshes where sophisticated routing rules direct requests based on headers, cookies, or content. Understanding these patterns helps design resilient, scalable architectures.Development Environments & DevOps
Dev, QA, Staging, and Production Environments
Link: https://northflank.com/blog/what-are-dev-qa-preview-test-staging-and-production-environments Modern development workflows use multiple environment tiers, each serving specific purposes in the software delivery pipeline. Development environments are for active coding, QA/test environments enable quality assurance with production-like data, staging mirrors production exactly for final validation, and production serves real users. Additional specialized environments include preview (per-feature branches), demo (for sales), and hotfix (emergency patches). Proper environment management with infrastructure-as-code ensures consistency, enables confident deployments, and allows testing without risking production data or availability.APIs & Protocols
REST API Design Principles
Link: https://restfulapi.net REST (Representational State Transfer) defines architectural constraints for building web services using standard HTTP methods (GET, POST, PUT, DELETE, PATCH). RESTful APIs organize resources using URL paths, use appropriate status codes to communicate results, and maintain statelessness so each request contains all necessary information. Best practices include versioning APIs, using nouns for resources not verbs, implementing proper authentication, and providing clear error messages. Well-designed REST APIs are predictable, cacheable, and easy to consume, forming the backbone of modern web and mobile applications.JWT (JSON Web Token) Authentication
Link: https://newsletter.systemdesign.one/p/how-jwt-worksLink: https://www.jwt.io/introduction JWT provides stateless authentication by encoding user information and authorization claims in a cryptographically signed token. The token has three parts: header (algorithm), payload (claims like user ID and expiration), and signature (verifies authenticity). Clients store the JWT (typically in memory or HTTP-only cookies) and include it in request headers; servers validate signatures without database lookups. Benefits include scalability through stateless servers and ease of use in microservices, but considerations include token revocation challenges and security risks if not implemented properly (use HTTPS, short expiration, and secure storage).
Architecture Principles
Scalability Best Practices
Link: https://github.com/binhnguyennus/awesome-scalability Comprehensive collection of resources covering distributed systems, CAP theorem, consistency patterns, and real-world architecture case studies. Topics include database replication strategies, caching layers, message queues, and microservices communication patterns. The repository provides battle-tested principles like designing for failure, implementing circuit breakers, and using backpressure mechanisms. Essential reading for understanding how large-scale systems like Twitter, Netflix, and Amazon handle millions of requests while maintaining reliability and performance.Fast and Resilient Web Apps (Google I/O)
Link: (Google I/O 2016 presentation) Modern web applications must balance performance with resilience using progressive enhancement, service workers, and intelligent caching strategies. Progressive Web Apps provide app-like experiences with offline capability, push notifications, and fast loading through aggressive caching. Techniques include critical rendering path optimization, lazy loading, code splitting, and using service workers as network proxies for offline-first functionality. The presentation demonstrates measuring performance with Lighthouse, implementing skeleton screens for perceived speed, and handling various network conditions gracefully.Dependency Injection
Dependency Injection Explained
Link: https://www.youtube.com/watch?v=J1f5b4vcxCQ Dependency Injection is a design pattern where objects receive their dependencies from external sources rather than creating them internally, improving testability and flexibility. Instead of a class instantiating its dependencies, they’re “injected” through constructor parameters, setters, or interface implementation. This inversion of control makes code more modular, easier to test with mock dependencies, and allows changing implementations without modifying dependent code. The video covers different DI patterns, container usage, and practical examples showing how DI reduces coupling and improves code maintainability.Database Concurrency & Transactions
Concurrency Control Fundamentals
Link: https://en.wikipedia.org/wiki/Concurrency_control Concurrency control ensures that multiple transactions executing simultaneously produce correct results while maintaining data integrity and maximizing performance. The main approaches include pessimistic (locking data until operations complete), optimistic (validating at commit time), and semi-optimistic methods, each balancing throughput against consistency guarantees. Database systems typically achieve correctness through serializability, ensuring concurrent transaction execution produces results equivalent to some serial execution order. Common techniques include two-phase locking, timestamp ordering, and multiversion concurrency control (MVCC), with tradeoffs between consistency, performance, and deadlock risks requiring careful design choices based on application needs.Preventing SQL Read-Modify-Write Race Conditions
Link: https://on-systems.tech/blog/128-preventing-read-committed-sql-concurrency-errors/ Read-modify-write cycles are a common SQL anti-pattern where transactions read data, perform computations in application code, then write results, creating race conditions with concurrent transactions. Even within transactions, the default READ COMMITTED isolation level doesn’t prevent logical race conditions where two processes can overwrite each other’s changes. The solution is SELECT FOR UPDATE, which locks rows returned by a query to ensure only one transaction can modify them at a time, preventing lost updates. While this introduces performance overhead as concurrent requests queue sequentially, correctness should be prioritized over performance until proven bottlenecks emerge, and alternative strategies explored only when necessary.PostgreSQL Anti-Patterns: Read-Modify-Write Cycles
Link: https://www.enterprisedb.com/blog/postgresql-anti-patterns-read-modify-write-cycles The naïve read-modify-write pattern appears to work during development but critically fails under concurrent access, causing data corruption when two sessions simultaneously update the same record. Solutions include avoiding the cycle entirely by performing calculations directly in SQL (e.g., UPDATE accounts SET balance = balance - 100), using SELECT FOR UPDATE to explicitly lock rows during transactions, or employing SERIALIZABLE isolation level. PostgreSQL’s default READ COMMITTED isolation automatically handles some conflicts by making later SELECTs wait for earlier UPDATEs to complete, but explicit locking provides stronger guarantees. The best approach is often eliminating the read-modify-write cycle through SQL-based updates, reserving locking strategies for complex business logic requiring application-side processing.SOLID Design Principles
Link: https://www.freecodecamp.org/news/solid-design-principles-in-software-development SOLID represents five object-oriented design principles that create maintainable, scalable, and flexible code: Single Responsibility (each class has one reason to change), Open/Closed (open for extension, closed for modification), Liskov Substitution (derived classes must be substitutable for base classes), Interface Segregation (clients shouldn’t depend on interfaces they don’t use), and Dependency Inversion (depend on abstractions, not concretions). These principles reduce coupling, improve testability, and make code easier to refactor and extend over time. While originally for OOP, many SOLID concepts apply to functional programming and component design in modern frameworks. Understanding SOLID helps developers write code that handles changing requirements gracefully without requiring extensive rewrites.React Advanced Patterns & Performance
React useEffect Cleanup Function
Link: https://blog.logrocket.com/understanding-react-useeffect-cleanup-function/ The useEffect cleanup function prevents memory leaks by canceling subscriptions, aborting fetch requests, and clearing timers before components unmount or dependencies change. React calls the cleanup function before running the effect on re-renders with changed dependencies and once on unmount, ensuring stale effects don’t persist. Common use cases include aborting API requests with AbortController, unsubscribing from WebSocket connections, and clearing setTimeout/setInterval timers to avoid updating unmounted components. While React 18 removed the “can’t perform state update on unmounted component” warning (as it was often misleading), proper cleanup remains essential for preventing actual memory leaks from long-lived subscriptions, improving application performance and avoiding unexpected behavior.React Advanced Patterns & Performance
React useEffect Cleanup Function
Link: https://blog.logrocket.com/understanding-react-useeffect-cleanup-function/ The useEffect cleanup function prevents memory leaks by canceling subscriptions, aborting fetch requests, and clearing timers before components unmount or dependencies change. React calls the cleanup function before running the effect on re-renders with changed dependencies and once on unmount, ensuring stale effects don’t persist. Common use cases include aborting API requests with AbortController, unsubscribing from WebSocket connections, and clearing setTimeout/setInterval timers to avoid updating unmounted components. While React 18 removed the “can’t perform state update on unmounted component” warning (as it was often misleading), proper cleanup remains essential for preventing actual memory leaks from long-lived subscriptions, improving application performance and avoiding unexpected behavior.JavaScript Performance & Multi-Threading
Handling CPU-Bound Tasks with Web Workers
Link: https://www.digitalocean.com/community/tutorials/how-to-handle-cpu-bound-tasks-with-web-workers JavaScript executes on a single thread, causing CPU-intensive tasks like image processing or complex calculations to block the main thread and freeze the UI. The Web Workers API solves this by enabling multithreading in browsers, allowing you to offload heavy computations to separate threads that run on different CPU cores. Web Workers communicate with the main thread through message passing using postMessage and onmessage, keeping the UI responsive during expensive operations. Unlike promises which don’t prevent blocking for CPU-bound tasks, Web Workers provide true parallelism for computationally intensive work while I/O-bound tasks like fetch remain suitable for promise-based async handling.Using Web Workers with React and TypeScript
Link: https://blog.logrocket.com/web-workers-react-typescript/ Integrating Web Workers into React applications enables offloading computationally expensive operations without blocking the React rendering cycle or user interactions. The implementation involves creating a separate worker file, instantiating it in your React component, and establishing two-way communication using postMessage for sending data and onmessage for receiving results. TypeScript adds type safety to worker communication, preventing runtime errors from incorrect message formats between the main thread and worker threads. Best practices include terminating workers when components unmount (using cleanup in useEffect), handling errors gracefully, and avoiding creating excessive workers since each consumes memory and CPU resources.Understanding JavaScript Event Loop and Web Workers
Link: https://www.youtube.com/watch?v=8aGhZQkoFbQ The JavaScript event loop manages asynchronous operations by continuously checking the call stack and callback queue, executing code in a non-blocking manner despite being single-threaded. Web Workers extend JavaScript’s capabilities by enabling true parallel execution on multi-core systems, bypassing event loop limitations for CPU-intensive tasks. Workers have their own event loop, global context, and cannot access the DOM, making them ideal for background computations like data processing or encryption. Understanding the relationship between the event loop (handling async I/O) and Web Workers (enabling CPU parallelism) is crucial for building performant web applications that remain responsive under heavy computational load.Node.js Worker Threads for Multi-Threading
Link: https://www.youtube.com/watch?v=Gcp7triXFjg Node.js introduced the worker_threads module to handle CPU-intensive tasks without blocking the event loop, bringing true multithreading to server-side JavaScript. Each worker thread runs on its own V8 instance and event loop, communicating through message passing rather than shared memory to avoid deadlocks and race conditions. Worker pools allow reusing threads efficiently rather than spawning new ones per request, critical for production systems handling concurrent CPU-bound workloads. The optimal number of workers typically equals available CPU cores minus one, and they’re most beneficial for tasks like encryption, image processing, or complex calculations, while I/O operations should still use Node’s built-in async APIs.Web Workers API Documentation (MDN)
Link: https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers The Web Workers API enables running scripts in background threads separate from the main execution thread, preventing UI blocking during intensive operations. Workers can perform tasks like data processing, network requests, or complex calculations while the main thread handles user interactions and rendering. Different worker types serve specific purposes: Dedicated Workers are owned by a single script, Shared Workers can be accessed by multiple scripts across windows/tabs, and Service Workers act as proxy servers enabling offline capabilities. Workers communicate via structured cloning (not direct object references), support importScripts for loading libraries, and have access to most JavaScript features except DOM manipulation and certain window properties.Web Workers API Documentation (MDN)
Link: https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers The Web Workers API enables running scripts in background threads separate from the main execution thread, preventing UI blocking during intensive operations. Workers can perform tasks like data processing, network requests, or complex calculations while the main thread handles user interactions and rendering. Different worker types serve specific purposes: Dedicated Workers are owned by a single script, Shared Workers can be accessed by multiple scripts across windows/tabs, and Service Workers act as proxy servers enabling offline capabilities. Workers communicate via structured cloning (not direct object references), support importScripts for loading libraries, and have access to most JavaScript features except DOM manipulation and certain window properties.React Synthetic Events
Link: https://www.geeksforgeeks.org/reactjs/what-are-synthetic-events-in-reactjs React Synthetic Events are cross-browser wrappers around native browser events that provide a consistent API across all browsers, normalizing event behavior differences between Chrome, Firefox, Safari, and others. Synthetic events use camelCase naming (onClick instead of onclick) and improve performance through event pooling, where React reuses event objects across multiple events to reduce memory consumption. Common methods like preventDefault(), stopPropagation(), and accessing event.target work identically across browsers, eliminating the need for browser-specific code. React’s event delegation attaches a single event listener at the root level rather than individual DOM nodes, significantly improving performance especially for large component trees with many interactive elements.Optimizing React with Code Splitting and Lazy Loading
Link: https://medium.com/@ignatovich.dm/optimizing-react-apps-with-code-splitting-and-lazy-loading-e8c8791006e3 Code splitting breaks large JavaScript bundles into smaller chunks loaded on demand, dramatically reducing initial load times and improving Time to Interactive metrics. React.lazy() enables dynamic imports that create separate bundles automatically at build time, loading components only when needed rather than in the initial bundle. Suspense provides fallback UI (loading spinners, skeleton screens) while lazy components load, preventing blank screens and improving perceived performance. Route-based code splitting (splitting at page level) offers maximum initial bundle reduction, while component-based splitting provides granular control for large, conditionally-rendered components like modals, charts, or text editors that users may never access.Database Management & Design
Keys in DBMS (Primary, Foreign, Unique)
Link: https://webandcrafts.com/blog/keys-in-dbms Database keys are attributes used to uniquely identify records and establish relationships between tables, forming the foundation of data integrity in relational databases. Primary keys uniquely identify each row in a table with non-null, unique values, serving as the main identifier for all CRUD operations. Foreign keys create relationships between tables by referencing the primary key of another table, enforcing referential integrity and preventing orphaned records. Unique keys ensure column values remain distinct but allow one NULL value, useful for alternate identifiers like email addresses or phone numbers, while candidate keys are minimal sets of attributes that could serve as primary keys.Object-Relational Mapping (ORM)
Link: https://www.baeldung.com/cs/object-relational-mapping Object-Relational Mapping (ORM) is a programming technique that bridges object-oriented code with relational databases, automatically converting between objects and database tables without manual SQL writing. ORMs handle the object-relational impedance mismatch, resolving differences like inheritance (objects) versus flat tables (databases), one-to-many relationships, and complex object graphs. Benefits include reduced boilerplate code, database abstraction enabling easy switching between vendors, automatic schema migrations, and improved maintainability as model changes don’t require rewriting all data access code. However, ORMs have learning curves, can generate inefficient SQL for complex queries, and may introduce performance overhead, making direct SQL preferable for bulk operations or highly optimized queries requiring fine-grained control.AI/ML & Prompt Engineering
OpenAI API Crash Course for Beginners
Link: https://youtu.be/xP_ZON_P4Ks This comprehensive tutorial covers integrating OpenAI’s API into applications, explaining authentication, request formatting, response handling, and best practices for production use. Learn how to work with chat completions, configure parameters like temperature and max tokens for controlling output randomness and length, and handle streaming responses for real-time interactions. The course demonstrates practical implementations including chatbots, content generation, and automated summarization while covering error handling, rate limiting strategies, and cost optimization techniques. Essential for developers wanting to add AI capabilities to their applications using GPT models through programmatic access.OpenAI API Documentation
Link: https://platform.openai.com/docs/api-reference/chat/create Official documentation for OpenAI’s Chat Completions API, the primary interface for interacting with GPT models including GPT-4 and GPT-3.5. The API uses a messages array with system, user, and assistant roles to provide conversation context and guide model behavior. Key parameters include model selection, temperature (creativity vs consistency), max_tokens (response length), and top_p (nucleus sampling) for controlling output characteristics. Advanced features cover function calling for structured outputs, response formats including JSON mode, and fine-tuning options for domain-specific applications requiring specialized knowledge or behavior.Prompt Engineering for Developers (DeepLearning.AI)
Link: https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/ This short course teaches systematic prompt engineering techniques for building AI-powered applications, covering principles like writing clear instructions and giving models time to think. Learn iterative prompt development, expanding and summarizing text, inferring sentiment and topics, transforming text between formats, and building conversational chatbots. The course emphasizes practical patterns like few-shot learning with examples, chain-of-thought prompting for complex reasoning, and structuring outputs in specific formats. Essential for developers integrating LLMs into production applications, focusing on reliable, predictable AI behavior rather than one-off chat interactions.Generative AI for Beginners (Medium Series)
Link: https://medium.com/@raja.gupta20/generative-ai-for-beginners-part-4-introduction-to-generative-ai-bb70f0854128Link: https://medium.com/@raja.gupta20/c57f3a15436a Comprehensive beginner-friendly series explaining generative AI fundamentals including how models like GPT work, training processes, and the transformer architecture powering modern AI. Topics cover the difference between discriminative and generative models, how attention mechanisms enable contextual understanding, and fine-tuning techniques for specializing pre-trained models. The series explores practical applications across text generation, image synthesis, code completion, and conversational AI while addressing limitations like hallucinations, biases, and computational requirements. Ideal for developers, product managers, and technical leaders seeking foundational understanding before implementing AI solutions.