Frontend
CSS Flexbox Handbook
Flexbox layout model, alignment, spacing, responsive design patterns, and practical CSS Grid alternatives.
This repo is a compact shelf of HTML handbooks for engineering, AI tooling, coding standards, and platform concepts. Each one is meant to be skimmed fast when you need the right pattern, command, or mental model.
Flexbox layout model, alignment, spacing, responsive design patterns, and practical CSS Grid alternatives.
Utility-first CSS framework, configuration, plugin system, responsive design, and production optimization patterns.
Foundations, CRUD, joins, views, CTEs, window functions, indexes, and query-plan basics for application engineers.
LATERAL, recursive CTEs, advanced grouping, procedures, PL/pgSQL functions, and JSONB patterns for deeper PostgreSQL work.
Schemas, constraints, CRUD, joins, views, temp structures, flow control, and TRY/CATCH-oriented T-SQL fundamentals.
APPLY operators, ranking, recursive CTEs, PIVOT/UNPIVOT, stored procedures, iTVFs, and safe dynamic SQL in T-SQL.
Clean coding conventions, project structure, patterns, and maintainability guidance for .NET teams.
Core runtime, web APIs, dependency injection, middleware, and practical implementation guidance for modern .NET Core services.
Comprehensive guide to building scalable applications with Java and Spring Boot.
ML pipelines, reusable components, hyperparameter tuning, training operators, and model deployment patterns on Kubernetes with Kubeflow.
Attention mechanisms, encoder-decoder architectures, BERT-style encoders, modern transformer variants, and when to choose dense or Mixture-of-Experts models.
Core machine learning concepts, model selection, validation strategies, and practical workflows for applied ML.
Machine learning basics, model types, metrics, workflows, and decision-making foundations.
Neural network architectures, backpropagation, regularization, optimization, and deep learning best practices.
Neural network fundamentals, layer types, activation functions, loss functions, and practical network design patterns.
Experiment tracking, model registry, aliases, deployment, LLMOps, and production anti-patterns with MLflow 2.x.
DVC versioning, experiment tracking, FastAPI serving, Docker, monitoring, and production ML patterns.
Experiment tracking, sweeps, artifacts, dashboard workflows, and collaboration patterns for serious ML teams.
Decision framework for CI/CD, GitOps, Helm, Kubernetes, registry strategy, observability, and security across a multi-service platform.
CI/CD, deployment strategies, observability, and operational patterns for modular monolithic architectures.
High-signal CI/CD, Kubernetes, IaC, security, observability, and platform operations guide with a direct link to the full playbook.
Core platform, DevEx, CI/CD, SecOps, FinOps, and service ownership concepts explained from beginner through intermediate depth.
Daily Docker commands, production Dockerfiles, container debugging, Podman tradeoffs, and orchestration guidance.
Branching, pull request habits, merge safety, and team workflows for real repositories.
Workflow syntax, CI/CD pipeline patterns, reusable workflows, environments, and secure automation practices with GitHub Actions.
Core Kubernetes objects, deployments, services, config management, and operational patterns for containerized workloads.
Production-grade Docker and Kubernetes command reference for SRE and DevOps teams — lifecycle, debugging, cluster ops, rollouts, and housekeeping.
Reference guide for Terraform fundamentals, HCL, modules, state, workflows, and production-grade infrastructure patterns.
Compute, storage, networking, cost optimization, and security patterns for AWS with Terraform and Boto3.
Reference patterns for topology, elasticity, security boundaries, and multi-region resilience across AWS, Azure, and GCP.
Guardrails for ownership, tagging, elasticity, commitment planning, and spend reviews across AWS, Azure, and GCP.
Operational standards for RTO, RPO, failover, restoration, validation, and recovery drills across AWS, Azure, and GCP.
Account structure, identity hierarchy, network foundations, security guardrails, and governance operating model across AWS, Azure, and GCP.
Compute, cost, IaC, networking, and operational guidance for modern Azure delivery teams.
Compute, BigQuery, networking, IAM hierarchy, cost management, and security patterns for Google Cloud.
VPC design, routing, private connectivity, load balancing, DNS, segmentation, and troubleshooting patterns across cloud networks.
Reference notes for multi-agent design, orchestration, and production usage patterns.
Chains, prompts, tools, retrieval, and application patterns across LangChain workflows.
State graphs, memory, agents, execution flow, and production orchestration with LangGraph.
Lightweight agent patterns, execution flow, and implementation guidance with SmolAgents.
Build agents, orchestrate teams, multi-tool agents, workflow agents, routing, and custom agent patterns with Google ADK.
Message design, few-shot patterns, reasoning strategies, RAG prompts, and structured JSON output guidance.
Modes, models, hooks, agents, MCP integrations, and workflow guidance in one place.
Environments as code, Containers, Cloud ready, builds, and isolation guidance in one place.
Data prep, training strategy, evaluation, and operational considerations for tuning models.
QLoRA, SFTTrainer, PEFT, DPO, adapter workflows, and deployment patterns for modern open-weight LLM training.
Local LLM inference, quantization formats, model loading, sampling parameters, and performance tuning for CPU and GPU with llama.cpp.
Core model ideas, prompting fundamentals, architecture terminology, and reference concepts.
OpenAI vs Anthropic payloads, tool-calling formats, agnostic wrappers, and integration anti-patterns.
QLoRA, local GPU setup, Unsloth Studio, GGUF export, and practical fine-tuning guidance for 12–16 GB consumer hardware.
Developer-facing notes for Foundry concepts, workflows, and delivery patterns.
Production-focused MCP architecture, tools, resources, and deployment patterns for enterprise AI integration.
Practical guidance for workflows, prompts, chat, and enterprise usage patterns with GitHub Copilot.
threat hunting, alert triage, incident handling, and security posture management.
Never trust, always verify. Assume breach. Verify explicitly.
Never trust, always verify. Assume breach. Verify explicitly.
how attacks work, the mindset behind them, real-world cases.
HNSW & IVF-Flat Pinecone Milvus Qdrant pgvector Advanced RAG Hybrid Search
Dependency trust, provenance, signing, SBOM strategy, and controls for end-to-end software supply chain security.
Unified telemetry setup, instrumentation patterns, and practical observability standards using OpenTelemetry.
Trace context, span design, sampling strategy, and troubleshooting patterns for distributed systems.
Gremlin, LitmusChaos, fault injection design, blast-radius control, GameDay planning, and resilience validation patterns.
Safety policies, prompt-injection defenses, output validation, moderation, and runtime guardrail patterns for AI systems.
Evaluation harnesses, golden datasets, automated test loops, and regression checks for LLM applications.
Offline evals, benchmark design, human review loops, and production testing strategies for LLM systems.
Routing, auth, rate limiting, aggregation, and governance patterns for API gateways and edge services.
Core architecture principles, system boundaries, tradeoffs, and design building blocks for engineering teams.
Core data structures, algorithms, complexity analysis, and practical problem-solving patterns for engineers.
Foundations, terminology, delivery models, and enterprise engineering context for newer builders.
Events, consumers, delivery semantics, outbox patterns, and operational tradeoffs in event-driven systems.
Schema design, resolver patterns, federation tradeoffs, authorization, and operational guidance for GraphQL at scale.
Service contracts, streaming, protobuf evolution, and production integration patterns with gRPC.
High-level design framing, component boundaries, system context, and tradeoff documentation for scalable systems.
Low-level design patterns, class and module boundaries, state handling, and implementation detail guidance.
Domain boundaries, module contracts, deployment tradeoffs, and evolution patterns for modular monoliths.
Pattern comparison, tradeoffs, and selection criteria for architecture leaders and technical decision-makers.
Enterprise architecture method, artifacts, governance, and capability mapping using TOGAF.
Pipelines, ingestion, transformations, data quality, and Python-based workflows for data engineering foundations.
Warehouse-first loading, transformation strategy, tooling choices, and operational tradeoffs for ELT systems.
Extraction, transformation, loading workflows, orchestration, and reliability patterns for ETL pipelines.
DataFrames, joins, grouping, reshaping, and practical analysis workflows with Pandas.
Local cluster setup, inner-loop workflows, manifests, and infrastructure-as-code patterns with Minikube.
Modern Angular features, components, signals, routing, forms, and application structure.
Core Angular concepts, standalone APIs, RxJS basics, and practical application patterns for growing teams.
Predictable state management, slices, selectors, async flows, and React integration patterns with Redux.
Retrieval design, chunking, memory, context windows, and advanced RAG patterns for production AI applications.
Tensors, autograd, modules, training loops, and practical deep learning workflows with PyTorch.
Classical ML workflows, preprocessing, pipelines, model selection, and evaluation with scikit-learn.
Tracing, evaluations, prompt iteration, and observability practices for LLM application development.
Core networking concepts, protocols, troubleshooting techniques, and connectivity fundamentals for engineers.
Project structure, ORM patterns, views, templates, APIs, and production delivery with Django.
Notebook workflows, kernels, widgets, reproducibility, parameterized execution, and production-safe Jupyter patterns.
Python basics, syntax, functions, modules, and beginner-friendly programming foundations.
Intermediate Python patterns, data structures, decorators, typing, and testing practices.
Advanced Python internals, concurrency, design patterns, and production engineering techniques.
FastAPI routing, validation, dependency injection, async APIs, and service design patterns.
ASGI serving, runtime configuration, performance tuning, and operational guidance for Uvicorn.