# ai-engineering-from-scratch | Rohit Ghumare | Knowledge Base | Instagit Learn it. Build it. Ship it for others. GitHub Stars: 10.2k Repository: https://github.com/rohitg00/ai-engineering-from-scratch --- ## Articles ### [Production LLM Deployment Best Practices: Caching, Rate Limiting, and Cost Optimization](/rohitg00/ai-engineering-from-scratch/production-llm-deployment-caching-rate-limiting-cost-optimization) Master production LLM deployment. Learn caching, rate limiting, and cost optimization strategies for efficient, high-availability AI systems. Optimize your token costs now. - Tags: best-practices - Published: 2026-06-11 ### [How to Achieve Agent Observability Using OpenTelemetry and Langfuse](/rohitg00/ai-engineering-from-scratch/agent-observability-opentelemetry-langfuse) Learn how to achieve agent observability with OpenTelemetry and Langfuse. Instrument your code, export spans, and gain valuable insights into your AI agent's performance. Start monitoring today. - Tags: tutorial - Published: 2026-06-11 ### [How the Transformer Architecture Is Implemented From First Principles](/rohitg00/ai-engineering-from-scratch/transformer-architecture-first-principles-implementation) Learn how the Transformer architecture is implemented from first principles using pure PyTorch. Explore every mathematical component of a working GPT-style decoder without high-level abstractions. - Tags: deep-dive - Published: 2026-06-11 ### [How to Fine-Tune LLMs Using LoRA and QLoRA: A Complete Implementation Guide](/rohitg00/ai-engineering-from-scratch/finetune-llms-lora-qlora) Master LoRA and QLoRA to fine-tune LLMs efficiently. Learn how these techniques drastically cut VRAM needs while preserving model quality. Implement now. - Tags: how-to-guide - Published: 2026-06-11 ### [Effective Implementation Strategies for RAG: A Production-Grade Architecture](/rohitg00/ai-engineering-from-scratch/rag-implementation-strategies) Implement production-grade RAG effectively with a multi-stage pipeline covering chunking, hybrid retrieval, query rewriting and reranking for peak accuracy before generation. - Tags: architecture - Published: 2026-06-11 ### [How the AI Engineering From Scratch Curriculum Uses the Build It / Use It Methodology](/rohitg00/ai-engineering-from-scratch/ai-engineering-curriculum-build-it-use-it-structure) Master AI engineering by building algorithms from scratch and then using production libraries. The AI Engineering From Scratch curriculum uses the Build It Use It methodology for deep understanding. - Tags: architecture - Published: 2026-06-11 ### [What Agent Memory Architectures Are Taught in AI: 4 Production Patterns Explained](/rohitg00/ai-engineering-from-scratch/ai-agent-memory-architectures-taught) Discover the 4 agent memory architectures taught in AI including hybrid stores tiered blocks virtual contexts and blackboards implemented in Python for production readiness. - Tags: deep-dive - Published: 2026-06-10 ### [How RAG Is Implemented with Chunking and Reranking in AI-Engineering-From-Scratch](/rohitg00/ai-engineering-from-scratch/rag-implementation-chunking-reranking) Learn how RAG is implemented with token chunking, TF-IDF indexing, and cosine similarity search. Discover our three-stage retrieval architecture and reranking method. - Tags: deep-dive - Published: 2026-06-10 ### [Production Patterns for Deploying AI Agents: 10 Enterprise Architectural Blueprints](/rohitg00/ai-engineering-from-scratch/production-patterns-deploying-ai-agents) Discover 10 enterprise architectural blueprints for deploying AI agents in production. Learn production patterns for robust, scalable AI services with layered architectures and safety guardrails. - Tags: architecture - Published: 2026-06-10 ### [What Are AI Agent Swarm Patterns? Decentralized Multi-Agent Orchestration Explained](/rohitg00/ai-engineering-from-scratch/ai-agent-swarm-patterns) Explore AI agent swarm patterns, the decentralized orchestration for homogeneous agents. Learn how direct state exchange enables efficient parallel task completion for optimization and routing. - Tags: deep-dive - Published: 2026-06-10 ### [How to Handle Multi-Agent Systems in AI: A Production-Ready Architecture Guide](/rohitg00/ai-engineering-from-scratch/multi-agent-systems-ai-handling) Learn to handle multi-agent systems in AI with a production-ready architecture. Explore layered design, state machines, A2A protocols, and failure auditing for robust agent coordination. - Tags: architecture - Published: 2026-06-10 ### [Vision Transformer (ViT) Architecture: From Pixels to Patches](/rohitg00/ai-engineering-from-scratch/vision-transformer-vit-architecture-explained) Understand the Vision Transformer ViT architecture. Learn how ViT converts images into patch embeddings and uses a transformer encoder for classification. Explore the core concepts. - Tags: deep-dive - Published: 2026-06-10 ### [How to Implement LLM Quantization for Inference: A Complete Guide](/rohitg00/ai-engineering-from-scratch/llm-quantization-inference-implementation) Learn LLM quantization for inference: Shrink models to INT4/INT8 with GPTQ/AWQ for efficient deployment on limited hardware while preserving accuracy. A complete guide for AI engineers on GitHub. - Tags: how-to-guide - Published: 2026-06-10 ### [How to Implement DPO for LLM Alignment: A Complete Guide from the ai-engineering-from-scratch Repository](/rohitg00/ai-engineering-from-scratch/implement-dpo-llm-alignment-training) Learn to implement Direct Preference Optimization DPO for LLM alignment with this comprehensive guide. Optimize language models directly using human preference pairs. No reward model needed. - Tags: how-to-guide - Published: 2026-06-10 ### [How to Implement RLHF for LLM Alignment: A Complete Guide from Scratch](/rohitg00/ai-engineering-from-scratch/implement-rlhf-llm-alignment-training) Learn how to implement RLHF for LLM alignment with this comprehensive guide. Build a reward model and optimize your LLM using PPO from scratch. - Tags: how-to-guide - Published: 2026-06-10 ### [How the ReAct Agent Loop Works: Understanding the Reason-Act Pattern](/rohitg00/ai-engineering-from-scratch/agent-loop-react-pattern-implementation) Understand the ReAct agent loop: LLM reasons, acts with tools, observes results. Learn this pattern for efficient AI task completion. - Tags: deep-dive - Published: 2026-06-10 ### [What Is the Model Context Protocol (MCP) in AI?](/rohitg00/ai-engineering-from-scratch/model-context-protocol-mcp-definition) Discover the Model Context Protocol (MCP) in AI. Unify LLM tool discovery and execution with this open standard, eliminating integration fragmentation. Learn more. - Tags: deep-dive - Published: 2026-06-10 ### [AI Engineering from Scratch: The Complete 20-Phase Learning Progression](/rohitg00/ai-engineering-from-scratch/ai-curriculum-recommended-learning-progression) Master AI Engineering with this 20-phase learning progression. Start with Python and math, advance through ML, DL, LLMs, and tackle multimodal AI and autonomous agents. - Tags: getting-started - Published: 2026-06-10 ### [The 20 Phases of the AI Engineering Curriculum: A Complete Developer Roadmap](/rohitg00/ai-engineering-from-scratch/ai-engineering-curriculum-20-phases) Explore the 20 phases of the AI engineering curriculum. This comprehensive developer roadmap guides you through fundamental tools to advanced projects with code and assessments. - Tags: architecture - Published: 2026-06-10 ### [How Reusable AI Artifacts Are Structured in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/reusable-ai-artifacts-structure-prompts-agents) Discover how reusable AI artifacts like prompts and agents are structured in the ai-engineering-from-scratch repository using a centralized JSON catalog for easy discovery. - Tags: architecture - Published: 2026-06-10 ### [What Is the Build It / Use It Philosophy in AI Engineering?](/rohitg00/ai-engineering-from-scratch/build-it-use-it-ai-engineering-philosophy) Discover the Build It Use It AI engineering philosophy. Learn algorithms from scratch then rebuild with frameworks to master abstraction and production readiness. - Tags: deep-dive - Published: 2026-06-10 ### [How the rohitg00/ai-engineering-from-scratch Repository Is Organized by Lessons](/rohitg00/ai-engineering-from-scratch/rohitg00-ai-engineering-from-scratch-lesson-organization) Explore the rohitg00/ai-engineering-from-scratch repository learn how its lessons are organized. Discover standardized documentation code quizzes and artifacts within a clear structure. - Tags: getting-started - Published: 2026-06-10 ### [Production Deployment Patterns for LLM Applications: 7 Production-Grade Architectures](/rohitg00/ai-engineering-from-scratch/what-production-deployment-patterns-are-covered-for-llm-applications) Explore 7 production deployment patterns for LLM applications: speculative decoding, hybrid RAG, multi-agent orchestration, TensorRT-LLM, safety, and observability architectures. - Tags: architecture - Published: 2026-06-09 ### [How `audit_lessons.py` Validates `docs/en.md` Files: 4 Automated Checks Explained](/rohitg00/ai-engineering-from-scratch/what-validation-does-audit_lessons.py-perform-on-docs-en.md-files) Discover the 4 automated validation checks in audit_lessons.py that ensure docs en md files are complete and consistent. Learn about existence, size, H1 headings and internal links. - Tags: how-to-guide - Published: 2026-06-09 ### [How install_skills.py Manages Artifact Versioning and Tagging](/rohitg00/ai-engineering-from-scratch/how-does-install_skills.py-manage-artifact-versioning-and-tagging) Discover how install_skills.py manages artifact versioning and tagging by leveraging YAML front-matter and generated manifests for efficient version tracking and filtering. - Tags: how-to-guide - Published: 2026-06-09 ### [Understanding the Lesson Contract in AGENTS.md: Required Files and Structure](/rohitg00/ai-engineering-from-scratch/what-is-the-lesson-contract-in-agents.md-and-required-files-for-each-lesson) Discover the lesson contract in AGENTS.md. Learn the essential files and structure required for each lesson in ai-engineering-from-scratch to ensure automated validation and publication. - Tags: deep-dive - Published: 2026-06-09 ### [How Phase Directories Are Structured in AI Engineering From Scratch: Naming Patterns Explained](/rohitg00/ai-engineering-from-scratch/how-are-phase-directories-structured-and-what-naming-patterns-are-used) Discover how phase directories in AI engineering from scratch are structured with zero-padded numbering and kebab-case descriptors for organized, automated content access. - Tags: deep-dive - Published: 2026-06-09 ### [CI/CD Workflows Defined in curriculum.yml: Automated Testing for AI Engineering Curriculum](/rohitg00/ai-engineering-from-scratch/what-ci-cd-workflows-are-defined-in-curriculum.yml-and-what-do-they-test) Explore CI/CD workflows in curriculum.yml: audit, readme-counts-sync, site-rebuild, and readme-counts-drift automate testing for AI Engineering curriculum, ensuring lesson structure and documentation accuracy. Learn more! - Tags: how-to-guide - Published: 2026-06-09 ### [How the AI Engineering from Scratch Curriculum Validates Internal Links in Lesson Documentation](/rohitg00/ai-engineering-from-scratch/how-does-the-curriculum-validate-internal-links-in-lesson-documentation) Learn how the AI Engineering from Scratch curriculum automatically validates internal links in lesson documentation using a Python script to ensure all cross-references are accurate and functional. - Tags: how-to-guide - Published: 2026-06-09 ### [How the AI Engineering From Scratch Curriculum Supports Python, Rust, and Julia](/rohitg00/ai-engineering-from-scratch/how-does-the-curriculum-support-multiple-programming-languages-like-python-rust-and-julia) Learn how the ai engineering from scratch curriculum supports Python Rust and Julia with its language agnostic lesson contract and parallel source files for seamless integration. - Tags: deep-dive - Published: 2026-06-09 ### [Layout Options in `install_skills.py`: How `flat`, `by-phase`, and `skills` Work](/rohitg00/ai-engineering-from-scratch/what-are-the-layout-options-flat-by-phase-skills-in-install_skills.py) Explore the flat, by-phase, and skills layout options in install_skills.py to organize course artifacts effectively in your AI engineering projects. - Tags: how-to-guide - Published: 2026-06-09 ### [How Lesson Outputs Are Organized in the Phases Directory: Structure and Naming Conventions](/rohitg00/ai-engineering-from-scratch/how-are-lesson-outputs-organized-in-the-phases-directory-and-what-are-the-naming-conventions) Learn how lesson outputs are organized in the phases directory of rohitg00/ai-engineering-from-scratch. Discover naming conventions for skills, prompts, and reports. - Tags: internals - Published: 2026-06-09 ### [Artifact Discovery and Frontmatter Parsing in install_skills.py: A Complete Guide](/rohitg00/ai-engineering-from-scratch/what-is-the-artifact-discovery-and-frontmatter-parsing-in-install_skills.py) Learn artifact discovery and frontmatter parsing in install_skills.py. This guide explains how the script extracts YAML frontmatter from Markdown files to create typed Artifacts without dependencies. - Tags: how-to-guide - Published: 2026-06-09 ### [How AI Engineering from Scratch Audits Lesson Structures: Automated Curriculum Validation](/rohitg00/ai-engineering-from-scratch/how-does-rohitg00-ai-engineering-from-scratch-audit-lesson-structures-and-enforce-rules) Learn how ai-engineering-from-scratch audits lesson structures using an automated pipeline and GitHub Actions. Ensure curriculum integrity with strict validation rules. - Tags: how-to-guide - Published: 2026-06-09 ### [Understanding the Agent Loop Implementation from Scratch: A Minimal ReAct Architecture](/rohitg00/ai-engineering-from-scratch/understanding-agent-loop-implementation-scratch-ai-project) Learn the agent loop implementation from scratch with this minimal ReAct architecture. Explore thought generation, tool execution, and observation in this dependency-free Python ReAct pattern. - Tags: deep-dive - Published: 2026-06-08 ### [How to Add New Terms to the Glossary in AI Engineering From Scratch](/rohitg00/ai-engineering-from-scratch/how-to-add-new-terms-glossary-terms.md) Easily add new terms to the AI Engineering From Scratch glossary. Learn the required H3 and bullet format for the terms.md file to ensure proper parsing. - Tags: how-to-guide - Published: 2026-06-08 ### [How to Install Skills with `install_skills.py`: Complete Guide to the AI Engineering Curriculum Artifact Installer](/rohitg00/ai-engineering-from-scratch/skill-installation-process-install_skills.py) Learn the skill installation process using install_skills.py. This guide covers the AI Engineering Curriculum Artifact Installer script for easy setup. - Tags: how-to-guide - Published: 2026-06-08 ### [How to Handle Merge Conflicts in the AI Engineering from Scratch Curriculum](/rohitg00/ai-engineering-from-scratch/how-to-handle-merge-conflicts-ai-engineering-scratch-curriculum) Learn to resolve merge conflicts in AI Engineering from Scratch. Preserve markdown syntax, regenerate data.js, and validate changes for seamless project integration. - Tags: how-to-guide - Published: 2026-06-08 ### [How to Locally Validate AI Engineering Lessons Before Submitting a PR](/rohitg00/ai-engineering-from-scratch/how-to-locally-validate-ai-engineering-lessons-before-pr) Validate AI engineering lessons locally before submitting a PR. Run audit, check_readme_counts, and lesson_run scripts to catch errors and ensure code quality before your pull request. - Tags: how-to-guide - Published: 2026-06-08 ### [Conventional Commit Format Requirement for rohitg00/ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/conventional-commit-format-requirement-rohitg00-ai-engineering-from-scratch) Learn the conventional commit format for rohitg00/ai-engineering-from-scratch. Commits need feat(phase-NN/MM): , be under 72 chars, and explain the why. - Tags: best-practices - Published: 2026-06-08 ### [How to Contribute Glossary Terms to the AI Engineering From-Scratch Repository](/rohitg00/ai-engineering-from-scratch/process-contributing-glossary-terms-ai-engineering-repo) Learn how to contribute glossary terms to the AI Engineering From-Scratch repository. Fork, add your term to terms.md, validate the index, and submit a pull request. - Tags: how-to-guide - Published: 2026-06-08 ### [CI Workflow Gates in curriculum.yml: Four Automated Validation Gates Explained](/rohitg00/ai-engineering-from-scratch/ci-workflow-gates-curriculum.yml-what-they-validate) Discover the four CI workflow gates in curriculum.yml: audit, readme-counts-sync, site-rebuild, and readme-counts-drift. Learn how they automate validation for your AI engineering curriculum. - Tags: how-to-guide - Published: 2026-06-08 ### [How `data.js` Is Generated from `README.md` and `ROADMAP.md` in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-data.js-generated-readme-roadmap-ai-engineering-project) Learn how site data js is generated in AI Engineering from Scratch. Discover how README md and ROADMAP md files are parsed and transformed into structured JavaScript objects for the project. - Tags: internals - Published: 2026-06-08 ### [Why NumPy, PyTorch, and h5py Are the Only Packages Allowed in the AI Engineering Curriculum](/rohitg00/ai-engineering-from-scratch/why-only-numpy-torch-h5py-allowed-ai-engineering-curriculum) Discover why AI Engineering restricts packages to NumPy, PyTorch, and h5py. Learn about the educational benefits of a standard-library-first, lightweight, and secure approach. - Tags: best-practices - Published: 2026-06-08 ### [How site/data.js URL Generation Works in AI Engineering From Scratch](/rohitg00/ai-engineering-from-scratch/how-does-site-data-js-url-generation-work) Explore how the site/data.js URL generation works in AI Engineering From Scratch. Discover how lesson links are parsed and converted into absolute URLs by the build script. - Tags: internals - Published: 2026-06-07 ### [How Phases and Prerequisites in AI Engineering from Scratch Form a Validated Learning DAG](/rohitg00/ai-engineering-from-scratch/what-is-relationship-between-phases-and-prerequisites) Discover how phases and prerequisites in AI Engineering from Scratch create a learning DAG. Understand lesson dependencies for expert AI development. Learn more. - Tags: internals - Published: 2026-06-07 ### [How Conventional Commit Format Works in the AI-Engineering-From-Scratch Repository](/rohitg00/ai-engineering-from-scratch/how-does-conventional-commit-format-work-here) Understand the strict conventional commit format in rohitg00/ai-engineering-from-scratch. Learn how feat, phase-NN/MM scope, and kebab-case descriptions ensure readability and machine processing. - Tags: how-to-guide - Published: 2026-06-07 ### [How Reusable Artifact Outputs (Prompts, Skills, Agents) Work in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-do-reusable-artifact-outputs-work) Learn how reusable artifact outputs like prompts skills and agents in AI Engineering from Scratch enable immediate deployment of battle-tested tools directly from lesson outputs. - Tags: internals - Published: 2026-06-07 ### [What Makes the AI Engineering from Scratch Curriculum Different from Other AI Courses](/rohitg00/ai-engineering-from-scratch/what-makes-this-curriculum-different-from-other-ai-courses) Explore the AI Engineering from Scratch curriculum's unique 20-phase approach. Learn by building algorithms from math before frameworks across Python, TypeScript, Rust, and Julia. - Tags: architecture - Published: 2026-06-07 ### [How to Customize or Extend Existing Lesson Code in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-to-customize-or-extend-existing-lesson-code) Easily customize and extend AI Engineering from Scratch lesson code. Modify main Python files, validate with lesson_run.py, and test thoroughly to build your AI projects. - Tags: how-to-guide - Published: 2026-06-07 ### [How catalog.json Is Generated and Used in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-is-catalog-json-generated-and-used) Discover how catalog.json is generated and used in AI Engineering from Scratch. Ensure your AI curriculum stays in sync with this essential manifest. - Tags: internals - Published: 2026-06-07 ### [What Does the `scaffold-lesson.sh` Automation Script Do?](/rohitg00/ai-engineering-from-scratch/what-does-scaffold-lesson-sh-automation-script-do) Discover what the scaffold-lesson.sh automation script does for the AI Engineering From Scratch repository. It creates standardized lesson structures to ensure consistency and streamline development. - Tags: how-to-guide - Published: 2026-06-07 ### [How to Resolve Merge Conflicts in the AI Engineering from Scratch Repository](/rohitg00/ai-engineering-from-scratch/how-to-resolve-merge-conflicts-in-this-repository) Learn to resolve merge conflicts in the AI Engineering from Scratch repository. Fetch main, fix conflicts, commit atomically, validate, and push for CI rebuild. - Tags: how-to-guide - Published: 2026-06-07 ### [What the curriculum.yml GitHub Workflow Does in AI Engineering from Scratch: 4 Automated Jobs Explained](/rohitg00/ai-engineering-from-scratch/what-does-curriculum-yml-github-workflow-do) Explore the curriculum.yml GitHub workflow in AI Engineering from Scratch. Learn how it automatically audits, syncs READMEs, rebuilds data, and prevents drift on every push or pull request. - Tags: internals - Published: 2026-06-07 ### [How MCP Servers Are Built in Phase 13: FastMCP, OAuth, and Registry Governance](/rohitg00/ai-engineering-from-scratch/how-are-mcp-servers-built-in-phase-13-lessons) Learn how to build MCP servers in Phase 13 of AI Engineering from Scratch. Explore FastMCP, OAuth, and OPA for robust HTTP transport, scope enforcement, and governance with a registry service. - Tags: deep-dive - Published: 2026-06-07 ### [How Claude and Cursor Skill Integrations Work in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-do-claude-and-cursor-skill-integrations-work) Discover how Claude and Cursor skill integrations work in AI Engineering from Scratch. Learn about SKILL.md artifacts and MCP for seamless reusable capability discovery and execution. - Tags: deep-dive - Published: 2026-06-07 ### [How ROADMAP.md Tracks Lesson Completion Status in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-does-roadmap-md-track-lesson-completion-status) Learn how ROADMAP.md tracks AI Engineering lesson completion using Unicode glyphs. Discover how status indicators power the curriculum website and llms.txt. - Tags: how-to-guide - Published: 2026-06-07 ### [How `glossary/terms.md` Powers Consistent Terminology Across Lessons in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-does-glossary-terms-md-work-across-lessons) Learn how glossary terms.md ensures consistent terminology in AI Engineering from Scratch. Discover how site build.js creates a GLOSSARY constant for unified lesson definitions. - Tags: internals - Published: 2026-06-07 ### [How to Run Individual Lesson Code Locally for AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-to-run-individual-lesson-code-locally) Easily run AI Engineering from Scratch lesson code locally. Clone the repository, install dependencies, and execute code from any lesson folder. Get hands-on with AI projects today. - Tags: how-to-guide - Published: 2026-06-07 ### [How site/build.js Generates the data.js File in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/how-does-site-build-js-generate-data-js-file) Learn how sitebuildjs in ai-engineering-from-scratch transforms markdown curriculum into structured JavaScript modules. Discover its content enrichment and export process. - Tags: internals - Published: 2026-06-07 ### [What Dependencies Are Allowed in AI Engineering from Scratch and Why](/rohitg00/ai-engineering-from-scratch/what-dependencies-are-allowed-in-lesson-code-and-why) Discover allowed dependencies in AI Engineering from Scratch lessons. Learn core math and algorithms without large frameworks. Focus on numpy torch hono zod and standard libraries for deeper understanding. - Tags: best-practices - Published: 2026-06-07 ### [How the audit_lessons.py CI Validation Script Enforces Lesson Quality](/rohitg00/ai-engineering-from-scratch/how-does-audit-lessons-py-ci-validation-script-work) Learn how the audit_lessons.py CI validation script ensures lesson quality. Discover how it checks documentation, code, quizzes, and links in rohitg00/ai-engineering-from-scratch. - Tags: how-to-guide - Published: 2026-06-07 ### [How to Add a New Lesson to the AI Engineering from Scratch Curriculum](/rohitg00/ai-engineering-from-scratch/how-do-i-add-new-lesson-to-ai-engineering-from-scratch-curriculum) Learn to add a new lesson to the AI Engineering from Scratch curriculum. Follow simple steps to create folders, write documentation, and register your lesson for contribution. - Tags: how-to-guide - Published: 2026-06-07 ### [What Is the Build It / Use It Methodology in AI Engineering From Scratch?](/rohitg00/ai-engineering-from-scratch/what-is-build-it-use-it-methodology-in-ai-engineering-from-scratch-curriculum) Discover the Build It Use It methodology in AI engineering from scratch. Learn AI algorithms from math, then refactor with production frameworks, understanding abstraction layers. - Tags: getting-started - Published: 2026-06-07 ### [How to Find Your Starting Level in the AI Engineering from Scratch Curriculum](/rohitg00/ai-engineering-from-scratch/how-do-i-find-my-starting-level-in-ai-engineering-from-scratch-curriculum) Discover your AI Engineering from Scratch starting level using the rohitg00/ai-engineering-from-scratch repository's placement quiz. Get personalized curriculum recommendations now. - Tags: getting-started - Published: 2026-06-07 ### [How the AI Engineering from Scratch Curriculum Phase Progression Works: A 20-Phase Blueprint](/rohitg00/ai-engineering-from-scratch/how-does-ai-engineering-from-scratch-curriculum-phase-progression-work) Explore the 20-phase AI Engineering from Scratch curriculum progression from foundations to autonomous agents. See prerequisite mapping and how CI enforces your learning path. - Tags: architecture - Published: 2026-06-07 ### [How to Debug Issues When Running Code in AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/how-to-debug-issues-running-ai-engineering-code) Debug runtime errors in AI Engineering from Scratch by validating structure with audit_lessons.py and running lesson tests via main.py. Fix issues in the rohitg00/ai-engineering-from-scratch curriculum efficiently. - Tags: how-to-guide - Published: 2026-06-06 ### [AI Engineering from Scratch Roadmap for Future Development: 20 Phases, 503 Lessons, and ~1,050 Hours](/rohitg00/ai-engineering-from-scratch/is-there-roadmap-for-future-development-of-ai-engineering-project) Explore the AI Engineering from Scratch roadmap with 20 phases and 503 lessons. Plan your learning journey for future development with this extensive curriculum. - Tags: roadmap - Published: 2026-06-06 ### [AI Engineering from Scratch License: MIT Terms and Usage Rights](/rohitg00/ai-engineering-from-scratch/what-are-licensing-details-for-ai-engineering-repo) Understand the MIT License for AI Engineering from Scratch. Freely use, modify, and distribute the code for commercial projects. All rights reserved. - Tags: api-reference - Published: 2026-06-06 ### [How to Test the AI Components Developed in the AI Engineering From Scratch Repository](/rohitg00/ai-engineering-from-scratch/how-to-test-ai-components-developed-in-repo) Easily test AI components from the ai engineering from scratch repository. Run self-contained test suites with standard runners, validated by our CI pipeline for robust results. - Tags: testing - Published: 2026-06-06 ### [Limitations of the AI Models in AI Engineering From Scratch: A Technical Deep Dive](/rohitg00/ai-engineering-from-scratch/what-are-limitations-of-ai-models-presented-in-repo) Explore 10 limitations of AI models in AI Engineering From Scratch, from prompt injection to training bottlenecks. Learn why production LLMs need advanced guardrails, calibration, and optimization. - Tags: deep-dive - Published: 2026-06-06 ### [Is rohitg00/ai-engineering-from-scratch Suitable for Beginners in AI Engineering?](/rohitg00/ai-engineering-from-scratch/is-ai-engineering-from-scratch-suitable-for-beginners) Yes, rohitg00/ai-engineering-from-scratch is perfect for AI engineering beginners. This 20-phase curriculum guides you from zero to understanding modern AI systems with basic coding skills. - Tags: getting-started - Published: 2026-06-06 ### [Recommended Tools and Frameworks for AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/what-tools-or-frameworks-recommended-for-ai-engineering-project) Master AI engineering from scratch with recommended Python, Node.js, and Rust tools and frameworks. Build production-grade AI solutions efficiently. - Tags: best-practices - Published: 2026-06-06 ### [How to Deploy AI Models from the AI Engineering From Scratch Repository](/rohitg00/ai-engineering-from-scratch/how-to-deploy-ai-models-from-this-repository) Deploy AI models from rohitg00/ai-engineering-from-scratch using Docker, FP8/INT4 quantization, and Kubernetes with queue-based autoscaling. Learn efficient AI model deployment now. - Tags: how-to-guide - Published: 2026-06-06 ### [CI/CD Pipelines in AI Engineering From Scratch: GitHub Actions Workflow Explained](/rohitg00/ai-engineering-from-scratch/are-there-ci-cd-pipelines-set-up-for-ai-engineering-project) Explore CI/CD pipelines in AI engineering with GitHub Actions. This repo automates curriculum validation, doc syncing, and website rebuilds for seamless project updates. - Tags: tutorial - Published: 2026-06-06 ### [AI Engineering Best Practices Demonstrated in the ai-engineering-from-scratch Repository](/rohitg00/ai-engineering-from-scratch/best-practices-for-ai-engineering-demonstrated-in-repo) Explore AI engineering best practices in the ai-engineering-from-scratch repository. Discover modular design, dual implementation, zero-dependency policies, and automated artifact generation for production-grade AI. - Tags: best-practices - Published: 2026-06-06 ### [How to Interpret the Results from AI Models: Metrics, Cross-Validation, and Evaluation Pipelines](/rohitg00/ai-engineering-from-scratch/how-to-interpret-results-from-ai-models-in-ai-engineering) Learn to interpret AI model results using train/validation/test splits, cross-validation, and learning curves. Choose appropriate metrics like precision, recall, RMSE, or R² to understand your AI's performance. - Tags: deep-dive - Published: 2026-06-06 ### [Clear Explanation of the Algorithms Used in AI Engineering From Scratch: A Complete Review](/rohitg00/ai-engineering-from-scratch/is-there-clear-explanation-of-algorithms-used-in-ai-engineering) Explore algorithms used in AI Engineering From Scratch. Get clear, step-by-step explanations with code and tests in this comprehensive review. - Tags: deep-dive - Published: 2026-06-06 ### [Evaluation Metrics for AI Models in ai-engineering-from-scratch: From BLEU to Calibration Error](/rohitg00/ai-engineering-from-scratch/what-evaluation-metrics-are-used-for-ai-models-in-this-project) Explore AI model evaluation metrics in ai-engineering-from-scratch. Discover BLEU, ROUGE, calibration error, and more built from first principles. - Tags: tutorial - Published: 2026-06-06 ### [How Model Training Is Handled in ai-engineering-from-scratch: From NumPy Loops to Distributed ZeRO](/rohitg00/ai-engineering-from-scratch/how-is-model-training-handled-in-ai-engineering-from-scratch) Learn how model training is handled in ai-engineering-from-scratch. Start with NumPy loops, then master PyTorch best practices like gradient clipping and distributed ZeRO sharding. - Tags: deep-dive - Published: 2026-06-06 ### [Data Preprocessing Techniques in AI Engineering from Scratch: Complete Implementation Guide](/rohitg00/ai-engineering-from-scratch/does-this-repository-include-data-preprocessing-techniques) Implement AI data preprocessing techniques from scratch. Explore NLP tokenization, lemmatization, image normalization, and LLM text cleaning in this comprehensive guide. - Tags: how-to-guide - Published: 2026-06-06 ### [How to Contribute to the AI Engineering from Scratch Project: A Complete Guide](/rohitg00/ai-engineering-from-scratch/how-can-i-contribute-to-ai-engineering-from-scratch-project) Contribute to the ai-engineering-from-scratch project easily. Fork the repo, add lessons, pass tests, and submit a pull request. Get started today! - Tags: how-to-guide - Published: 2026-06-06 ### [AI Engineering Tutorials and Guides: Complete Hands-On Curriculum](/rohitg00/ai-engineering-from-scratch/are-there-tutorials-or-guides-in-ai-engineering-from-scratch) Explore AI engineering with hands-on tutorials and guides. This complete curriculum offers explanations, runnable code, and deployable artifacts for practical learning. - Tags: tutorial - Published: 2026-06-06 ### [AI Engineering From Scratch Folder Structure: Complete 20-Phase Curriculum Guide](/rohitg00/ai-engineering-from-scratch/what-is-folder-structure-of-rohitg00-ai-engineering-from-scratch) Explore the AI Engineering From Scratch folder structure with this comprehensive 20-phase curriculum guide. Discover the organized layout of code, docs, and outputs in the rohitg00/ai-engineering-from-scratch repository. - Tags: architecture - Published: 2026-06-06 ### [How to Run Example Code in ai-engineering-from-scratch: A Complete Execution Guide](/rohitg00/ai-engineering-from-scratch/how-to-run-example-code-in-ai-engineering-from-scratch) Learn to run example code in ai-engineering-from-scratch. Clone the repo, install dependencies, and execute lessons easily with our execution guide. - Tags: how-to-guide - Published: 2026-06-06 ### [AI-Engineering-from-Scratch Dependencies: Python, TypeScript, Rust, and Julia Libraries](/rohitg00/ai-engineering-from-scratch/what-are-dependencies-for-ai-engineering-from-scratch-project) Discover the essential dependencies for AI Engineering from Scratch. Explore Python, TypeScript, Rust, and Julia libraries required for this comprehensive project. - Tags: getting-started - Published: 2026-06-06 ### [What Programming Languages Are Used in the AI Engineering From Scratch Repository?](/rohitg00/ai-engineering-from-scratch/what-programming-languages-used-in-ai-engineering-repository) Discover AI engineering from scratch using Python, TypeScript, Rust, and Julia. Explore 435 lessons building AI concepts from first principles in the rohitg00/ai-engineering-from-scratch repository. - Tags: getting-started - Published: 2026-06-06 ### [Core AI Concepts Covered in AI Engineering from Scratch: Complete 20‑Phase Curriculum](/rohitg00/ai-engineering-from-scratch/what-are-core-ai-concepts-in-ai-engineering-from-scratch) Explore core AI concepts in AI Engineering from Scratch. This 16-phase open-source curriculum covers math, deep learning, generative AI, and autonomous agents. - Tags: getting-started - Published: 2026-06-06 ### [How to Set Up the rohitg00/ai-engineering-from-scratch Project: Complete Installation Guide](/rohitg00/ai-engineering-from-scratch/how-to-set-up-rohitg00-ai-engineering-from-scratch-project) Set up the rohitg00/ai-engineering-from-scratch project easily. Follow our complete installation guide to clone the repo, install dependencies, and verify your environment is ready for AI engineering. - Tags: getting-started - Published: 2026-06-06 ### [How Verification Gates and Runtime Feedback Loops Operate in Autonomous Agents](/rohitg00/ai-engineering-from-scratch/verification-gates-runtime-feedback-loops-explained) Understand verification gates and runtime feedback loops in autonomous agents. Discover how these systems ensure safety and observability by filtering LLM tool calls and managing execution logs. - Tags: deep-dive - Published: 2026-06-05 ### [How ROADMAP.md Tracks the Completion Status of Lessons in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/how-roadmap-md-tracks-lesson-completion) Discover how ROADMAP.md in ai-engineering-from-scratch uses emojis to track lesson completion status. Learn how site build scripts process these statuses for the project website. - Tags: how-to-guide - Published: 2026-06-05 ### [What Criteria Determine Which Dependencies Are Allowed or Banned in AI Engineering from Scratch?](/rohitg00/ai-engineering-from-scratch/dependency-allowlist-and-blocklist-criteria) Discover criteria for approved AI engineering dependencies. Explore the stdlib-first philosophy and dependency allowlist used in ai-engineering-from-scratch for clarity. - Tags: best-practices - Published: 2026-06-05 ### [What Makes MCP Server Lessons Different from Standard Code Lessons](/rohitg00/ai-engineering-from-scratch/mcp-server-lessons-vs-regular-code-lessons) Discover how MCP server lessons teach production-grade architectural design with Model Context Protocol, unlike standard code lessons that focus on isolated algorithms. Learn scalable service development. - Tags: comparison - Published: 2026-06-05 ### [Find-Your-Level Placement Quiz Skill: How It Works in the AI Engineering from Scratch Curriculum](/rohitg00/ai-engineering-from-scratch/find-your-level-placement-quiz-skill-explained) Discover the find-your-level placement quiz skill that assesses 5 core AI engineering areas. Find your ideal starting phase in the 20-phase AI Engineering from Scratch curriculum. - Tags: getting-started - Published: 2026-06-05 ### [How `site/data.js` Is Generated in ai-engineering-from-scratch: Build Pipeline Explained](/rohitg00/ai-engineering-from-scratch/site-data-js-generation-process) Discover how site/data.js is generated in ai-engineering-from-scratch. Learn about the build pipeline that parses markdown and scans lesson directories, exporting PRASES, GLOSSARY, and ARTIFACTS. - Tags: internals - Published: 2026-06-05 ### [How to Contribute Terms to the Glossary at terms.md in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/how-to-add-terms-to-glossary-md) Learn how to contribute terms to the glossary at terms.md in the ai-engineering-from-scratch repository. Follow straightforward steps to add your AI definitions. - Tags: how-to-guide - Published: 2026-06-05 ### [What Is the Specific Structure of Agent Workbench Lessons? Inside the ai-engineering-from-scratch Curriculum](/rohitg00/ai-engineering-from-scratch/structure-of-agent-workbench-lessons) Explore the specific structure of Agent Workbench lessons within the ai-engineering-from-scratch curriculum. Discover documented tutorials, executable code, unit tests, and quizzes. - Tags: getting-started - Published: 2026-06-05 ### [How Multi-Language Lessons Are Implemented in ai-engineering-from-scratch: Python, Julia, Rust, and TypeScript](/rohitg00/ai-engineering-from-scratch/multi-language-lesson-implementation) Learn how ai-engineering-from-scratch implements multi-language lessons using Python, Julia, Rust, and TypeScript. Explore the code structure and understand the unified approach across languages. - Tags: internals - Published: 2026-06-05 ### [The Four Types of Artifacts in AI Engineering: Prompts, Skills, Agents, and MCP Servers](/rohitg00/ai-engineering-from-scratch/four-artifact-types-prompts-skills-agents-mcp-servers) Discover the four key AI engineering artifacts prompts skills agents and MCP servers essential for building production grade AI systems. Learn their roles and applications in ai engineering from scratch. - Tags: deep-dive - Published: 2026-06-05 ### [Distinctions Between Learn, Build, and Reference Lesson Types in AI Engineering From Scratch](/rohitg00/ai-engineering-from-scratch/difference-between-learn-build-reference-lesson-types) Understand the differences between Learn, Build, and Reference lesson types in AI engineering from scratch. Discover how each type contributes to foundational AI knowledge and practical application. - Tags: deep-dive - Published: 2026-06-05 ### [How to Install and Use Reusable Skill Artifacts in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/install-and-use-reusable-skill-artifacts) Install reusable skill artifacts in ai-engineering-from-scratch using the install_skills.py script. Copy Markdown files and manifest.json to create AI pipelines. - Tags: how-to-guide - Published: 2026-06-05 ### [Commit Message Conventions for Contributing Lessons to AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/commit-conventions-for-contributing-lessons) Learn Conventional Commits for AI engineering contributions. Follow the feat(phase-NN/MM): format to submit lessons effectively to the ai-engineering-from-scratch repository. - Tags: best-practices - Published: 2026-06-05 ### [How to Add a New Lesson to the AI Engineering from Scratch Curriculum Including Frontmatter Requirements](/rohitg00/ai-engineering-from-scratch/how-to-add-new-lesson-with-frontmatter) Learn to add a new lesson to the AI Engineering from Scratch curriculum. Follow steps for scaffolding, frontmatter, code, and quizzes, then integrate your content easily. - Tags: how-to-guide - Published: 2026-06-05 ### [Allowed and Banned Dependencies in AI Engineering From Scratch: Language-Specific Guide](/rohitg00/ai-engineering-from-scratch/allowed-and-banned-dependencies-for-lesson-code) Understand allowed and banned dependencies for AI Engineering From Scratch projects. Discover the strict stdlib-first policy and language-specific allow-lists to ensure compliant code. - Tags: best-practices - Published: 2026-06-05 ### [How the Build It / Use It Teaching Methodology Works in ai-engineering-from-scratch](/rohitg00/ai-engineering-from-scratch/how-does-build-it-use-it-teaching-methodology-work) Discover the Build It Use It methodology in ai-engineering-from-scratch. Learn algorithms from scratch then redeploy with production libraries to demystify abstraction layers. - Tags: teaching-methodology - Published: 2026-06-05 ### [Programming Languages Used for Multi-Language Implementation in AI Engineering From Scratch](/rohitg00/ai-engineering-from-scratch/multi-language-implementation-languages-used) Explore the programming languages used in AI Engineering From Scratch: Python, TypeScript, Rust, and Julia. Discover multi-language implementation strategies for robust AI development. - Tags: deep-dive - Published: 2026-06-04 ### [MIT License Terms and Forking Guidelines for AI Engineering from Scratch](/rohitg00/ai-engineering-from-scratch/mit-license-forking.md-terms-reuse) Understand MIT License terms and FORKING.md guidelines for the AI Engineering from Scratch repository. Learn about unrestricted use, modification, and distribution for your projects. - Tags: licensing-and-contribution - Published: 2026-06-04 ### [Invariant Validation Checks and Rules in audit_lessons.py: Complete Guide to the Curriculum Auditor](/rohitg00/ai-engineering-from-scratch/audit_lessons.py-invariant-validation-checks-rules) Master invariant validation checks including L001–L010 rules in audit_lessons.py. Ensure lesson directory structure, docs, code, and quiz schema integrity for the AI Engineering curriculum. - Tags: how-to-guide - Published: 2026-06-04 ### [How to Evaluate the Effectiveness of the AI Engineering Approach: Automated Validation and Artifact Verification](/rohitg00/ai-engineering-from-scratch/how-to-evaluate-the-effectiveness-of-the-ai-engineering-approach) Evaluate AI engineering effectiveness with automated validation, artifact verification, and CI audits. Inspect outputs and test pass rates to measure success. - Tags: how-to-guide - Published: 2026-06-03 ### [What Are the Benefits of Building AI from Scratch? A Complete Guide](/rohitg00/ai-engineering-from-scratch/what-are-the-benefits-of-building-ai-from-scratch) Discover the powerful benefits of building AI from scratch. Gain deep understanding, master debugging. and create over 500 portable artifacts beyond black-box frameworks. Explore AI engineering from scratch. - Tags: how-to-guide - Published: 2026-06-03 ### [Security Considerations for MCP Server Implementations: 10 Critical Hardening Strategies](/rohitg00/ai-engineering-from-scratch/what-are-the-security-considerations-for-mcp-server-implementations) Learn essential MCP server security considerations. Discover 10 critical hardening strategies to protect your implementations from unauthorized access and data leaks. - Tags: best-practices - Published: 2026-05-21 ### [How the A2A Protocol Works for Multi-Agent Communication: HTTP-Based Discovery and Task Execution](/rohitg00/ai-engineering-from-scratch/how-does-the-a2a-protocol-work-for-multi-agent-communication) Learn how the A2A protocol facilitates multi-agent communication using HTTP for discovery, task submission, and artifact retrieval. Explore agent communication. - Tags: deep-dive - Published: 2026-05-21 ### [How to Build Production-Ready LLM Applications with Guardrails: A Layered Architecture Guide](/rohitg00/ai-engineering-from-scratch/how-to-build-production-ready-llm-applications-with-guardrails) Build production-ready LLM applications with robust guardrails. Discover a layered architecture for safety, reliability, and compliance before user exposure. - Tags: architecture - Published: 2026-05-21 ### [Multimodal AI Architectures Explained: CLIP and LLaVA Implementations from Scratch](/rohitg00/ai-engineering-from-scratch/what-are-the-different-multimodal-ai-architectures-clip-llava) Explore multimodal AI architectures like CLIP and LLaVA. Learn how CLIP builds joint embeddings and LLaVA integrates vision into LLMs. Implement these foundational models from scratch. - Tags: deep-dive - Published: 2026-05-21 ### [How Stable Diffusion Generates Images: Architecture Explained](/rohitg00/ai-engineering-from-scratch/what-is-the-architecture-behind-stable-diffusion-image-generation) Discover the Stable Diffusion architecture, from VAE to U-Net, and understand how it transforms text prompts into stunning images by denoising latent space. - Tags: architecture - Published: 2026-05-21 ### [DPO vs RLHF: How Direct Preference Optimization Compares to Reinforcement Learning from Human Feedback](/rohitg00/ai-engineering-from-scratch/how-does-dpo-compare-to-rlhf-for-preference-optimization) Compare DPO vs RLHF for preference optimization. Discover how Direct Preference Optimization simplifies alignment with a stable supervised loop, while RLHF captures complex nuances in a multi-stage process. - Tags: deep-dive - Published: 2026-05-21 ### [How to Debug Neural Network Training Issues and Gradient Problems: A Systematic Guide](/rohitg00/ai-engineering-from-scratch/how-to-debug-neural-network-training-issues-and-gradient-problems) Debug neural network training issues like vanishing gradients and loss divergence systematically. Learn to use hooks for efficient pathology detection without altering your training loop. - Tags: how-to-guide - Published: 2026-05-21 ### [Transformer Positional Encoding Methods: Sinusoidal, RoPE, and ALiBi Explained with Code](/rohitg00/ai-engineering-from-scratch/what-are-the-different-transformer-positional-encoding-methods-rope-alibi) Explore transformer positional encoding methods like sinusoidal, RoPE, and ALiBi. Understand how these techniques inject sequence order into token representations for better transformer understanding. Code included. - Tags: deep-dive - Published: 2026-05-21 ### [How to Implement Agent Memory and Planning Patterns in Python](/rohitg00/ai-engineering-from-scratch/how-to-implement-agent-memory-and-planning-patterns) Unlock sophisticated AI capabilities by implementing agent memory and planning patterns in Python. Explore virtual-context systems, HTN decomposition, LLM fallbacks, and evolutionary search. - Tags: how-to-guide - Published: 2026-05-21 ### [Best Practices for LLM Fine-Tuning with LoRA and QLoRA: A Complete Guide](/rohitg00/ai-engineering-from-scratch/what-are-the-best-practices-for-llm-fine-tuning-with-lora-and-qlora) Master LLM fine-tuning with LoRA and QLoRA. Learn best practices to reduce memory usage by 75% while preserving model quality. Explore this complete guide now. - Tags: best-practices - Published: 2026-05-21 ### [How to Build a RAG Pipeline with Embeddings and Vector Databases: A Production‑Ready Guide](/rohitg00/ai-engineering-from-scratch/how-to-build-a-rag-pipeline-with-embeddings-and-vector-databases) Build a production-ready RAG pipeline. Learn to use embeddings vector databases like pgvector, document chunking, and hybrid retrieval for LLM context. - Tags: how-to-guide - Published: 2026-05-21 ### [What Is the Model Context Protocol (MCP) and How to Build MCP Servers](/rohitg00/ai-engineering-from-scratch/what-is-the-model-context-protocol-and-how-to-build-mcp-servers) Understand the Model Context Protocol MCP a standard for LLM assistants to safely interact with external tools via handshake, OAuth 2.1, and Streamable HTTP. Learn to build MCP servers. - Tags: how-to-guide - Published: 2026-05-21 ### [How RLHF Works for LLM Alignment and Preference Optimization: A Three-Stage Technical Guide](/rohitg00/ai-engineering-from-scratch/how-does-rlhf-work-for-llm-alignment-and-preference-optimization) Learn how RLHF aligns LLMs using SFT, reward modeling, and PPO. This technical guide details the three-stage process for preference optimization, drawing from the ai-engineering-from-scratch repository. - Tags: deep-dive - Published: 2026-05-21 ### [How to Build an Agent Loop from Scratch in Python: A Complete ReAct Implementation](/rohitg00/ai-engineering-from-scratch/how-to-build-an-agent-loop-from-scratch-in-python) Build a production-ready ReAct agent loop from scratch in Python. Combine message history, tool registry, and turn-based control for robust AI applications. - Tags: how-to-guide - Published: 2026-05-21 ### [Architectural Differences Between GPT and BERT Models: Decoder-Only vs Encoder-Only Transformers](/rohitg00/ai-engineering-from-scratch/what-are-the-architectural-differences-between-gpt-and-bert-models) Understand the core architectural differences between GPT decoder-only and BERT encoder-only Transformer models. Explore their unique approaches to natural language processing. - Tags: architecture - Published: 2026-05-21 ### [How to Implement Self-Attention Mechanism from Scratch: A NumPy-Only Guide](/rohitg00/ai-engineering-from-scratch/how-to-implement-self-attention-mechanism-from-scratch) Learn to implement the self-attention mechanism from scratch using only NumPy. Understand scaled dot-product attention with Query, Key, and Value matrices for AI engineering without frameworks. - Tags: how-to-guide - Published: 2026-05-21 ### [How Backpropagation Works from Scratch in Neural Networks: A Complete Implementation Guide](/rohitg00/ai-engineering-from-scratch/how-does-backpropagation-work-from-scratch-in-neural-networks) Implement backpropagation from scratch in neural networks. Build an autograd engine, construct a computational graph, and traverse it to learn gradients and update parameters. Full guide available. - Tags: deep-dive - Published: 2026-05-21