Content Changelog#
All notable changes to learning content (lessons, exercises, assessments) are documented here.
Categories: Added for new content, Changed for updates, Removed for deletions.
Unreleased#
Changed#
Merged the Reference section into Learning. The former
reference/section is gone; every topic now lives insidelearning/alongside the tiered tracks:AI cheatsheets under
learning/ai/cheatsheets/(prompt-engineering,llm-api-cheatsheet,embeddings-and-vector-search)AI introduction at
learning/ai/introductionand review materials underlearning/ai/reviews/Software engineering cheatsheets under
learning/software-engineering/cheatsheets/(git, SQL, API security, testing, containers, architecture, microservices vs serverless)Cloud cheatsheets under
learning/cloud-and-infrastructure/cheatsheets/(AWS core, Kubernetes, CI/CD, ML services)Former 4-file topic format (index/documentation/practice/question) collapsed to single pages with
## Practiceand## Review QuestionsH2 sections for easier search and bookmarking
Three overlap pairs merged into single pages instead of cross-linked duplicates:
learning/ai/advanced/evaluation-metrics— RAGAS narrative theory + Python API + practice + review questionslearning/cloud-and-infrastructure/advanced/redis-caching— strategies + RAG/LLM caching patterns + practice + review questionslearning/cloud-and-infrastructure/advanced/observability— LGTM narrative + PromQL/LogQL patterns + Grafana tips + practice + review questions
Translated the Vietnamese frontend practice page to English and moved it to
learning/software-engineering/appendix/frontend-practiceSidebar no longer shows a “References” section; the “Learning” entry now contains cheatsheets as siblings of the tiered tracks
Added Cloudflare
_redirectsfor all formerreference/*URLs so existing bookmarks continue to work
2026-04-10#
Added#
8 new quick-reference topic directories (each with index, documentation, practice, and question files) — all later merged into
learning/during the 2026-04-10 reference-into-learning merge:AI cheatsheets:
prompt-engineering,llm-api-cheatsheet,embeddings-and-vector-search; RAGAS API content merged intolearning/ai/advanced/evaluation-metricsCloud & Infrastructure cheatsheets:
aws-core-services,kubernetes-quick-reference,ci-cd-patterns; observability cheatsheet content merged intolearning/cloud-and-infrastructure/advanced/observability
Full teaching content for
learning/cloud-and-infrastructure/advanced/observability(three pillars, LGTM stack, RED/USE methods, SLOs and burn-rate alerts)Full teaching content for
learning/cloud-and-infrastructure/advanced/redis-caching(strategies, invalidation, stampede mitigation, operational notes)
Changed#
Migrated all
learning/ai/content to LangChain 1.x canonical APIs:create_agentfromlangchain.agents,init_chat_modelfromlangchain.chat_models, messages fromlangchain.messages(no longerlangchain_core.messages),InMemorySaver(wasMemorySaver),workflow.add_edge(START, ...)(wasset_entry_point)Refreshed model references across AI content to current frontier models: Claude Opus 4.6, Claude Sonnet 4.6, Claude Haiku 4.5, GPT-5.2, Gemini 3 (previously GPT-4, Claude 2/3)
Updated
training/ai/assignment prerequisites to Python 3.11+ and LangChain 1.x dependency specs across 18 files; replaced deprecatedTavilySearchResultsfromlangchain_communitywithTavilySearchfromlangchain-tavilyRewrote
llmops-observability.mdLangFuse integration from deprecatedLLMChainto modern LCEL (prompt | llm); updated LangSmith env vars to canonicalLANGSMITH_*namesRewrote
applied/tool-calling.mdOpenAI section from legacyopenai.ChatCompletion.create()v0 SDK (withfunctions=) to modernclient.chat.completions.create()with the unifiedtools=parameterRefreshed glossary (LLM, Chain, Agent, Context Window entries) to reflect LangChain 1.x and 2026 model landscape
Filled missing
{doc}refs intraining/ai/integration/knowledge/(added agentic-patterns, graph-rag) andtraining/cloud-and-infrastructure/applied/knowledge/(added aws-services)Bumped Python prerequisite from 3.9+/3.10+ to 3.11+ in glossary,
training/ai/overview.md, slide-deck, and 18 training assignment files
2026-04-03#
Added#
Context Engineering lesson — context window anatomy, token budgeting, write vs. read context, dynamic assembly, caching, grounding patterns
Harness Engineering lesson — eval harness architecture, dataset curation, deterministic and LLM-as-judge metrics, regression testing, CI/CD integration
Context Engineering training materials: practice assignment and quiz
Harness Engineering training materials: practice assignment and quiz
Intro paragraphs to 15 lesson pages for better previews and SEO
Section descriptions on all Learning, Training, and Resources index pages
Changed#
Restructured all three domains into 4-tier progression: foundations → applied → advanced → integration
Renamed “Learn” section to “Learning” site-wide
Organized Cloud reference guides by functional domain
Moved greenlets lesson to foundations, advanced-indexing training to core-techniques
Normalized page titles for consistency across all sections
Replaced 62 diagram images with Mermaid code blocks across 28 files
Resolved all markdownlint issues: added code block languages, image alt text, and heading fixes across 52 files
2026-03-22#
Added#
Glossary with 70+ terms across 7 domains
Contributor profiles and presentation decks in Resources
Changed#
Reorganized all content into Learning / Training / Resources structure (the initial Learn / Training / Reference / Resources split was later consolidated by merging Reference back into Learning)
AI lessons moved to Learning > AI (foundations, core techniques, advanced)
Software Engineering lessons moved to Learning > Software Engineering
Cloud & Infrastructure lessons moved to Learning > Cloud & Infrastructure
All quizzes, assignments, and exams moved to Training sections
Blog articles converted to quick-lookup cheatsheets (later moved under each domain’s
cheatsheets/subdir)Added SEO meta descriptions to main pages
2026-03-03#
Added#
AI Fundamentals training module — knowledge checks, practice assignments, and final exam
RAG Optimization training module — hybrid search, query transformation, post-retrieval quizzes and project
LLMOps & Evaluation training module — experiment comparison, observability quizzes and project
LangGraph & Agentic AI training module — agentic patterns, human-in-the-loop, multi-agent quizzes and project
DevOps Essentials training module — containerization quiz, CI/CD assignment, and final exam
Cloud Essentials training module — AWS services quiz and final exam
Microservices Architecture training module — API gateway, async communication, saga pattern project
2026-02-09#
Added#
Advanced indexing techniques lesson (semantic chunking, HNSW)
Syllabi for all 7 fresher training modules
Quiz and exam materials for AI Fundamentals and AI Advanced tracks
Changed#
Updated RAG evaluation metrics documentation with new images
2026-02-03#
Added#
AWS cloud services overview
Azure ML services overview
LLM evaluation and FastAPI monolith lessons
Changed#
Expanded Docker documentation with fundamentals, optimization, and multi-stage builds
Enhanced Git and Docker Compose docs with security and best practices
Improved testing methodologies coverage (white box, black box)
2026-01-26#
Added#
Fresher training program structure with 7 modules
AI Fundamentals knowledge base (generative AI, RAG theory, modern RAG architecture, LangChain, building RAG agents)
2026-01-17#
Added#
Agentic AI roadmap and patterns
Git Collaboration Workflow article
API security, JWT authentication, and Redis caching articles
AI introductory blog post (AI, Generative AI, LLMs, RAG overview)
Changed#
Updated Docker and Compose docs with uv and BuildKit best practices
Updated CI/CD workflows documentation
Updated Git references with Pro Git and GitHub Skills courses
Revised observability and experiment comparison content
2026-01-08#
Added#
Initial documentation site with blog-style content
Software Engineering articles: Git collaboration, database design, API security, caching strategies, testing methodologies, Docker best practices, microservices vs serverless, CI/CD pipelines, and design patterns
AI module 1 (RAG foundations) and module 2 (RAG implementation)