AI & LLMs
Generative AI & LLM Engineering
LLMs, RAG, agents, transformers, vector DBs, prompt engineering, MLOps.
This is the TechLeague pillar page for AI & LLMs: 64 hand-curated guides, blueprints and roadmaps, grouped by sub-topic so you can go from zero to production fast. Start anywhere — every article is independent and links back to its cluster.
Latest articles
Fundamentals10
Attention mechanism explained
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Context window engineering and long-context tricks
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Embeddings explained: from word2vec to LLMs
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Knowledge distillation for smaller models
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM fundamentals for engineers
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Model Context Protocol (MCP) deep dive
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Mixture of Experts (MoE) explained
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Quantization techniques: GPTQ, AWQ, GGUF, FP8
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Tokenization: BPE vs SentencePiece vs Tiktoken
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Transformer architecture deep dive
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →RAG & Agents12
Advanced RAG: hybrid search, reranking, HyDE, GraphRAG
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI agents for NetOps: practical patterns
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI agents for SecOps: SOC copilots
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI storage for training: parallel filesystems
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →DSPy: programming, not prompting
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Fine-tuning vs RAG vs prompting: when to use what
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Function calling and tool use across providers
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LangChain vs LlamaIndex in 2026
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM agents architecture: ReAct, planning, tools
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Pydantic AI overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →RAG architecture patterns that actually work
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Microsoft Semantic Kernel overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLMOps & Tooling8
AI cost optimization: tokens, GPUs, caching
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →llama.cpp deep dive: GGUF, quantization
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM evaluation: lm-eval, MMLU, HELM, RAGAS
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM observability with LangSmith, Langfuse, Arize
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLMOps vs MLOps: what changes
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →MLOps pipeline design
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Model serving with vLLM and TGI
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Ollama and running LLMs locally
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Safety & Governance8
AI red teaming techniques
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →EU AI Act for engineers
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →ISO/IEC 42001 AI management system
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM guardrails and safety
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →NIST AI Risk Management Framework overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →OWASP LLM Top 10: practical defenses
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Prompt injection defense: OWASP LLM Top 10
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Responsible AI overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Foundation models12
Anthropic Claude family overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Copilot-style coding assistants compared
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →DeepSeek and the open Chinese LLM wave
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Google Gemini family overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Meta Llama family overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Mistral models overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Multimodal LLMs: vision, audio, video
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →OpenAI GPT-5 family overview
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Speech-to-text: Whisper and beyond
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Text-to-image models: SDXL, Flux, DALL-E
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Text-to-speech: ElevenLabs, OpenAI TTS, Bark
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Text-to-video models in 2026: Sora, Veo, Kling
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI data center design fundamentals
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI Engineer roadmap 2026
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LLM evals with Promptfoo and Inspect
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →AI power and cooling design 2026
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Vector search tuning at scale
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Chain of thought and reasoning models
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →GPU cluster networking: RDMA, RoCEv2, InfiniBand
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →LoRA, QLoRA and PEFT: efficient fine-tuning
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →NCCL collectives explained for network engineers
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Prompt engineering in 2026: what still matters
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →RLHF, DPO and preference tuning
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →RoCEv2 vs InfiniBand for AI fabrics
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Synthetic data for ML training
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →Vector databases overview: pgvector, Pinecone, Milvus, Qdrant, Weaviate
Practical, blueprint-driven walk-through with design choices, pitfalls and a fast learning path.
Read article →TechLeague Challenges
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Open the challenge arena →FAQ
- Where should I start with AI & LLMs?
- Open the "Certifications" or "Fundamentals" cluster above and read top-down — every guide is self-contained.
- Are these guides updated for 2026?
- Yes. Every post on this page is dated 2026 and follows current vendor blueprints.
- Do I need a lab to follow them?
- Recommended. Most guides include lab suggestions; for AI & LLMs a free trial or sandbox is usually enough.