Guided Courses
Tracks
Learn it in order
Building RAG Systems
Ground language models in your own knowledge — retrieval, reranking, evaluation, and production, end to end.
Tokenization, Inside and Out
BPE, WordPiece, Unigram, SentencePiece, tiktoken — every algorithm, every tradeoff, every production implication.
Attention Mechanisms, from First Principles
Self-attention, multi-head, KV cache, MQA, GQA, MLA, FlashAttention — the complete mechanism that makes transformers work.
The Transformer Architecture
From 'Attention Is All You Need' to GPT-4 and Llama 3 — every layer, every design choice, every scaling decision.
Prompt Engineering and Context Design
System prompts, structured outputs, chain-of-thought, and the context engineering patterns that make LLMs reliable in production.
Vector Databases, Inside and Out
Algorithms, architecture, and operations — from HNSW internals to production at scale.
AI Agents in Production
From the agent loop to multi-agent systems — LangGraph, MCP, tool calling, memory, and the guardrails that make agents safe to ship.
LLM Evaluation and Testing
Golden datasets, LLM-as-a-judge, regression testing, and CI/CD gates — the engineering discipline that separates demos from products.
LLM Fine-Tuning for Production
LoRA, QLoRA, dataset engineering, and the decision framework for when fine-tuning is the right answer — and when it isn't.
LLMOps: Serving and Operating LLMs
Model serving, inference optimization, guardrails, observability, and cost control — the engineering that keeps LLM systems running.
Loop Engineering and Agent Harnesses
Harness design, context management, subagent orchestration, evaluation-as-steering, and the Claude Agent SDK — the infrastructure layer that makes agents reliable.
Autonomous and Headless Agents
Durable execution with Temporal, event-driven triggers, sandbox isolation, crash recovery, and the governance framework for agents that run without human oversight.
Self-Improving AI Systems
Automated prompt optimization, log-driven harness patching, principle extraction, memory-driven evolution, and the governance framework for systems that modify themselves.
Compound AI Systems
Multi-model routing, cascading, the classifier-generator-verifier triad, AI gateways, protocol composition, and the systems engineering that turns models into products.
About Nybble™
The AI space moves fast.
Nybble™ is how you keep up — and stay sharp.
What happened. In two minutes.
The AI news cycle moves at a pace no one can keep up with. Snack distills what launched, what shipped, and what matters — every day, without the filler.
Go to SnackThe concepts behind the headlines.
News tells you what. Stack tells you why and how. From RAG architectures to agentic evals, these are the ideas that will shape what you build next.
Go to StackProve you actually get it.
Reading about LangChain is not the same as knowing it. Hack challenges you with production-grade questions, then shows you the references that make the answer stick.
Go to Hack