·AI & ChatGPT
Module 2 Lesson 5: System vs User Prompts
Understanding the difference between high-level architectural instructions and immediate conversational queries.
architecture
42 articles
·AI Agents and LLMs
From APIs to Platforms: The New AI Stack
The AI tech stack is moving beyond the OpenAI API. Explore the layers of the modern AI platform: vector stores, orchestration, and specialized deployment.
·AI Security
Module 15 Lesson 2: NeMo Guardrails
The programmable barrier. Learn about NVIDIA's NeMo Guardrails architecture and how to define 'Colang' flows to control AI dialog.
·AI Security
Module 17 Lesson 4: AI Security Proxies
The intelligent firewall. Learn how to use Middleware and Proxies (like LiteLLM, Portkey) to centralize security, logging, and access control for all your AI models.
·AI Security
Module 22 Lesson 2: AI Security Capstone
Put it all together. Design a complete security architecture for a hypothetical enterprise AI application, from supply chain to guardrails.
·DevOps
Module 10 Lesson 3: DNS and Service Discovery
Stop using IP addresses. Master Docker's internal DNS system to allow your containers to find and talk to each other using simple human-readable names.
·DevOps
Module 12 Lesson 1: What is Orchestration?
From one to a thousand. Learn the core concepts of container orchestration: why it's needed for high availability, self-healing, and automated scaling.
·DevOps
Module 12 Lesson 4: Introduction to Kubernetes
Meet the industry standard. Discover the architecture of Kubernetes, the difference between Pods and Containers, and why it is the OS of the modern cloud.
·DevOps
Module 14 Lesson 4: Project: Multi-Service Architecture
The microservices puzzle. Learn how to orchestrate a complex system with a Gateway, separate Services for Auth and Data, and a shared Message Queue.
·DevOps
Module 15 Lesson 1: Capstone Project: Enterprise System
The ultimate challenge. Apply every skill you've learned to design and build a secure, scalable, and automated multi-tier architecture for a fictional global company.
·DevOps
Module 5 Lesson 5: Real-World Multi-Container Example
The capstone of the basics. Build a complete Voting App architecture with a Python worker, a Redis queue, a Postgres DB, and a Node.js results page.
·DevOps
Module 9 Lesson 1: Volume Drivers and Types
Master the data layer of Docker. Explore the different volume drivers and types, and learn how to choose the right storage strategy for your application's data.
·DevOps
Module 10 Lesson 2: Modular Pipeline Design
Divide and conquer. Learn the architectural patterns of splitting your pipeline into independent, testable modules that are easy for different teams to maintain.
·DevOps
Capstone Part 1: Architecture and Planning
The big picture. Define the requirements, architecture, and technology stack for your final Enterprise CI/CD project: 'GlobalHealth Connect'.
·DevOps
Module 2 Lesson 1: GitLab Runners
The muscle behind the code. Learn how GitLab Runners execute your jobs, and the critical difference between using GitLab's cloud runners and hosting your own.
·DevOps
Module 4 Lesson 5: Optimizing for Large Clusters
Handle the scale. Learn how to optimize GitLab CI/CD for environments with hundreds of runners, thousands of developers, and massive data throughput.
·Automation
Capstone Part 1: Architecture & Requirements
The Blueprint. Plan your final n8n project: 'Nexus-One', an automated business assistant that handles leads, customer support, and social media reporting.
·AWS Bedrock
Module 10 Lesson 1: What are Bedrock Agents?
The Autonomous Brain. Understanding how Bedrock Agents use reasoning to solve multi-step problems.
·AWS Bedrock
Module 18 Lesson 1: Introducing AgentCore
The Enterprise Orchestrator. Understanding why AgentCore exists and how it brings deterministic control to AI workflows.
·AWS Bedrock
Module 18 Lesson 2: AgentCore vs Basic Agents
Choosing the Right Tool. Comparing the strengths of autonomous Bedrock Agents and controlled AgentCore workflows.
·AWS Bedrock
Module 19 Lesson 1: AgentCore Nodes and Flow
The Blueprint. Understanding how AgentCore uses 'Nodes' and 'Edges' to create complex, manageable AI graphs.
·AWS Bedrock
Module 19 Wrap-up: Mapping the Logic
Hands-on: Design a multi-node AgentCore graph that includes AI reasoning and data validation.
·AWS Bedrock
Module 7 Lesson 1: What is a Knowledge Base?
Foundations of RAG. Why Knowledge Bases are the secret to building AI that 'knows' your private business data.
·Generative AI
Module 2 Lesson 3: The Transformer Architecture
Attention Mechanisms and Context. Understanding the 'Secret Sauce' that allows AI to reason across long documents.
·Generative AI
Module 5 Lesson 1: Retrieval-Augmented Generation (RAG)
Connecting AI to Reality. How to ground AI responses in your own private data to prevent hallucinations.
·LangChain
Module 7 Lesson 1: Why RAG Matters
Fighting Hallucinations. Understanding the architectural pattern of grounding AI responses in factual, retrieved context.
·Agentic AI
Module 1 Lesson 2: Agents vs Chatbots
Defining the boundary. Why adding a 'Search' tool to a chatbot doesn't make it an agent.
·Agentic AI
Module 11 Lesson 5: Mixing Frameworks
The Hybrid Approach. How to combine LangGraph's control with CrewAI's collaboration for the ultimate system.
·Agentic AI
Module 11 Wrap-up: The Strategic Selection
Hands-on: Use a decision matrix to select the right framework for three real-world business scenarios.
·Agentic AI
Module 14 Lesson 1: The Reliability Gap
Why LLMs aren't enough. Understanding the limit of probabilistic reasoning in deterministic business systems.
·Agentic AI
Module 2 Lesson 1: Agent Components
Dissecting the agent. Understanding the four pillars: LLM, Memory, Tools, and the Control Loop.
·Agentic AI
Module 5 Lesson 5: Why Control Flow Matters
From magic to structure. Why giving an agent too much freedom is a recipes for disaster.
·Agentic AI
Module 6 Lesson 1: Why LangGraph Exists
The successor to the Loop. Understanding the need for cyclic graphs in agent development.
·Agentic AI
Module 6 Lesson 2: Graph-Based Agent Architecture
Designing the flowchart of intelligence. Understanding nodes, edges, and state transitions.
·Agentic AI
Module 9 Lesson 1: What StrandAgents Are
The lightweight alternative. Understanding the event-driven, streaming-first architecture of StrandAgents.
·Agentic AI
Module 9 Lesson 3: Stateless vs Stateful Agents
Choosing your memory model. When to build agents that remember the past vs agents that treat every event as new.
·AI & LLMs
Module 1 Lesson 2: Local vs Cloud-Based Models
A deep dive comparison between local LLMs and cloud-based giants like GPT-4. When to stay local and when to go to the cloud.
·AI & LLMs
Module 10 Lesson 1: Why RAG Is Important for Local Models
Fixing the memory problem. How Retrieval-Augmented Generation gives local AI a 'library' to consult.
·AI & LLMs
Module 10 Lesson 5: Retrieval Pipelines
Connecting the dots. How a user's question travels through the vector store and back to the LLM.
·AI & LLMs
Module 2 Lesson 2: Ollama Architecture
How Ollama works under the hood. Understanding the service, the CLI, and the llama.cpp engine.
·AI & LLMs
Module 5 Lesson 5: Model Inheritance
Standing on the shoulders of giants. How to create layers of custom models using the FROM command.
·AI & LLMs
Module 6 Lesson 3: Supported Architectures
Not all models are equal. Understanding which architectures (Llama, Mistral, BERT) work with the Ollama engine.