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@@ -0,0 +1,973 @@
+{
+  "Py9nst2FDJ1_hoXeX_qSF": {
+    "title": "Introduction",
+    "description": "Docker is an open-source platform that automates application deployment, scaling, and management using lightweight, portable containers. Containers are standalone executable units containing all necessary dependencies, libraries, and configuration files for consistent application execution across various environments.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker",
+        "url": "https://www.docker.com/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Docs",
+        "url": "https://docs.docker.com/",
+        "type": "article"
+      }
+    ]
+  },
+  "74JxgfJ_1qmVNZ_QRp9Ne": {
+    "title": "What are Containers?",
+    "description": "Containers are lightweight, portable, and isolated software environments that package applications with their dependencies for consistent execution across different platforms. They streamline development, deployment, and management while ensuring applications run reliably regardless of underlying infrastructure.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Introduction to Containers - AWS Skill Builder",
+        "url": "https://explore.skillbuilder.aws/learn/course/106/introduction-to-containers",
+        "type": "course"
+      },
+      {
+        "title": "What is a Container?",
+        "url": "https://www.docker.com/resources/what-container/",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about Containers",
+        "url": "https://app.daily.dev/tags/containers?ref=roadmapsh",
+        "type": "article"
+      }
+    ]
+  },
+  "i4ijY3T5gLgNz0XqRipXe": {
+    "title": "Why do we need Containers?",
+    "description": "Containers solve environment inconsistency issues when working in teams by standardizing runtime environments. Before containers, significant time was lost configuring local environments to run projects shared by teammates, leading to \"works on my machine\" problems.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Need for Containers",
+        "url": "https://www.redhat.com/en/topics/containers",
+        "type": "article"
+      }
+    ]
+  },
+  "3hatcMVLDbMuz73uTx-9P": {
+    "title": "Bare Metal vs VMs vs Containers",
+    "description": "Bare metal runs applications directly on hardware with maximum performance but limited flexibility. VMs use hypervisors to run multiple OS instances with strong isolation but higher overhead. Containers share the host OS kernel, providing lightweight isolation with better resource efficiency than VMs while maintaining portability.\n\nYou can learn more from the following resources:",
+    "links": [
+      {
+        "title": "History of Virtualization",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/01-history-and-motivation/03-history-of-virtualization",
+        "type": "article"
+      },
+      {
+        "title": "Bare Metal Machine",
+        "url": "https://glossary.cncf.io/bare-metal-machine/",
+        "type": "article"
+      },
+      {
+        "title": "What is a Virtual Machine?",
+        "url": "https://azure.microsoft.com/en-au/resources/cloud-computing-dictionary/what-is-a-virtual-machine",
+        "type": "article"
+      }
+    ]
+  },
+  "43drPbTwPqJQPyzwYUdBT": {
+    "title": "Docker and OCI",
+    "description": "The Open Container Initiative (OCI) is a Linux Foundation project which aims at creating industry standards for container formats and runtimes. Its primary goal is to ensure the compatibility and interoperability of container environments through defined technical specifications.\n\nYou can learn more from the following resources:",
+    "links": [
+      {
+        "title": "Open Container Initiative",
+        "url": "https://opencontainers.org/",
+        "type": "article"
+      },
+      {
+        "title": "OCI - Wikipedia",
+        "url": "https://en.wikipedia.org/wiki/Open_Container_Initiative",
+        "type": "article"
+      }
+    ]
+  },
+  "mw-weCutd2ECKlx2DE_ZJ": {
+    "title": "Package Managers",
+    "description": "",
+    "links": []
+  },
+  "uKjB2qntFTpPuYUT9sdxd": {
+    "title": "Users / Groups Permissions",
+    "description": "",
+    "links": []
+  },
+  "W5kX5jn49hghRgkEw6_S3": {
+    "title": "Shell Commands",
+    "description": "",
+    "links": []
+  },
+  "InlMtuaUJ9EXO-OD9x1jj": {
+    "title": "Shell Scripting",
+    "description": "",
+    "links": []
+  },
+  "XxT9UUjbKW1ARyERSLH_W": {
+    "title": "Programming Languages",
+    "description": "",
+    "links": []
+  },
+  "EqYWfBL5l5OOquok_OvOW": {
+    "title": "Application Architecture",
+    "description": "Application architecture in containerized environments focuses on designing applications to leverage containerization benefits. This includes microservices patterns, service decomposition, inter-service communication, data persistence strategies, and designing for scalability and fault tolerance in distributed systems.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Microservices Architecture",
+        "url": "https://microservices.io/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Application Design Patterns",
+        "url": "https://docs.docker.com/get-started/docker-concepts/building-images/",
+        "type": "article"
+      },
+      {
+        "title": "Container Design Patterns",
+        "url": "https://kubernetes.io/blog/2016/06/container-design-patterns/",
+        "type": "article"
+      },
+      {
+        "title": "Twelve-Factor App Methodology",
+        "url": "https://12factor.net/",
+        "type": "article"
+      },
+      {
+        "title": "Microservices vs Monolith Architecture",
+        "url": "https://www.youtube.com/watch?v=GBTdnfD6s5Q",
+        "type": "video"
+      }
+    ]
+  },
+  "jrH1qE6EnFXL4fTyYU8gR": {
+    "title": "Underlying Technologies",
+    "description": "Docker containers use Linux kernel technologies for isolation and resource management: namespaces for process isolation, cgroups for resource limits, and union filesystems for efficient layered storage. These enable lightweight, portable, and secure containers that share the host kernel.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Underlying Technologies",
+        "url": "https://www.docker.com/resources/what-container/#underlying-technologies",
+        "type": "article"
+      },
+      {
+        "title": "Underlying Technologies - Medium",
+        "url": "https://medium.com/@furkan.turkal/how-does-docker-actually-work-the-hard-way-a-technical-deep-diving-c5b8ea2f0422",
+        "type": "article"
+      }
+    ]
+  },
+  "BvV8VCX39wRB-g8WvGF1g": {
+    "title": "Namespaces",
+    "description": "Docker namespaces are a Linux kernel feature that creates isolated environments for containers by providing separate instances of global system resources. Docker uses PID, NET, MNT, UTS, IPC, and USER namespaces to ensure each container believes it has its own unique resources, enabling lightweight, portable, and secure containerization.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Namespaces",
+        "url": "https://docs.docker.com/engine/security/userns-remap/",
+        "type": "article"
+      },
+      {
+        "title": "Linux Namespaces",
+        "url": "https://man7.org/linux/man-pages/man7/namespaces.7.html",
+        "type": "article"
+      }
+    ]
+  },
+  "fRl4EfNwlBiidzn3IV34-": {
+    "title": "cgroups",
+    "description": "cgroups (control groups) are Linux kernel features that limit and manage system resources like CPU, memory, and I/O for process groups. Docker uses cgroups to enforce resource constraints on containers, ensuring predictable performance and preventing containers from consuming excessive system resources.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Control Groups",
+        "url": "https://www.docker.com/resources/what-container/#control-groups",
+        "type": "article"
+      },
+      {
+        "title": "Control Groups - Medium",
+        "url": "https://medium.com/@furkan.turkal/how-does-docker-actually-work-the-hard-way-a-technical-deep-diving-c5b8ea2f0422",
+        "type": "article"
+      },
+      {
+        "title": "An introduction to cgroups, runc & containerD",
+        "url": "https://www.youtube.com/watch?v=u1LeMndEk70",
+        "type": "video"
+      }
+    ]
+  },
+  "vEUfw_vobshuZI0-q8RZo": {
+    "title": "Union Filesystems",
+    "description": "Union filesystems (UnionFS) create virtual, layered file structures by overlaying multiple directories without modifying originals. Docker uses this to manage storage efficiently by minimizing duplication and reducing image sizes through layered filesystem approach that keeps directory contents separate while mounted together.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "AUFS (Advanced Multi-Layered Unification Filesystem)",
+        "url": "http://aufs.sourceforge.net/",
+        "type": "article"
+      },
+      {
+        "title": "OverlayFS (Overlay Filesystem)",
+        "url": "https://www.kernel.org/doc/html/latest/filesystems/overlayfs.html",
+        "type": "article"
+      },
+      {
+        "title": "Btrfs (B-Tree Filesystem)",
+        "url": "https://btrfs.readthedocs.io/en/stable/",
+        "type": "article"
+      },
+      {
+        "title": "ZFS (Z File System)",
+        "url": "https://zfsonlinux.org/",
+        "type": "article"
+      }
+    ]
+  },
+  "01nDXqxVdMv4SeXc0nYHH": {
+    "title": "Installation / Setup",
+    "description": "Docker provides Docker Desktop, a desktop application that simplifies installation and setup with GUI capabilities. Alternatively, you can install Docker Engine for command-line only functionality without graphical interface components.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Desktop website",
+        "url": "https://www.docker.com/products/docker-desktop",
+        "type": "article"
+      },
+      {
+        "title": "Docker Engine",
+        "url": "https://docs.docker.com/engine/install/",
+        "type": "article"
+      }
+    ]
+  },
+  "NCdsPRhJy7UtQFNLo1J1f": {
+    "title": "Docker Desktop (Win/Mac/Linux)",
+    "description": "Docker Desktop is a comprehensive development environment for Windows, macOS, and Linux with a GUI. It includes Docker Engine, CLI, Buildx, Extensions, Compose, Kubernetes, and credentials helper, providing everything needed for container development on desktop platforms.\n\nLearn more from the following resources:",
+    "links": [
+      {
+        "title": "Docker Desktop Documentation",
+        "url": "https://docs.docker.com/desktop/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Get Started Guide",
+        "url": "https://docs.docker.com/get-started/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Hub",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about Docker",
+        "url": "https://app.daily.dev/tags/docker?ref=roadmapsh",
+        "type": "article"
+      }
+    ]
+  },
+  "0NKqLUWtJMlXn-m6wpA6f": {
+    "title": "Docker Engine ( Linux )",
+    "description": "Docker Engine is the core open-source containerization runtime that creates and manages containers, builds images, and provides the Docker API. It runs on Linux, Windows, and macOS, serving as the foundation for Docker Desktop and standalone Docker installations on servers.\n\nFor more information about docker engine see:",
+    "links": [
+      {
+        "title": "Docker Engine Installation Guide",
+        "url": "https://docs.docker.com/engine/install/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Engine - Docker Documentation",
+        "url": "https://docs.docker.com/engine/",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about Docker",
+        "url": "https://app.daily.dev/tags/docker?ref=roadmapsh",
+        "type": "article"
+      },
+      {
+        "title": "Docker Engine for Linux Servers Setup and Tips",
+        "url": "https://www.youtube.com/watch?v=YeF7ObTnDwc",
+        "type": "video"
+      }
+    ]
+  },
+  "kIqx7Inf50mE9W0juwNBz": {
+    "title": "Basics of Docker",
+    "description": "Docker is a platform that simplifies building, packaging, and deploying applications in lightweight, portable containers. Key components include Dockerfiles (build instructions), Images (snapshots), and Containers (running instances). Essential commands cover pulling images, building from Dockerfiles, running containers with port mapping, and managing both containers and images.\n\nWhat is a Container?\n--------------------\n\nA container is a lightweight, standalone, and executable software package that includes all the dependencies (libraries, binaries, and configuration files) required to run an application. Containers isolate applications from their environment, ensuring they work consistently across different systems.\n\nDocker Components\n-----------------\n\nThere are three key components in the Docker ecosystem:\n\n*   **Dockerfile**: A text file containing instructions (commands) to build a Docker image.\n*   **Docker Image**: A snapshot of a container, created from a Dockerfile. Images are stored in a registry, like Docker Hub, and can be pulled or pushed to the registry.\n*   **Docker Container**: A running instance of a Docker image.\n\nDocker Commands\n---------------\n\nBelow are some essential Docker commands you'll use frequently:\n\n*   `docker pull <image>`: Download an image from a registry, like Docker Hub.\n*   `docker build -t <image_name> <path>`: Build an image from a Dockerfile, where `<path>` is the directory containing the Dockerfile.\n*   `docker image ls`: List all images available on your local machine.\n*   `docker run -d -p <host_port>:<container_port> --name <container_name> <image>`: Run a container from an image, mapping host ports to container ports.\n*   `docker container ls`: List all running containers.\n*   `docker container stop <container>`: Stop a running container.\n*   `docker container rm <container>`: Remove a stopped container.\n*   `docker image rm <image>`: Remove an image from your local machine.",
+    "links": []
+  },
+  "uUPYXmwu27SBPqKZx6U_q": {
+    "title": "Data Persistence",
+    "description": "Docker enables you to run containers that are isolated pieces of code, including applications and their dependencies, separated from the host operating system. Containers are ephemeral by default, which means any data stored in the container will be lost once it is terminated. To overcome this problem and retain data across container lifecycle, Docker provides various data persistence methods.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Data Persistence - Docker Documentation",
+        "url": "https://docs.docker.com/get-started/docker-concepts/running-containers/persisting-container-data/",
+        "type": "article"
+      }
+    ]
+  },
+  "086zZYjtzdCaDHm-MkSqg": {
+    "title": "Ephemeral Container Filesystem",
+    "description": "By default, the storage within a Docker container is ephemeral, meaning that any data changes or modifications made inside a container will only persist until the container is stopped and removed. Once the container is stopped and removed, all the associated data will be lost. This is because Docker containers are designed to be stateless by nature. This temporary or short-lived storage is called the \"ephemeral container file system\". It is an essential feature of Docker, as it enables fast and consistent deployment of applications across different environments without worrying about the state of a container.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Data Persistence - Docker Documentation",
+        "url": "https://docs.docker.com/get-started/docker-concepts/running-containers/persisting-container-data/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Concepts - Persisting container data",
+        "url": "https://www.youtube.com/watch?v=10_2BjqB_Ls",
+        "type": "video"
+      }
+    ]
+  },
+  "woemCQmWTR-hIoWAci3d5": {
+    "title": "Volume Mounts",
+    "description": "Volume mounts are a way to map a folder or file on the host system to a folder or file inside a container. This allows the data to persist outside the container even when the container is removed. Additionally, multiple containers can share the same volume, making data sharing between containers easy.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Volumes",
+        "url": "https://docs.docker.com/storage/volumes/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Volume Flags",
+        "url": "https://docs.docker.com/storage/bind-mounts/#choose-the--v-or---mount-flag",
+        "type": "article"
+      },
+      {
+        "title": "Docker Volumes explained in 6 minutes",
+        "url": "https://www.youtube.com/watch?v=p2PH_YPCsis",
+        "type": "video"
+      }
+    ]
+  },
+  "wZcCW1ojGzUakHCv2AaI1": {
+    "title": "Bind Mounts",
+    "description": "Bind mounts have limited functionality compared to volumes. When you use a bind mount, a file or directory on the host machine is mounted into a container. The file or directory is referenced by its absolute path on the host machine. By contrast, when you use a volume, a new directory is created within Docker's storage directory on the host machine, and Docker manages that directory's contents.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Bind Mounts",
+        "url": "https://docs.docker.com/storage/bind-mounts/",
+        "type": "article"
+      }
+    ]
+  },
+  "LShK3-1EGGuXnEvdScFR7": {
+    "title": "Using 3rd Party Container Images",
+    "description": "Third-party images are pre-built Docker container images that are available on Docker Hub or other container registries. These images are created and maintained by individuals or organizations and can be used as a starting point for your containerized applications.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Hub Registry",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      }
+    ]
+  },
+  "jKSE_wKYf4P9wnSh_LkMi": {
+    "title": "Databases",
+    "description": "Running your database in a Docker container can help streamline your development process and ease deployment. Docker Hub provides numerous pre-made images for popular databases such as MySQL, PostgreSQL, and MongoDB.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Containerized Databases",
+        "url": "https://docs.docker.com/guides/use-case/databases/",
+        "type": "article"
+      },
+      {
+        "title": "How to Setup MySQL Database with Docker",
+        "url": "https://www.youtube.com/watch?v=igc2zsOKPJs",
+        "type": "video"
+      }
+    ]
+  },
+  "HlTxLqKNFMhghtKF6AcWu": {
+    "title": "Interactive Test Environments",
+    "description": "Docker allows you to create isolated, disposable environments that can be deleted once you're done with testing. This makes it much easier to work with third party software, test different dependencies or versions, and quickly experiment without the risk of damaging your local setup.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Launch a Dev Environment",
+        "url": "https://docs.docker.com/desktop/dev-environments/create-dev-env/",
+        "type": "article"
+      },
+      {
+        "title": "Test Environments - Medium",
+        "url": "https://manishsaini74.medium.com/containerized-testing-orchestrating-test-environments-with-docker-5201bfadfdf2",
+        "type": "article"
+      }
+    ]
+  },
+  "YzpB7rgSR4ueQRLa0bRWa": {
+    "title": "Command Line Utilities",
+    "description": "Docker images can include command line utilities or standalone applications that we can run inside containers.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Images",
+        "url": "https://docs.docker.com/engine/reference/commandline/images/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Run",
+        "url": "https://docs.docker.com/reference/cli/docker/container/run/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Pull",
+        "url": "https://docs.docker.com/engine/reference/commandline/pull/",
+        "type": "article"
+      }
+    ]
+  },
+  "5OEfBQaYNOCi999x6QUqW": {
+    "title": "Building Container Images",
+    "description": "Container images are executable packages that include everything required to run an application: code, runtime, system tools, libraries, and settings. By building custom images, you can deploy applications seamlessly with all their dependencies on any Docker-supported platform. The key component in building a container image is the `Dockerfile`. It is essentially a script containing instructions on how to assemble a Docker image. Each instruction in the Dockerfile creates a new layer in the image, making it easier to track changes and minimize the image size. Here's a simple example of a Dockerfile:\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Dockerfile Examples",
+        "url": "https://github.com/dockersamples",
+        "type": "opensource"
+      },
+      {
+        "title": "Docker Image Builder",
+        "url": "https://docs.docker.com/reference/cli/docker/buildx/build/",
+        "type": "article"
+      },
+      {
+        "title": "Dockerfile Reference",
+        "url": "https://docs.docker.com/engine/reference/builder/",
+        "type": "article"
+      }
+    ]
+  },
+  "yGRQcx64S-yBGEoOeMc55": {
+    "title": "Dockerfiles",
+    "description": "A Dockerfile is a text document that contains a list of instructions used by the Docker engine to build an image. Each instruction in the Dockerfile adds a new layer to the image. Docker will build the image based on these instructions, and then you can run containers from the image.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Dockerfile Examples",
+        "url": "https://github.com/dockersamples",
+        "type": "opensource"
+      },
+      {
+        "title": "Dockerfile Reference",
+        "url": "https://docs.docker.com/engine/reference/builder/",
+        "type": "article"
+      },
+      {
+        "title": "Dockerfile Best Practices",
+        "url": "https://docs.docker.com/develop/develop-images/dockerfile_best-practices/",
+        "type": "article"
+      }
+    ]
+  },
+  "frshJqVMP8D7o_7tMZMPI": {
+    "title": "Efficient Layer Caching",
+    "description": "When building container images, Docker caches the newly created layers. These layers can then be used later on when building other images, reducing the build time and minimizing bandwidth usage. However, to make the most of this caching mechanism, you should be aware of how to efficiently use layer caching. Docker creates a new layer for each instruction (e.g., `RUN`, `COPY`, `ADD`, etc.) in the Dockerfile. If the instruction hasn't changed since the last build, Docker will reuse the existing layer.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Layer Caching",
+        "url": "https://docs.docker.com/build/cache/",
+        "type": "article"
+      },
+      {
+        "title": "Layer Caching",
+        "url": "https://www.youtube.com/watch?v=_nMpndIyaBU",
+        "type": "video"
+      }
+    ]
+  },
+  "-8wAzF6_3gruiM3VYMvB0": {
+    "title": "Image Size and Security",
+    "description": "Reducing Docker image size is crucial for optimizing storage, transfer speeds, and deployment times. Key strategies include using minimal base images like Alpine Linux, leveraging multi-stage builds to exclude unnecessary build tools, removing unnecessary files and packages, and minimizing the number of layers by combining commands.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Multi-stage builds",
+        "url": "https://docs.docker.com/build/building/multi-stage/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Best Practices",
+        "url": "https://docs.docker.com/develop/develop-images/dockerfile_best-practices/",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about Security",
+        "url": "https://app.daily.dev/tags/security?ref=roadmapsh",
+        "type": "article"
+      }
+    ]
+  },
+  "3VKPiMfbGBxv9m_SljIQV": {
+    "title": "Container Registries",
+    "description": "A Container Registry is a centralized storage and distribution system for Docker container images. It allows developers to easily share and deploy applications in the form of these images. Container registries play a crucial role in the deployment of containerized applications, as they provide a fast, reliable, and secure way to distribute container images across various production environments.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Registry",
+        "url": "https://docs.docker.com/registry/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Hub",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      },
+      {
+        "title": "Artifact Registry",
+        "url": "https://cloud.google.com/artifact-registry",
+        "type": "article"
+      },
+      {
+        "title": "Amazon ECR",
+        "url": "https://aws.amazon.com/ecr/",
+        "type": "article"
+      },
+      {
+        "title": "Azure Container Registry",
+        "url": "https://azure.microsoft.com/en-in/products/container-registry",
+        "type": "article"
+      }
+    ]
+  },
+  "rxVR62_yXIjc-L4GFSV6u": {
+    "title": "Dockerhub",
+    "description": "Docker Hub is a cloud-based registry service that serves as the primary public repository for Docker container images. It allows users to store, share, and distribute Docker images, offering both free public repositories and paid private ones and integrates seamlessly with Docker CLI, enabling easy pushing and pulling of images. It features official images maintained by software vendors, automated builds linked to source code repositories, and webhooks for triggering actions based on repository events.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "DockerHub",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      },
+      {
+        "title": "DockerHub Repositories",
+        "url": "https://docs.docker.com/docker-hub/repos/",
+        "type": "article"
+      },
+      {
+        "title": "DockerHub Webhooks",
+        "url": "https://docs.docker.com/docker-hub/webhooks/",
+        "type": "article"
+      }
+    ]
+  },
+  "Vs4WQwgJFhA63U9Gf2ym0": {
+    "title": "Image Tagging Best Practices",
+    "description": "Docker image tagging best practices center on creating clear, consistent, and informative labels. Adopt semantic versioning for releases, avoid the ambiguous \"latest\" tag in production, and include relevant metadata like build dates or Git commit hashes. Implement a strategy distinguishing between environments, use descriptive tags for variants, and automate tagging in CI/CD pipelines. Regularly clean up old tags and document your conventions to maintain clarity and facilitate team-wide adoption. These practices ensure efficient image management and improve collaboration across your organization.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Tags",
+        "url": "https://docs.docker.com/get-started/docker-concepts/building-images/build-tag-and-publish-an-image/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Image Tagging Best Practices",
+        "url": "https://medium.com/@nirmalkushwah08/docker-image-tagging-strategy-4aa886fb4fcc",
+        "type": "article"
+      },
+      {
+        "title": "Semantic Versioning",
+        "url": "https://semver.org/",
+        "type": "article"
+      }
+    ]
+  },
+  "fh5aERX7c-lY9FPsmftoF": {
+    "title": "Others (ghcr, ecr, gcr, acr, etc)",
+    "description": "Container images can be stored in many different registries, not just Dockerhub. Most major cloud platforms now provide container registries such as \"Artifact Registry\" on Google Cloud Platform, Elastic Container Registry on AWS and Azure Container Registry on Microsoft Azure. GitHub also provides it's own registry which is useful when container builds are included in your GitHub Actions workflow.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "DockerHub",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      },
+      {
+        "title": "Artifact Registry",
+        "url": "https://cloud.google.com/artifact-registry",
+        "type": "article"
+      },
+      {
+        "title": "Amazon ECR",
+        "url": "https://aws.amazon.com/ecr/",
+        "type": "article"
+      },
+      {
+        "title": "Azure Container Registry",
+        "url": "https://azure.microsoft.com/en-in/products/container-registry",
+        "type": "article"
+      },
+      {
+        "title": "GitHub Container Registry",
+        "url": "https://docs.github.com/en/packages/guides/about-github-container-registry",
+        "type": "article"
+      }
+    ]
+  },
+  "z2eeBXPzo-diQ67Fcfyhc": {
+    "title": "Running Containers",
+    "description": "The `docker run` command creates and starts containers from images in one step. It combines `docker create` and `docker start` operations, allowing you to execute applications in isolated environments with various configuration options like port mapping, volumes, and environment variables.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Run",
+        "url": "https://docs.docker.com/engine/reference/commandline/run/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Containers",
+        "url": "https://docs.docker.com/engine/reference/commandline/container/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Exec",
+        "url": "https://docs.docker.com/engine/reference/commandline/exec/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Stop",
+        "url": "https://docs.docker.com/engine/reference/commandline/stop/",
+        "type": "article"
+      }
+    ]
+  },
+  "6eu5NRA1sJuaHTlHtNurc": {
+    "title": "docker run",
+    "description": "The `docker run` command creates and starts a new container from a specified image. It combines `docker create` and `docker start` operations, offering a range of options to customize the container's runtime environment. Users can set environment variables, map ports and volumes, define network connections, and specify resource limits. The command supports detached mode for background execution, interactive mode for shell access, and the ability to override the default command defined in the image. Common flags include `-d` for detached mode, `-p` for port mapping, `-v` for volume mounting, and `--name` for assigning a custom container name. Understanding `docker run` is fundamental to effectively deploying and managing Docker containers.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Run",
+        "url": "https://docs.docker.com/engine/reference/commandline/run/",
+        "type": "article"
+      }
+    ]
+  },
+  "jjA9E0J8N2frfeJCNtA1m": {
+    "title": "docker compose",
+    "description": "Docker Compose is a tool for defining and running multi-container applications using a YAML file (`docker-compose.yml`). It describes application services, networks, and volumes, enabling you to create, manage, and run entire containerized applications with single commands for simplified orchestration.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Curated Docker Compose Samples",
+        "url": "https://github.com/docker/awesome-compose?tab=readme-ov-file",
+        "type": "opensource"
+      },
+      {
+        "title": "Docker Compose documentation",
+        "url": "https://docs.docker.com/compose/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Compose Tutorial",
+        "url": "https://www.youtube.com/watch?v=DM65_JyGxCo",
+        "type": "video"
+      }
+    ]
+  },
+  "mAaEz-bwB5DLaBbOSYGMn": {
+    "title": "Runtime Configuration Options",
+    "description": "Docker runtime configuration options give you powerful control over your containers' environments. By tweaking resource limits, network settings, security profiles, and logging drivers, you can optimize performance and enhance security. You'll also find options for setting environment variables, mounting volumes, and overriding default behaviors – all crucial for tailoring containers to your specific needs. For more advanced users, there are tools to adjust kernel capabilities and set restart policies. Whether you're using command-line flags or Docker Compose files, these options help ensure your containers run smoothly and consistently, no matter where they're deployed.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Documentation",
+        "url": "https://docs.docker.com/engine/reference/run/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Runtime Arguments",
+        "url": "https://galea.medium.com/docker-runtime-arguments-604593479f45",
+        "type": "article"
+      }
+    ]
+  },
+  "78YFahP3Fg-c27reLkuK4": {
+    "title": "Container Security",
+    "description": "Container security encompasses a broad set of practices and tools aimed at protecting containerized applications from development through deployment and runtime. It involves securing the container image, ensuring that only trusted and non-vulnerable code is used, implementing strong access controls for container environments, and configuring containers to follow the principle of least privilege. Additionally, it includes monitoring for unexpected behavior, protecting communication between containers, and maintaining the host environment’s security. Effective container security integrates seamlessly into DevSecOps workflows to provide continuous visibility and protection across the container lifecycle without disrupting development speed or agility.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Security",
+        "url": "https://docs.docker.com/engine/security/",
+        "type": "article"
+      },
+      {
+        "title": "Kubernetes Security Best Practices",
+        "url": "https://www.aquasec.com/cloud-native-academy/kubernetes-in-production/kubernetes-security-best-practices-10-steps-to-securing-k8s/",
+        "type": "article"
+      }
+    ]
+  },
+  "vYug8kcwrMoWf8ft4UDNI": {
+    "title": "Runtime Security",
+    "description": "Runtime security in Docker focuses on ensuring the safety and integrity of containers during their execution, safeguarding against vulnerabilities and malicious activities that could arise while the containerized application is running. This involves monitoring container behavior for anomalies, implementing access controls to limit permissions, and employing tools to detect and respond to suspicious activity in real time. Effective runtime security also ensures that only verified images are deployed and continuously audits the system to maintain compliance, thereby providing a robust defense layer to prevent exploits and maintain the desired security posture throughout the container lifecycle.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Security",
+        "url": "https://docs.docker.com/engine/security/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Security Best Practices",
+        "url": "https://docs.docker.com/build/building/best-practices/",
+        "type": "article"
+      }
+    ]
+  },
+  "M5UG-ZcyhBPbksZd0ZdNt": {
+    "title": "Image Security",
+    "description": "Image security is a crucial aspect of deploying Docker containers in your environment. Ensuring the images you use are secure, up to date, and free of vulnerabilities is essential. In this section, we will review best practices and tools for securing and managing your Docker images. When pulling images from public repositories, always use trusted, official images as a starting point for your containerized applications. Official images are vetted by Docker and are regularly updated with security fixes. You can find these images on the Docker Hub or other trusted registries.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Content Trust",
+        "url": "https://docs.docker.com/engine/security/trust/content_trust/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Hub",
+        "url": "https://hub.docker.com/",
+        "type": "article"
+      }
+    ]
+  },
+  "b-LwyYiegbF0jIrn7HYRv": {
+    "title": "Docker CLI",
+    "description": "The Docker Command Line Interface (CLI) is a powerful tool used to interact with the Docker engine, enabling developers and operators to build, manage, and troubleshoot containers and related resources. With a wide range of commands, the Docker CLI provides control over all aspects of Docker, including creating and managing containers (`docker run`, `docker stop`), building images (`docker build`), managing networks (`docker network`), handling storage (`docker volume`), and inspecting system status (`docker ps`, `docker info`). Its intuitive syntax and flexibility allow users to automate complex workflows, streamline development processes, and maintain containerized applications with ease, making it a foundational utility for Docker management and orchestration.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker CLI",
+        "url": "https://docs.docker.com/reference/cli/docker/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Compose",
+        "url": "https://docs.docker.com/compose/",
+        "type": "article"
+      }
+    ]
+  },
+  "3Nsg-F3wMKEzEsXw1MBZv": {
+    "title": "Images",
+    "description": "Docker images are lightweight, standalone packages containing everything needed to run software: application code, runtime, libraries, and system tools. Built in layers for efficient storage, they serve as blueprints for containers and can be shared through registries like Docker Hub for consistent deployment across environments.\n\nLearn more from the following resources:",
+    "links": [
+      {
+        "title": "What's the Difference Between Docker Images and Containers?",
+        "url": "https://aws.amazon.com/compare/the-difference-between-docker-images-and-containers/",
+        "type": "article"
+      },
+      {
+        "title": "What is an image?",
+        "url": "https://www.youtube.com/watch?v=NyvT9REqLe4",
+        "type": "video"
+      }
+    ]
+  },
+  "jhwe-xfVc-C7qy8YuS5dZ": {
+    "title": "Containers",
+    "description": "Containers are isolated, lightweight environments that run applications using a shared operating system kernel, ensuring consistency and portability across different computing environments. They encapsulate everything needed to run an application, such as code, dependencies, and configurations, making it easy to move and run the containerized application anywhere. Using the Docker CLI, you can create, start, stop, and manage containers with commands like `docker run`, `docker ps` to list running containers, `docker stop` to halt them, and `docker exec` to interact with them in real time. The CLI provides a powerful interface for developers to build, control, and debug containers effortlessly, allowing for streamlined development and operational workflows.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker CLI Commands",
+        "url": "https://docs.docker.com/engine/reference/commandline/cli/",
+        "type": "article"
+      },
+      {
+        "title": "Docker CLI Commands Cheat Sheet",
+        "url": "https://docs.docker.com/get-started/docker_cheatsheet.pdf",
+        "type": "article"
+      }
+    ]
+  },
+  "eHtVLB6v3h7hatJb-9cZK": {
+    "title": "Volumes",
+    "description": "Docker volumes are persistent storage solutions used to manage and store data outside the container's filesystem, ensuring data remains intact even if the container is deleted or recreated. They are ideal for storing application data, logs, and configuration files that need to persist across container restarts and updates. With the Docker CLI, you can create and manage volumes using commands like `docker volume create` to define a new volume, `docker volume ls` to list all volumes, and `docker run -v` to mount a volume to a specific container. This approach helps maintain data integrity, simplifies backup processes, and supports data sharing between containers, making volumes a core part of stateful containerized applications.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Volumes",
+        "url": "https://docs.docker.com/storage/volumes/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Volume Commands",
+        "url": "https://docs.docker.com/engine/reference/commandline/volume/",
+        "type": "article"
+      }
+    ]
+  },
+  "w5QjzvOaciK2rotOkjvjQ": {
+    "title": "Networks",
+    "description": "Docker networks enable containers to communicate with each other and with external systems, providing the necessary connectivity for microservices architectures. By default, Docker offers several network types such as bridge, host, and overlay, each suited for different use cases like isolated environments, high-performance scenarios, or multi-host communication. Using the Docker CLI, you can create, inspect, and manage networks with commands like `docker network create` to define custom networks, `docker network ls` to list existing networks, and `docker network connect` to attach a container to a network. This flexibility allows developers to control how containers interact, ensuring secure and efficient communication across distributed applications.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Networks",
+        "url": "https://docs.docker.com/network/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Network Commands",
+        "url": "https://docs.docker.com/engine/reference/commandline/network/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Networking",
+        "url": "https://www.youtube.com/watch?v=bKFMS5C4CG0",
+        "type": "video"
+      }
+    ]
+  },
+  "hHXTth0ZP8O-iMGR9xfu9": {
+    "title": "Developer Experience",
+    "description": "Docker significantly enhances the developer experience by providing a consistent, isolated environment for building, testing, and running applications, eliminating the “it works on my machine” problem. With Docker, developers can package their applications and dependencies into portable containers, ensuring consistency across different environments, from local development to staging and production. The simplified setup and reproducibility of environments accelerate onboarding, minimize conflicts, and allow developers to focus on coding rather than troubleshooting configurations. Moreover, tools like Docker Compose enable quick orchestration of complex multi-container applications, making it easier to prototype, iterate, and collaborate, ultimately streamlining the entire development lifecycle.\n\nFor more details and practical examples:",
+    "links": [
+      {
+        "title": "Developer Experience Wishlist - Docker",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/11-development-workflow/00-devx-wishlist#key-devx-features",
+        "type": "article"
+      },
+      {
+        "title": "Docker Developer Experience",
+        "url": "https://www.docker.com/blog/cto-chat-overcoming-the-developer-experience-gap-feat-redmonk-flow-io/",
+        "type": "article"
+      }
+    ]
+  },
+  "4p5d3rzCHy4vjg2PRX-2k": {
+    "title": "Hot Reloading",
+    "description": "Even though we can speed up the image building with layer caching enable, we don't want to have to rebuild our container image with every code change. Instead, we want the state of our application in the container to reflect changes immediately. We can achieve this through a combination of bind mounts and hot reloading utilities!\n\nHave a look at the following resources for sample implementations:",
+    "links": [
+      {
+        "title": "Hot Reloading - Docker",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/11-development-workflow/01-hot-reloading",
+        "type": "article"
+      }
+    ]
+  },
+  "LiAV9crrTHhLqeZhD25a2": {
+    "title": "Debuggers",
+    "description": "In order to make developing with containers competitive with developing locally, we need the ability to run and attach to debuggers inside the container.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Buildx Debug",
+        "url": "https://docs.docker.com/reference/cli/docker/buildx/debug/",
+        "type": "article"
+      },
+      {
+        "title": "Debuggers in Docker",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/11-development-workflow/02-debug-and-test",
+        "type": "article"
+      }
+    ]
+  },
+  "Kmyo1_Mor9WHLkRhNShRZ": {
+    "title": "Tests",
+    "description": "We want to run tests in an environment as similar as possible to production, so it only makes sense to do so inside of our containers! This can include unit tests, integration tests, and end-to-end tests, all run within Docker containers to simulate real-world scenarios while avoiding interference from external dependencies. Using Docker CLI and tools like Docker Compose, you can create isolated testing environments, run tests in parallel, and spin up and tear down the necessary infrastructure automatically.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Running Tests - Docker",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/11-development-workflow/03-tests",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about Testing",
+        "url": "https://app.daily.dev/tags/testing?ref=roadmapsh",
+        "type": "article"
+      }
+    ]
+  },
+  "oyqw4tr-taZcxt5kREh1g": {
+    "title": "Continuous Integration",
+    "description": "Continuous integration is the idea of executing some actions (for example build, test, etc...) automatically as you push code to your version control system.\n\nFor containers, there are a number of things we may want to do:\n\n*   Build the container images\n*   Execute tests\n*   Scan container images for vulnerabilities\n*   Tag images with useful metadata\n*   Push to a container registry\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Continuous Integration - Docker",
+        "url": "https://courses.devopsdirective.com/docker-beginner-to-pro/lessons/11-development-workflow/04-continuous-integration-github-actions",
+        "type": "article"
+      },
+      {
+        "title": "Explore top posts about CI/CD",
+        "url": "https://app.daily.dev/tags/cicd?ref=roadmapsh",
+        "type": "article"
+      }
+    ]
+  },
+  "qXOGqORi3EdqwsP9Uhi9m": {
+    "title": "Deploying Containers",
+    "description": "Deploying containers is a crucial step in using Docker and containerization to manage applications more efficiently, easily scale, and ensure consistent performance across environments. This topic will give you an overview of how to deploy Docker containers to create and run your applications.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Deployment",
+        "url": "https://docs.docker.com/get-started/deployment/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Compose",
+        "url": "https://docs.docker.com/compose/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Swarm",
+        "url": "https://docs.docker.com/engine/swarm/",
+        "type": "article"
+      }
+    ]
+  },
+  "PP_RRBo_pThe2mgf6xzMP": {
+    "title": "PaaS Options",
+    "description": "Platform-as-a-Service (PaaS) options for deploying containers provide a simplified and managed environment where developers can build, deploy, and scale containerized applications without worrying about the underlying infrastructure. Popular PaaS offerings include Google Cloud Run, Azure App Service, AWS Elastic Beanstalk, and Heroku, which abstract away container orchestration complexities while offering automated scaling, easy integration with CI/CD pipelines, and monitoring capabilities. These platforms support rapid development and deployment by allowing teams to focus on application logic rather than server management, providing a seamless way to run containers in production with minimal operational overhead.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "PaaS Options for Deploying Containers",
+        "url": "https://www.docker.com/resources/what-container/#paas-options",
+        "type": "article"
+      },
+      {
+        "title": "Azure Container Instances",
+        "url": "https://azure.microsoft.com/en-us/services/container-instances/",
+        "type": "article"
+      },
+      {
+        "title": "Google Cloud Run",
+        "url": "https://cloud.google.com/run",
+        "type": "article"
+      },
+      {
+        "title": "IBM Cloud Code Engine",
+        "url": "https://www.ibm.com/cloud/code-engine",
+        "type": "article"
+      },
+      {
+        "title": "Amazon Elastic Container Service",
+        "url": "https://aws.amazon.com/ecs/",
+        "type": "article"
+      }
+    ]
+  },
+  "RqXpX2XabtHYVjgg1EZR_": {
+    "title": "Kubernetes",
+    "description": "Kubernetes is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. It provides a robust framework for handling complex container workloads by organizing containers into logical units called pods, managing service discovery, load balancing, and scaling through declarative configurations. Kubernetes enables teams to deploy containers across clusters of machines, ensuring high availability and fault tolerance through self-healing capabilities like automatic restarts, replacements, and rollback mechanisms. With its extensive ecosystem and flexibility, Kubernetes has become the de facto standard for running large-scale, distributed applications, simplifying operations and improving the reliability of containerized workloads.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Kubernetes",
+        "url": "https://kubernetes.io/",
+        "type": "article"
+      },
+      {
+        "title": "Docker Swarm",
+        "url": "https://docs.docker.com/engine/swarm/",
+        "type": "article"
+      }
+    ]
+  },
+  "r1eJZDZYouUjnGwAtRbyU": {
+    "title": "Nomad",
+    "description": "Nomad is a cluster manager and scheduler that enables you to deploy, manage and scale your containerized applications. It automatically handles node failures, resource allocation, and container orchestration. Nomad supports running Docker containers as well as other container runtime(s) and non-containerized applications.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Nomad Documentation",
+        "url": "https://www.nomadproject.io/docs",
+        "type": "article"
+      }
+    ]
+  },
+  "ks6PFN-0Z9zH7gtWaWgxz": {
+    "title": "Docker Swarm",
+    "description": "Docker Swarm is Docker’s native container orchestration tool that allows users to deploy, manage, and scale containers across a cluster of Docker hosts. By transforming a group of Docker nodes into a single, unified cluster, Swarm provides high availability, load balancing, and automated container scheduling using simple declarative commands. With features like service discovery, rolling updates, and integrated security through TLS encryption, Docker Swarm offers an approachable alternative to more complex orchestrators like Kubernetes. Its tight integration with the Docker CLI and ease of setup make it a suitable choice for small to medium-sized deployments where simplicity and straightforward management are priorities.\n\nVisit the following resources to learn more:",
+    "links": [
+      {
+        "title": "Docker Swarm",
+        "url": "https://docs.docker.com/engine/swarm/",
+        "type": "article"
+      }
+    ]
+  }
+}
\ No newline at end of file
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index 3476c39d4..b69eec40f 100644
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+++ b/public/roadmap-content/prompt-engineering.json
@@ -1,232 +1,232 @@
 {
   "jrH1qE6EnFXL4fTyYU8gR": {
     "title": "Introduction",
-    "description": "",
+    "description": "Prompt engineering is the practice of designing effective inputs for Large Language Models to achieve desired outputs. This roadmap covers fundamental concepts, core techniques, model parameters, and advanced methods. It's a universal skill accessible to anyone, requiring no programming background, yet crucial for unlocking AI potential across diverse applications and domains.",
     "links": []
   },
   "74JxgfJ_1qmVNZ_QRp9Ne": {
     "title": "LLMs and how they work?",
-    "description": "",
+    "description": "LLMs function as sophisticated prediction engines that process text sequentially, predicting the next token based on relationships between previous tokens and patterns from training data. They don't predict single tokens directly but generate probability distributions over possible next tokens, which are then sampled using parameters like temperature and top-K. The model repeatedly adds predicted tokens to the sequence, building responses iteratively. This token-by-token prediction process, combined with massive training datasets, enables LLMs to generate coherent, contextually relevant text across diverse applications and domains.",
     "links": []
   },
   "i4ijY3T5gLgNz0XqRipXe": {
     "title": "What is a Prompt?",
-    "description": "",
+    "description": "A prompt is an input provided to a Large Language Model (LLM) to generate a response or prediction. It serves as the instruction or context that guides the AI model's output generation process. Effective prompts are clear, specific, well-structured, and goal-oriented, directly affecting the accuracy and relevance of AI responses.",
     "links": []
   },
   "43drPbTwPqJQPyzwYUdBT": {
     "title": "What is Prompt Engineering?",
-    "description": "",
+    "description": "Prompt engineering is the practice of crafting effective input text to guide AI language models toward desired outputs. It involves designing prompts that communicate intent clearly to get accurate, relevant responses. This iterative process requires understanding how LLMs work as prediction engines and using techniques to optimize their performance for specific tasks.",
     "links": []
   },
   "Yb5cQiV2ETxPbBYCLOpt2": {
     "title": "OpenAI",
-    "description": "",
+    "description": "OpenAI developed influential language models including GPT-3, GPT-4, and ChatGPT, setting industry standards for prompt engineering practices. Their API provides access to powerful LLMs with configurable parameters like temperature and max tokens. Many prompt engineering techniques and best practices originated from working with OpenAI systems.",
     "links": []
   },
   "o-6UKLZ6oCRbAKgRjH2uI": {
     "title": "Google",
-    "description": "",
+    "description": "Google develops influential LLMs including Gemini, PaLM, and Bard. Through Vertex AI and Google Cloud Platform, they provide enterprise-grade model access with extensive prompt testing via Vertex AI Studio. Google's research has advanced many prompt engineering techniques, including Chain of Thought reasoning methods.",
     "links": []
   },
   "V8pDOwrRKKcHBTd4qlSsH": {
     "title": "Anthropic",
-    "description": "",
+    "description": "Anthropic created Claude, a family of large language models known for safety features and constitutional AI training. Claude models excel at following instructions, maintaining context, and avoiding harmful outputs. Their strong instruction-following capabilities and built-in safety measures make them valuable for reliable, ethical AI applications.",
     "links": []
   },
   "Td2YzDFT4LPGDw8JMmQSQ": {
     "title": "Meta",
-    "description": "",
+    "description": "Meta (formerly Facebook) develops the Llama family of open-source large language models. Llama models are available for research and commercial use, offering strong performance across various tasks. For prompt engineering, Meta's models provide transparency in training data and architecture, allowing developers to fine-tune and customize prompts for specific applications without vendor lock-in.",
     "links": []
   },
   "3wshuH7_DXgbhxsLzzI4D": {
     "title": "xAI",
-    "description": "",
+    "description": "xAI is Elon Musk's AI company that created Grok, a conversational AI model trained on web data with a focus on real-time information and humor. Grok aims to be more truthful and less politically correct than other models. For prompt engineering, xAI offers unique capabilities in accessing current events and generating responses with a distinctive conversational style.",
     "links": []
   },
   "pamV5Z8DRKk2ioZbg6QVK": {
     "title": "LLM",
-    "description": "",
+    "description": "Large Language Models (LLMs) are AI systems trained on vast text data to understand and generate human-like language. They work as prediction engines, analyzing input and predicting the next most likely token. LLMs perform tasks like text generation, translation, summarization, and Q&A. Understanding token processing is key to effective prompt engineering.",
     "links": []
   },
   "NPcaSEteeEA5g22wQ7nL_": {
     "title": "Tokens",
-    "description": "",
+    "description": "Tokens are fundamental units of text that LLMs process, created by breaking down text into smaller components like words, subwords, or characters. Understanding tokens is crucial because models predict the next token in sequences, API costs are based on token count, and models have maximum token limits for input and output.",
     "links": []
   },
   "b-Xtkv6rt8QgzJXSShOX-": {
     "title": "Context Window",
-    "description": "",
+    "description": "Context window refers to the maximum number of tokens an LLM can process in a single interaction, including both input prompt and generated output. When exceeded, older parts are truncated. Understanding this constraint is crucial for prompt engineering—you must balance providing sufficient context with staying within token limits.",
     "links": []
   },
   "SWDa3Su3VS815WQbvvNsa": {
     "title": "Hallucination",
-    "description": "",
+    "description": "Hallucination in LLMs refers to generating plausible-sounding but factually incorrect or fabricated information. This occurs when models fill knowledge gaps or present uncertain information with apparent certainty. Mitigation techniques include requesting sources, asking for confidence levels, providing context, and always verifying critical information independently.",
     "links": []
   },
   "yfsjW1eze8mWT0iHxv078": {
     "title": "Model Weights / Parameters",
-    "description": "",
+    "description": "Model weights and parameters are the learned values that define an LLM's behavior and knowledge. Parameters are the trainable variables adjusted during training, while weights represent their final values. Understanding parameter count helps gauge model capabilities - larger models typically have more parameters and better performance but require more computational resources.",
     "links": []
   },
   "Ke5GT163k_ek9SzbcbBGE": {
     "title": "Fine-Tuning vs Prompt Engg.",
-    "description": "",
+    "description": "Fine-tuning trains models on specific data to specialize behavior, while prompt engineering achieves customization through input design without model modification. Prompt engineering is faster, cheaper, and more accessible. Fine-tuning offers deeper customization but requires significant resources and expertise.",
     "links": []
   },
   "gxydtFKmnXNY9I5kpTwjP": {
     "title": "RAG",
-    "description": "",
+    "description": "Retrieval-Augmented Generation (RAG) combines LLMs with external knowledge retrieval to ground responses in verified, current information. RAG retrieves relevant documents before generating responses, reducing hallucinations and enabling access to information beyond the model's training cutoff. This approach improves accuracy and provides source attribution.",
     "links": []
   },
   "Pw5LWA9vNRY0N2M0FW16f": {
     "title": "Agents",
-    "description": "",
+    "description": "AI agents are autonomous systems that use LLMs to reason, plan, and take actions to achieve specific goals. They combine language understanding with tool usage, memory, and decision-making to perform complex, multi-step tasks. Agents can interact with external APIs and services while maintaining context across interactions.",
     "links": []
   },
   "6W_ONYREbXHwPigoDx1cW": {
     "title": "Prompt Injection",
-    "description": "",
+    "description": "Prompt injection is a security vulnerability where malicious users manipulate LLM inputs to override intended behavior, bypass safety measures, or extract sensitive information. Attackers embed instructions within data to make models ignore original prompts and follow malicious commands. Mitigation requires input sanitization, injection-resistant prompt design, and proper security boundaries.",
     "links": []
   },
   "Sj1CMZzZp8kF-LuHcd_UU": {
     "title": "AI vs AGI",
-    "description": "",
+    "description": "AI (Artificial Intelligence) refers to systems that perform specific tasks intelligently, while AGI (Artificial General Intelligence) represents hypothetical AI with human-level reasoning across all domains. Current LLMs are narrow AI - powerful at language tasks but lacking true understanding or general intelligence like AGI would possess.",
     "links": []
   },
   "JgigM7HvmNOuKnp60v1Ce": {
     "title": "Sampling Parameters",
-    "description": "",
+    "description": "Sampling parameters (temperature, top-K, top-P) control how LLMs select tokens from probability distributions, determining output randomness and creativity. These parameters interact: at extreme settings, one can override others (temperature 0 makes top-K/top-P irrelevant). A balanced starting point is temperature 0.2, top-P 0.95, top-K 30 for coherent but creative results. Understanding their interactions is crucial for optimal prompting—use temperature 0 for factual tasks, higher values for creativity, and combine settings strategically based on your specific use case.",
     "links": []
   },
   "iMwg-I76-Tg5dhu8DGO6U": {
     "title": "Temperature",
-    "description": "",
+    "description": "Temperature controls the randomness in token selection during text generation. Lower values (0-0.3) produce deterministic, factual outputs. Medium values (0.5-0.7) balance creativity and coherence. Higher values (0.8-1.0) generate creative, diverse outputs but may be less coherent. Use low temperature for math/facts, high for creative writing.",
     "links": []
   },
   "FF8ai1v5GDzxXLQhpwuPj": {
     "title": "Top-K",
-    "description": "",
+    "description": "Top-K restricts token selection to the K most likely tokens from the probability distribution. Low values (1-10) produce conservative, factual outputs. Medium values (20-50) balance creativity and quality. High values (50+) enable diverse, creative outputs. Use low K for technical tasks, high K for creative writing.",
     "links": []
   },
   "-G1U1jDN5st1fTUtQmMl1": {
     "title": "Top-P",
-    "description": "",
+    "description": "Top-P (nucleus sampling) selects tokens from the smallest set whose cumulative probability exceeds threshold P. Unlike Top-K's fixed number, Top-P dynamically adjusts based on probability distribution. Low values (0.1-0.5) produce focused outputs, medium (0.6-0.9) balance creativity and coherence, high (0.9-0.99) enable creative diversity.",
     "links": []
   },
   "wSf7Zr8ZYBuKWX0GQX6J3": {
     "title": "Output Control",
-    "description": "",
+    "description": "Output control encompasses techniques and parameters for managing LLM response characteristics including length, format, style, and content boundaries. Key methods include max tokens for length limits, stop sequences for precise boundaries, temperature for creativity control, and structured output requirements for format consistency. Effective output control combines prompt engineering techniques with model parameters to ensure responses meet specific requirements. This is crucial for production applications where consistent, appropriately formatted outputs are essential for user experience and system integration.",
     "links": []
   },
   "vK9Gf8dGu2UvvJJhhuHG9": {
     "title": "Max Tokens",
-    "description": "",
+    "description": "Max tokens setting controls the maximum number of tokens an LLM can generate in response, directly impacting computation cost, response time, and energy consumption. Setting lower limits doesn't make models more concise—it simply stops generation when the limit is reached. This parameter is crucial for techniques like ReAct where models might generate unnecessary tokens after the desired response. Balancing max tokens involves considering cost efficiency, response completeness, and application requirements while ensuring critical information isn't truncated.",
     "links": []
   },
   "v3CylRlojeltcwnE76j8Q": {
     "title": "Stop Sequences",
-    "description": "",
+    "description": "Stop sequences are specific strings that signal the LLM to stop generating text when encountered, providing precise control over output length and format. Common examples include newlines, periods, or custom markers like \"###\" or \"END\". This parameter is particularly useful for structured outputs, preventing models from generating beyond intended boundaries. Stop sequences are essential for ReAct prompting and other scenarios where you need clean, precisely bounded responses. They offer more control than max tokens by stopping at logical breakpoints rather than arbitrary token limits.",
     "links": []
   },
   "g8ylIg4Zh567u-E3yVVY4": {
     "title": "Repetition Penalties",
-    "description": "",
+    "description": "Repetition penalties discourage LLMs from repeating words or phrases by reducing the probability of selecting previously used tokens. This includes frequency penalty (scales with usage count) and presence penalty (applies equally to any used token). These parameters improve output quality by promoting vocabulary diversity and preventing redundant phrasing.",
     "links": []
   },
   "YIVNjkmTOY61VmL0md9Pj": {
     "title": "Frequency Penalty",
-    "description": "",
+    "description": "Frequency penalty reduces token probability based on how frequently they've appeared in the text, with higher penalties for more frequent tokens. This prevents excessive repetition and encourages varied language use. The penalty scales with usage frequency, making overused words less likely to be selected again, improving content diversity.",
     "links": []
   },
   "WpO8V5caudySVehOcuDvK": {
     "title": "Presence Penalty",
-    "description": "",
+    "description": "Presence penalty reduces the likelihood of repeating tokens that have already appeared in the text, encouraging diverse vocabulary usage. Unlike frequency penalty which considers how often tokens appear, presence penalty applies the same penalty to any previously used token, promoting varied content and creativity.",
     "links": []
   },
   "j-PWO-ZmF9Oi9A5bwMRto": {
     "title": "Structured Outputs",
-    "description": "",
+    "description": "Structured outputs involve prompting LLMs to return responses in specific formats like JSON, XML, or other organized structures rather than free-form text. This approach forces models to organize information systematically, reduces hallucinations by imposing format constraints, enables easy programmatic processing, and facilitates integration with applications. For example, requesting movie classification results as JSON with specified schema ensures consistent, parseable responses. Structured outputs are particularly valuable for data extraction, API integration, and applications requiring reliable data formatting.",
     "links": []
   },
   "GRerL9UXN73TwpCW2eTIE": {
     "title": "Zero-Shot Prompting",
-    "description": "",
+    "description": "Zero-shot prompting provides only a task description without examples, relying on the model's training patterns. Simply describe the task clearly, provide input data, and optionally specify output format. Works well for simple classification, text generation, and Q&A, but may produce inconsistent results for complex tasks.",
     "links": []
   },
   "Iufv_LsgUNls-Alx_Btlh": {
     "title": "One-Shot / Few-Shot Prompting",
-    "description": "",
+    "description": "One-shot provides a single example to guide model behavior, while few-shot includes multiple examples (3-5) to demonstrate desired patterns. Examples show output structure, style, and tone, increasing accuracy and consistency. Use few-shot for complex formatting, specialized tasks, and when zero-shot results are inconsistent.",
     "links": []
   },
   "fWo39-hehRgwmx7CF36mM": {
     "title": "System Prompting",
-    "description": "",
+    "description": "System prompting sets the overall context, purpose, and operational guidelines for LLMs. It defines the model's role, behavioral constraints, output format requirements, and safety guardrails. System prompts provide foundational parameters that influence all subsequent interactions, ensuring consistent, controlled, and structured AI responses throughout the session.",
     "links": []
   },
   "XHWKGaSRBYT4MsCHwV-iR": {
     "title": "Role Prompting",
-    "description": "",
+    "description": "Role prompting assigns a specific character, identity, or professional role to the LLM to generate responses consistent with that role's expertise, personality, and communication style. By establishing roles like \"teacher,\" \"travel guide,\" or \"software engineer,\" you provide the model with appropriate domain knowledge, perspective, and tone for more targeted, natural interactions.",
     "links": []
   },
   "5TNK1KcSzh9GTKiEJnM-y": {
     "title": "Contextual Prompting",
-    "description": "",
+    "description": "Contextual prompting provides specific background information or situational details relevant to the current task, helping LLMs understand nuances and tailor responses accordingly. Unlike system or role prompts, contextual prompts supply immediate, task-specific information that's dynamic and changes based on the situation. For example: \"Context: You are writing for a blog about retro 80's arcade video games. Suggest 3 topics to write articles about.\" This technique ensures responses are relevant, accurate, and appropriately framed for the specific context provided.",
     "links": []
   },
   "2MboHh8ugkoH8dSd9d4Mk": {
     "title": "Step-back Prompting",
-    "description": "",
+    "description": "Step-back prompting improves LLM performance by first asking a general question related to the specific task, then using that answer to inform the final response. This technique activates relevant background knowledge before attempting the specific problem. For example, before writing a video game level storyline, first ask \"What are key settings for engaging first-person shooter levels?\" then use those insights to create the specific storyline. This approach reduces biases and improves accuracy by grounding responses in broader principles.",
     "links": []
   },
   "weRaJxEplhKDyFWSMeoyI": {
     "title": "Chain of Thought (CoT) Prompting",
-    "description": "",
+    "description": "Chain of Thought prompting improves LLM reasoning by generating intermediate reasoning steps before providing the final answer. Instead of jumping to conclusions, the model \"thinks through\" problems step by step. Simply adding \"Let's think step by step\" to prompts often dramatically improves accuracy on complex reasoning tasks and mathematical problems.",
     "links": []
   },
   "1EzqCoplXPiHjp9Z-vqn-": {
     "title": "Self-Consistency Prompting",
-    "description": "",
+    "description": "Self-consistency prompting generates multiple reasoning paths for the same problem using higher temperature settings, then selects the most commonly occurring answer through majority voting. This technique combines sampling and voting to improve accuracy and provides pseudo-probability of answer correctness. While more expensive due to multiple API calls, it significantly enhances reliability for complex reasoning tasks by reducing the impact of single incorrect reasoning chains and leveraging diverse problem-solving approaches.",
     "links": []
   },
   "ob9D0W9B9145Da64nbi1M": {
     "title": "Tree of Thoughts (ToT) Prompting",
-    "description": "",
+    "description": "Tree of Thoughts (ToT) generalizes Chain of Thought by allowing LLMs to explore multiple reasoning paths simultaneously rather than following a single linear chain. This approach maintains a tree structure where each thought represents a coherent step toward solving a problem, enabling the model to branch out and explore different reasoning directions. ToT is particularly effective for complex tasks requiring exploration and is well-suited for problems that benefit from considering multiple solution approaches before converging on the best answer.",
     "links": []
   },
   "8Ks6txRSUfMK7VotSQ4sC": {
     "title": "ReAct Prompting",
-    "description": "",
+    "description": "ReAct (Reason and Act) prompting enables LLMs to solve complex tasks by combining reasoning with external tool interactions. It follows a thought-action-observation loop: analyze the problem, perform actions using external APIs, review results, and iterate until solved. Useful for research, multi-step problems, and tasks requiring current data.",
     "links": []
   },
   "diHNCiuKHeMVgvJ4OMwVh": {
     "title": "Automatic Prompt Engineering",
-    "description": "",
+    "description": "Automatic Prompt Engineering (APE) uses LLMs to generate and optimize prompts automatically, reducing human effort while enhancing model performance. The process involves prompting a model to create multiple prompt variants, evaluating them using metrics like BLEU or ROUGE, then selecting the highest-scoring candidate. For example, generating 10 variants of customer order phrases for chatbot training, then testing and refining the best performers. This iterative approach helps discover effective prompts that humans might not consider, automating the optimization process.",
     "links": []
   },
   "Wvu9Q_kNhH1_JlOgxAjP6": {
     "title": "AI Red Teaming",
-    "description": "",
+    "description": "AI red teaming involves deliberately testing AI systems to find vulnerabilities, biases, or harmful behaviors through adversarial prompting. Teams attempt to make models produce undesired outputs, bypass safety measures, or exhibit problematic behaviors. This process helps identify weaknesses and improve AI safety and robustness before deployment.",
     "links": []
   },
   "0H2keZYD8iTNyBgmNVhto": {
     "title": "Prompt Debiasing",
-    "description": "",
+    "description": "Prompt debiasing involves techniques to reduce unwanted biases in LLM outputs by carefully crafting prompts. This includes using neutral language, diverse examples, and explicit instructions to avoid stereotypes or unfair representations. Effective debiasing helps ensure AI outputs are more fair, inclusive, and representative across different groups and perspectives.",
     "links": []
   },
   "HOqWHqAkxLX8f2ImSmZE7": {
     "title": "Prompt Ensembling",
-    "description": "",
+    "description": "Prompt ensembling combines multiple different prompts or prompt variations to improve output quality and consistency. This technique involves running the same query with different prompt formulations and aggregating results through voting, averaging, or selection. Ensembling reduces variance and increases reliability by leveraging diverse prompt perspectives.",
     "links": []
   },
   "CvV3GIvQhsTvE-TQjTpIQ": {
     "title": "LLM Self Evaluation",
-    "description": "",
+    "description": "LLM self-evaluation involves prompting models to assess their own outputs for quality, accuracy, or adherence to criteria. This technique can identify errors, rate confidence levels, or check if responses meet specific requirements. Self-evaluation helps improve output quality through iterative refinement and provides valuable feedback for prompt optimization.",
     "links": []
   },
   "P5nDyQbME53DOEfSkcY6I": {
     "title": "Calibrating LLMs",
-    "description": "",
+    "description": "Calibrating LLMs involves adjusting models so their confidence scores accurately reflect their actual accuracy. Well-calibrated models express appropriate uncertainty - being confident when correct and uncertain when likely wrong. This helps users better trust and interpret model outputs, especially in critical applications where uncertainty awareness is crucial.",
     "links": []
   }
 }
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