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GitHub Pull Requests

2026-01-07T17:12:47+00:00

GitHub Pull Requests Cheat Sheet Pull requests are a structured way to propose and manage code changes within a project. As GitHub’s primary collaboration feature, it provides a dedicated space for reviewing modifications, holding discussions, and requesting improvements before integration. By introducing review checkpoints and shared visibility, pull requests help teams collaborate efficiently, detect problems early, and uphold long-term code quality and project stability. Branches When a repository is created on GitHub with initial content, it is initialized with a single branch. This first branch is known as the default branch. The default branch is the branch displayed when someone [...]

GitHub Pull Requests2026-01-07T17:12:47+00:00

GitHub Issues

2026-01-06T11:12:49+00:00

GitHub Issues Cheat Sheet Issues enable teams to plan, discuss, and track work within a repository. They are quick to create, flexible, and can be used to manage bug reports, feature requests, ideas, and other tasks. When combined with projects, issues help organize work, manage priorities, and track progress across a team. Work can be further structured by using sub-issues, making it easier to view and manage the full hierarchy of tasks.   Issues can be created in multiple ways to suit different workflows, including directly from a repository, alongside sub-issues, from comments on issues or pull requests, from specific [...]

GitHub Issues2026-01-06T11:12:49+00:00

A Beginner’s Guide to the Machine Learning Pipeline on GCP

2026-01-08T13:02:44+00:00

When people hear the term "machine learning," they often imagine complex math, advanced algorithms, or mysterious "AI magic" happening behind the scenes. In reality, machine learning on the cloud is far more practical and structured than it may sound. At its core, an ML pipeline is a series of steps that transform raw data into useful predictions. Think of it like a typical software workflow: You prepare your code You build the application You deploy it Users interact with it An ML pipeline follows the same idea, just with different building blocks. Instead of starting with source code, you begin [...]

A Beginner’s Guide to the Machine Learning Pipeline on GCP2026-01-08T13:02:44+00:00

GitHub Discussions

2026-01-06T11:11:07+00:00

GitHub Discussions Cheat Sheet A forum-like space within a GitHub repository or organization for collaborative communication. It is designed for open-ended conversations, questions, ideas, planning, updates, and community interaction, distinct from issues (which are for actionable work). Answering questions Sharing ideas or proposals Announcing news or releases Brainstorming and community feedback Creating a community knowledge base GitHub Discussions Categories Discussions must be grouped into categories that define their purpose and format. Category Purpose Format Announcements Latest updates and announcements from project maintainers. Announcement General Everything relevant to the project. Open-ended discussion Ideas Suggestions for project improvements. Open-ended discussion Polls Polls [...]

GitHub Discussions2026-01-06T11:11:07+00:00

Amazon Bedrock Prompt Management

2025-12-30T14:14:17+00:00

Bookmarks Core Concepts Supported Regions and Models Prerequisites Creating a Prompt Viewing Prompt Information Modifying a Prompt Testing a Prompt Optimizing a Prompt Deployment using Versions Deleting a Prompt Security Best Practices Pricing Amazon Bedrock Prompt Management Cheat Sheet Amazon Bedrock Prompt Management is a centralized prompt management system for generative AI, enabling easy creation, testing, versioning, and deployment of structured prompts while separating prompt engineering from application code. It offers key [...]

Amazon Bedrock Prompt Management2025-12-30T14:14:17+00:00

Amazon Titan

2025-12-30T14:40:34+00:00

Bookmarks Features Use Cases Amazon Titan Text Models Amazon Titan Text Embeddings Models Amazon Titan Multimodal Embeddings G1 Model Amazon Titan Image Generator G1 Models Pricing Amazon Titan Cheat Sheet Amazon Titan models are a family of powerful, general-purpose models pre-trained by AWS on massive datasets. They are designed to be used out of the box or fine-tuned with your own data, allowing you to adapt them for specific tasks without the need to annotate large volumes of training data. The Titan family consists [...]

Amazon Titan2025-12-30T14:40:34+00:00

AWS Strands Agents

2025-12-30T14:06:23+00:00

Bookmarks Key Features Use Cases Implementation Approach for Strands Agents Real World Examples of Strands Agents Agents Tools Model Providers Streaming Multi-Agent Safety and Security Observability and evaluation Strands Agents vs. Strands Agents SOPs Pricing AWS Strands Agents Cheat Sheet AWS Strands Agents is an open-source SDK that enables developers to build, test, and deploy AI agents by simply defining a prompt and a list of tools in code. True to its [...]

AWS Strands Agents2025-12-30T14:06:23+00:00

AWS Agent Squad

2025-12-30T14:03:07+00:00

Bookmarks Key Features Use Cases How AWS Squad Agents Work Agents Supported (Built-in Agents) Core Concepts Pricing AWS Agent Squad Cheat Sheet An open-source framework for orchestrating and routing user queries across multiple specialized AI agents. It uses LLM-based intent classification to dynamically assign tasks to the best-suited agent, such as Amazon Bedrock models, Lex bots, or Lambda functions, while maintaining unified conversation context for seamless interactions.   Key Features Intelligent Intent Classification: Dynamically routes queries to the most suitable agent by analyzing context and content. [...]

AWS Agent Squad2025-12-30T14:03:07+00:00

How to Stay Valuable as Cloud Tools Keep Changing

2025-12-30T08:06:12+00:00

If you work in cloud computing or are trying to break into it you have probably wondered how to stay valuable in cloud computing when the tools you learn today may be irrelevant tomorrow. Cloud platforms evolve quickly. Amazon Web Services releases new services every year, updates existing ones, and quietly deprecates others. DevOps tooling shifts just as fast. It is easy to feel like staying relevant means constantly chasing whatever is new. In reality, long-term value in cloud careers has very little to do with memorizing tools.  Why Tool Chasing Becomes a Trap Many people approach cloud learning by [...]

How to Stay Valuable as Cloud Tools Keep Changing2025-12-30T08:06:12+00:00

Building a Cost-Aware RAG Application with Amazon Bedrock

2026-01-06T08:43:56+00:00

What if your Client can have a Chatbot that throws a highly accurate responses based on your documents? Without having a guilt of the monthly expenses. Without even subscribing to any costly,  AI-support subscriptions. Only pay per inquiry requests to your model provider,  and of course only costs you cents, and it lessens when your client is already satisfied with the answer, as it returns a fully verified response based from the documents you have in your database? Consider this as well, it is cost-aware, making sure that it will notify you once it exceeds your budget limits for you [...]

Building a Cost-Aware RAG Application with Amazon Bedrock2026-01-06T08:43:56+00:00

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