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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

Zero-Sweat: A Comprehensive Guide to IAM Policy Autopilot

2025-12-28T16:02:53+00:00

Picture this: your application works perfectly on your local machine. You deploy it to AWS, then immediately hit an “Access Denied” error. If you’ve worked with AWS for any length of time, you’ve experienced this. What follows is usually a frustrating dive into IAM documentation, trial-and-error permission updates, and lost development momentum. AWS Labs created IAM Policy Autopilot to solve exactly this problem. IAM Policy Autopilot analyzes your application code and generates AWS IAM policies based on the actual SDK calls your code makes. No guessing. No hallucinated permissions. Just deterministic, repeatable policy generation. What Is IAM Policy Autopilot? IAM [...]

Zero-Sweat: A Comprehensive Guide to IAM Policy Autopilot2025-12-28T16:02:53+00:00

AWS Career Paths Explained: Cloud Engineer vs Solutions Architect vs DevOps Engineer

2025-12-28T07:57:24+00:00

At some point in your AWS journey, you will probably stop and ask yourself a simple question: “What job am I actually preparing for?” You might already be learning AWS services, building labs, or taking practice exams. You know what EC2, S3, and IAM are. At the same time, you keep seeing job titles like Cloud Engineer, Solutions Architect, and DevOps Engineer. Sometimes they sound interchangeable. Other times they feel like completely different careers. Choosing between different AWS career paths can be confusing, especially when job titles overlap but day-to-day work looks very different. These roles overlap by design, but [...]

AWS Career Paths Explained: Cloud Engineer vs Solutions Architect vs DevOps Engineer2025-12-28T07:57:24+00:00

The Year of the Agent: Anthropic’s Claude AI Models and Agents

2025-12-26T17:20:34+00:00

  Looking back on the past year of 2025 coding with the help of artificial intelligence, we can safely say that it was the year of agents, especially pioneered by Anthropic with Claude Code. AI products have matured to offer highly reliable agents that can understand, navigate, and work seamlessly on large codebases. It is the end of the old ways: of manually copying and pasting code into web AI applications. Agents are now actually part of the codebase, navigating around like a real developer. And they can now be left with long-running tasks on their own,opening and working on [...]

The Year of the Agent: Anthropic’s Claude AI Models and Agents2025-12-26T17:20:34+00:00

AI-Driven Cloud Security at AWS re:Invent 2025

2025-12-26T11:28:51+00:00

Cloud computing continues to accelerate at a pace that traditional security models were never designed to support. Development teams now provision infrastructure in minutes, deploy services continuously, and scale applications automatically. However, security processes often lag behind this speed. In many organizations, security still enters the workflow after key architectural decisions are already finalized. As a result, teams spend more time fixing problems than preventing them. Although many organizations attempt to shift security earlier in development, the results are often disappointing. Security tools may run during build or deployment stages, yet they frequently lack the context required to provide meaningful [...]

AI-Driven Cloud Security at AWS re:Invent 20252025-12-26T11:28:51+00:00

Amazon Q in Practice: How AWS’s AI Assistant Actually Works for Businesses and Developers

2025-12-21T16:15:25+00:00

Amazon Q is often introduced as AWS's generative AI assistant, but that description doesn't really explain why it exists or how it behaves once you start using it. If you treat Amazon Q like a general chatbot, it can feel restrictive or underwhelming. If you treat it as an AWS-native system designed around identity, permissions, and retrieval, it becomes much easier to understand. And much more useful. I've spent a lot of time working with Amazon Q while creating video content for Tutorials Dojo courses, and most of what I'll share here comes from that hands-on experience. My goal is [...]

Amazon Q in Practice: How AWS’s AI Assistant Actually Works for Businesses and Developers2025-12-21T16:15:25+00:00

Automating PII Detection and Redaction with Amazon Comprehend

2025-12-19T13:49:49+00:00

Organizations today are entrusted with enormous amounts of sensitive information. Customer support logs, healthcare records, financial transactions, and even training datasets often contain Personally Identifiable Information (PII) such as names, phone numbers, email addresses, or credit card numbers. Protecting this information is not just a matter of compliance with regulations like GDPR, HIPAA, or PCI DSS. It is also central to maintaining customer trust and reducing the risk of data breaches. Amazon Comprehend, a managed natural language processing (NLP) service, provides a powerful way to automate the detection and redaction of PII. Instead of relying on manual review or custom [...]

Automating PII Detection and Redaction with Amazon Comprehend2025-12-19T13:49:49+00:00

Build a Model-Agnostic AI Text Summarizer Web Extension

2025-12-17T14:53:51+00:00

Browser extensions are a great way to bring AI directly into your everyday workflows. Instead of copying text into external tools and websites to be summarized, you can do it right on the page. In this tutorial, we'll build a lightweight, model-agnostic Chrome extension that summarizes selected text using AI. With a simple right-click, users can send any highlighted text to an AI model of their choice and instantly view a concise summary in the extension popup. Rather than focusing on a single provider, this project is designed to be beginner-friendly and privacy-focused. API keys are supplied by the user [...]

Build a Model-Agnostic AI Text Summarizer Web Extension2025-12-17T14:53:51+00:00

Can Gemini 3 Replace My AI Toolkit?

2025-12-04T00:51:06+00:00

I've always approached AI with one mindset: use whatever tool gets the job done fastest and cleanest. I'm not loyal to one model, one company, or one ecosystem. I switch between tools depending on what my day looks like. In school, that might mean summarizing academic papers. At work or during self-study, that might mean debugging code or reviewing a cloud diagram. For daily life, it might just mean drafting an email or organizing my notes. So when Gemini 3 came out, I didn't ask whether it was "better" in the vague, marketing sense. My question was simpler: Could it [...]

Can Gemini 3 Replace My AI Toolkit?2025-12-04T00:51:06+00:00

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