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How Content Chunking Works in Amazon Bedrock Knowledge Bases: How AI Really Reads Your Documents

2026-01-11T12:03:57+00:00

Modern generative AI systems often appear to “read” entire documents instantly, returning precide answers form long PDFs or dense technical manuals. In reality, large language models do not consume documents holistically. Instead, they rely on carefully prepared context that is retrieved and supplied at query time. One  of the most critical and often misunderstood mechanisms behind this process is content chunking. At its core, content chunking determines how raw documents such as PDFs, webpages, or text files are transformed into smaller, meaningful units that can be indexed, embedded, and retrieved efficiently. Understanding how chunking works and how to configure it [...]

How Content Chunking Works in Amazon Bedrock Knowledge Bases: How AI Really Reads Your Documents2026-01-11T12:03:57+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

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

2026-01-08T08:21:54+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 Comprehend2026-01-08T08:21:54+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

AWS Vector Databases Explained: Semantic Search and RAG Systems

2025-12-21T03:02:32+00:00

The generative AI (GenAI) revolution has transformed how organizations extract value from their data. While large language models (LLMs) demonstrate remarkable capabilities in understanding and generating human-like text, their true enterprise potential is unlocked only when they can access proprietary, domain-specific information. This necessity has propelled vector databases from a specialized niche into an essential pillar of modern AI infrastructure. But First, What Are Vector Databases? A vector database, as its name suggests, is a type of database designed to store, index, and efficiently search vector embeddings. These vectors are high-dimensional points that represent meaning.  At its core, a vector [...]

AWS Vector Databases Explained: Semantic Search and RAG Systems2025-12-21T03:02:32+00:00

What is Amazon Bedrock AgentCore?

2025-12-02T08:36:36+00:00

Imagine spending months building an AI agent that integrates seamlessly into your development environment. It employs tools, responds to inquiries, and completes duties precisely as planned. But moving it to production becomes a nightmare: suddenly, you are dealing with scale problems, security concerns, authentication systems, and API interfaces. What should have been a simple deployment becomes weeks of infrastructure labor unrelated to your agent's intelligence. This production gap is the bane of countless developers, and it is precisely the problem Amazon Bedrock AgentCore was built to stop. What is Amazon Bedrock AgentCore? The Amazon Bedrock AgentCore is an all-in-one platform [...]

What is Amazon Bedrock AgentCore?2025-12-02T08:36:36+00:00

High-Performing ≠ Massive: The Rise and Progression of Small Language Models (SLMs)

2025-10-17T11:29:21+00:00

Have you ever needed to find a new charger for your device, only to discover that its voltage wasn’t compatible, causing it not to work or even risking damage? Without checking the actual needs of your device, you’ve probably thought that you could go with what the seller recommends as the “highest quality” rather than your device’s fitting needs. With the current utilization of AI for businesses, bigger doesn’t always mean better. Large Language Models (LLMs) like GPT, Gemini, Claude, etc. have been in the spotlight for their high-performing power for computational tasks and content generation capabilities. But let’s be [...]

High-Performing ≠ Massive: The Rise and Progression of Small Language Models (SLMs)2025-10-17T11:29:21+00:00

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