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Building Diffender: A Serverless AI Security Reviewer for GitHub Pull Requests with Amazon Bedrock

2026-07-13T20:55:30+00:00

A pull request can pass its tests, satisfy its acceptance criteria, and still expose a production credential in one line of code. Diffender is an Amazon Bedrock pull request reviewer built to identify that kind of risk before the change reaches the main branch. However, human review remains essential, and its depth can vary with workload, time pressure, and security experience. Meanwhile, deterministic scanners provide valuable coverage, although their findings are not always presented in a form that developers can immediately understand and act on. Diffender adds another layer to that review process. It is a serverless GitHub bot that [...]

Building Diffender: A Serverless AI Security Reviewer for GitHub Pull Requests with Amazon Bedrock2026-07-13T20:55:30+00:00

Everything You Need to Know About Harness Engineering

2026-07-13T20:21:29+00:00

AI agents can now write code, browse the web, and run for hours without a human watching. Ask one to build a feature, and it might open ten files and call five tools. It can make a hundred small decisions before it ever shows you a result. That is a different animal from a chatbot answering one question. In my experience following this shift, it also breaks the old playbook for controlling AI behavior. For a while, prompt engineering was the go-to answer. Write a clearer instruction, add a few examples, and the model behaves. That still works for single-turn [...]

Everything You Need to Know About Harness Engineering2026-07-13T20:21:29+00:00

Agentjacking: How Fake Sentry Errors Hijack AI Coding Agents

2026-06-28T15:46:35+00:00

AI coding agents like Claude Code, Cursor, and Codex now do far more than autocomplete. They read source code, query observability platforms, open pull requests, and run terminal commands on developer machines. That expanded access is useful, but it also creates a problem most security teams have not accounted for: when an agent reads data from an external tool, it often treats that data as trustworthy. A new attack class called agentjacking takes advantage of exactly this assumption. Researchers at Tenet Security documented the technique in June 2026. It tricks AI coding agents into executing attacker-controlled code by hiding instructions [...]

Agentjacking: How Fake Sentry Errors Hijack AI Coding Agents2026-06-28T15:46:35+00:00

AWS Data and AI Journey: Building Agentic AI Systems

2026-05-25T16:14:40+00:00

Stage 5 of the AWS Data and AI Journey: Building Agentic AI Systems Building agentic AI systems is the next frontier for organizations that have already laid the groundwork with a modern data foundation, governed pipelines, and enterprise-wide generative AI. This is where agentic AI enters the picture. Generative AI systems can answer questions, summarize documents, and generate content. Agentic AI goes further by enabling systems to reason through tasks, interact with tools, make decisions, coordinate workflows, and complete multi-step objectives with limited human intervention. Instead of acting only as assistants, AI systems begin operating more like autonomous digital workers [...]

AWS Data and AI Journey: Building Agentic AI Systems2026-05-25T16:14:40+00:00

AWS Data and AI Journey: Applying Generative AI Across the Enterprise

2026-05-25T12:49:16+00:00

Stage 4 of the AWS Data and AI Journey: Applying Generative AI Across the Enterprise Applying generative AI across the enterprise is no longer just an experiment, it's a strategic priority for organizations ready to turn their data into real business intelligence. This is where generative AI enters the picture. With trusted, connected, and governed data in place, organizations can confidently apply large language models, retrieval systems, and AI agents to real business problems. Generative AI shifts data from being a record of what happened into an active driver of decisions, automation, and customer experience. Stage 4 of the AWS [...]

AWS Data and AI Journey: Applying Generative AI Across the Enterprise2026-05-25T12:49:16+00:00

AI Isn’t Just for Developers Anymore

2026-05-21T16:20:06+00:00

A few years ago, AI tools were mostly associated with developers and data scientists. Fast forward to 2026, and the story has changed completely. Marketing interns are generating full campaign ideas in an afternoon, HR coordinators are screening resumes in minutes, and designers are turning simple text prompts into polished mockups, all without writing a single line of code. This shift is one of the most important changes happening in the workplace right now as AI tools for non-technical users narrow the gap between technical and non-technical professionals. In this article, I will show you how different non-technical roles are actually [...]

AI Isn’t Just for Developers Anymore2026-05-21T16:20:06+00:00

Physical AI in 2026: Why Mechatronics Matters

2026-05-04T15:11:03+00:00

Many learners and engineers who focus on cloud and AI still think of intelligence as something that exists only in data centers or large language models. In 2026, a major shift is happening. AI is stepping out of the digital world and into the physical one. This is called Physical AI, also known as Embodied AI. It combines powerful foundation models with real-world robotics and mechatronic systems. For the first time, AI does not just think. It acts through hardware such as sensors, actuators, motors, and control systems. This article explores what Physical AI means in practice and why mechatronics [...]

Physical AI in 2026: Why Mechatronics Matters2026-05-04T15:11:03+00:00

Amazon Quick Sight Sheet Tooltips: Enhancing Data Storytelling and Dashboard UX

2026-04-29T06:08:05+00:00

Modern organizations use data visualization tools for critical decisions. Dashboards simplify complex datasets, turning millions of rows of raw data into digestible formats. Still, users often view a dashboard and feel they aren't seeing the whole picture. Dashboards often lack immediate context, resulting in a frustrating user experience. Analysts must constantly switch between views, tabs, and reports just to understand the insights. To solve this, AWS introduced Sheet Tooltips in Amazon Quick Sight, a powerful feature that enables richer, more interactive data storytelling in a single dashboard view. The Problem with Traditional Dashboards While business intelligence (BI) has evolved significantly, [...]

Amazon Quick Sight Sheet Tooltips: Enhancing Data Storytelling and Dashboard UX2026-04-29T06:08:05+00:00

AWS Data and AI Journey: Data Governance and Security

2026-04-27T15:18:02+00:00

Stage 3 of the AWS Data and AI Journey: Data Governance and Security As organizations establish a modern data foundation (Stage 1) and enable seamless data movement (Stage 2), the next critical step is ensuring that data remains trusted, secure, and compliant across the entire ecosystem. At this stage, data is no longer confined to a single platform. It flows across cloud services, SaaS applications, analytics environments, and AI systems. Without strong governance and security, this expanded data landscape introduces risks such as unauthorized access, data leakage, compliance violations, and loss of trust in data. Stage 3 focuses on building [...]

AWS Data and AI Journey: Data Governance and Security2026-04-27T15:18:02+00:00

Tech Debt in the AI Era

2026-04-02T17:30:43+00:00

Every software team knows the feeling. You ship fast to hit a deadline, planning to clean it up late, but "later" never comes. Soon, quick fixes pile up, and instead of saving time, you’re spending more than you planned. That’s technical debt in a nutshell — and it’s not going away anytime soon. What is changing is how we manage and deal with it. Modern systems are more distributed, interconnected, and increasingly powered by AI. In this environment, periodic clean-ups, manual code reviews, and occasional rewrites aren’t enough. Costs compound faster, dependencies deepen, and risks become harder to trace. So [...]

Tech Debt in the AI Era2026-04-02T17:30:43+00:00

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