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Cursor Automations, MCP, and API Integrations: How AI-Powered Workflows Are Reshaping Modern Development

2026-08-27T12:26:32+00:00

In late 2025, most developers were still using AI coding assistants as glorified autocomplete engines: press Tab, accept a suggestion, and move on. By mid-2026, the same tools are reviewing pull requests, triaging incidents from PagerDuty alerts, posting summaries to Slack, and assigning reviewers based on time zones, all without a human touching the keyboard. At the center of this transformation is Cursor, an AI-native IDE that has evolved far beyond a VS Code fork with an LLM bolted on. With the introduction of Cursor Automations, Background Agents, BugBot Autofix, and deep support for the Model Context Protocol (MCP), Cursor [...]

Cursor Automations, MCP, and API Integrations: How AI-Powered Workflows Are Reshaping Modern Development2026-08-27T12:26:32+00:00

The Modern Developer: AI, Cloud, and What Comes Next

2026-08-27T12:54:24+00:00

For the longest time, the standard advice for entering the technology industry was simple: learn to code. But as AI in software development becomes more common, knowing how to write code is no longer the whole story. At first it's like this: learn Python, JavaScript, Java, or another programming language. Practice writing programs. Build projects. Learn how to debug your mistakes. Eventually, those skills could become the foundation of a career in software development. Yet, technology has expanded far beyond the act of writing code. Developers today work in an environment shaped by cloud computing, automation, and other countless technologies. [...]

The Modern Developer: AI, Cloud, and What Comes Next2026-08-27T12:54:24+00:00

Agentic AI on AWS: From Terraform Modules to the Model Context Protocol

2026-08-28T14:26:33+00:00

Most teams deploying AI on AWS were still running the same playbook: take a foundation model, wire up a retrieval layer, wrap it in an API Gateway endpoint, and call it a chatbot. By mid-2026, the same teams are deploying autonomous agents that reason through multi-step workflows, authenticate against enterprise APIs, call tools they discover at runtime, delegate subtasks to other agents, and roll themselves back when their evaluation scores drop, all without a human touching the AWS Console. At the center of this shift is Amazon Bedrock AgentCore, a managed platform that treats AI agents as first-class infrastructure. Pair [...]

Agentic AI on AWS: From Terraform Modules to the Model Context Protocol2026-08-28T14:26:33+00:00

Building Production AI Agents on AWS: AgentCore Harness, Strands 1.0, and the Multi-Agent Architecture that Actually Ships

2026-08-06T16:10:24+00:00

Six months ago, "AI agents on AWS" meant duct-taping together Amazon Bedrock, a Lambda function to handle tool routing, DynamoDB for session state, CloudWatch for tracing, and a LangGraph loop you prayed would recover from a network hiccup mid-reasoning. Every team was reinventing the same infrastructure. Every demo worked; most productions did not. That changed on June 17, 2026, at AWS Summit New York, where Dr. Swami Sivasubramanian (VP of Agentic AI) announced what AWS is calling the agentic infrastructure layer: Amazon Bedrock AgentCore Harness reaching general availability, the Strands Agents 1.0 SDK going production-grade with native multi-agent primitives, and [...]

Building Production AI Agents on AWS: AgentCore Harness, Strands 1.0, and the Multi-Agent Architecture that Actually Ships2026-08-06T16:10:24+00:00

Automating Publications with Claude, Canva, and n8n

2026-08-19T08:15:15+00:00

Every business that runs a social media page knows the same repetitive cycle. Pick a topic. Write a caption. Design a graphic. Post it on schedule. Repeat tomorrow. Multiply that by every campaign, every seasonal push, every recurring content series, and it becomes a real operational cost, not just a marketing task. That repetitive cycle is exactly what a project called Automating Publications was built to solve. It is a working, experimental content pipeline built with Claude, Canva, Slack, Google Drive, and n8n, and it is a useful reference for any business or enterprise team thinking about applying AI to [...]

Automating Publications with Claude, Canva, and n8n2026-08-19T08:15:15+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

UI/UX Design: Speeding Up the Creative Process with AI

2026-07-13T20:17:29+00:00

If you have ever stared at a blank Figma canvas with a deadline looming, whether that is a thesis defense, a hackathon demo, or a personal app you finally want to ship. You already know that speed matters as much as polish. A traditional UI/UX workflow covers research, wireframing, high-fidelity mockups, and developer handoff, which can take weeks in a normal product cycle. Most people building on a deadline simply do not have weeks to spare. Students finishing a thesis MVP, hackathon participants racing the clock, and hobbyists building for fun on a weekend all share the same goal: getting [...]

UI/UX Design: Speeding Up the Creative Process with AI2026-07-13T20:17:29+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

Amazon Quick & Agentic AI: Understanding the Tools Behind Your AI-Powered Workflow

2026-06-28T11:18:25+00:00

AI is no longer just a tool that answers questions. It is becoming something that takes action, runs workflows, and works alongside teams the way a capable colleague would. Amazon Quick is AWS's take on what that looks like in practice, and this article breaks down what it is, how it works, and why the infrastructure behind it matters. What is Amazon Quick? Imagine asking one platform to pull your sales data, automate a workflow, build you a web app, and research your competitors. That's Amazon Quick. It's AWS's agentic AI platform, and it does a lot. Six things, specifically: [...]

Amazon Quick & Agentic AI: Understanding the Tools Behind Your AI-Powered Workflow2026-06-28T11:18:25+00:00

Build AI Apps Faster with Google AI Studio and Gemini

2026-06-26T16:11:01+00:00

Artificial intelligence has become an essential part of modern software development. It helps developers build applications that understand natural language, generate content, analyze documents, write code, and automate complex tasks. While large language models (LLMs) make these features easier to use, integrating them into real applications still takes time. Developers must configure API authentication, choose the right model, design prompts, and set up supporting infrastructure before they can start building. Google AI Studio simplifies this process. It provides a browser-based environment where developers can test Gemini models without writing integration code first. They can prototype prompts, compare responses, generate API [...]

Build AI Apps Faster with Google AI Studio and Gemini2026-06-26T16:11:01+00:00

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