This article explains how to maintain a single source of truth for coding standards in a .ai/rules directory and automatically synchronize those rules across various AI assistants such as Kiro, GitHub Copilot, Cursor, Windsurf, and Qodo using configurable steering files and a sync script.
The article analyses how AI‑generated code creates massive technical debt, explains Spec‑Driven Development (SDD) and its three maturity levels, evaluates three real‑world tools—Kiro, spec‑kit and Tessl—through concrete metrics and expert commentary, and finally advises when SDD is worthwhile and when it becomes a heavyweight process.
This article shows how to use Kiro IDE to turn business needs into AI Agent solutions, generate SPEC‑driven documentation, and deploy the agents on Amazon Bedrock AgentCore, covering the AI‑driven development workflow, architecture choices, code examples, deployment steps, and common troubleshooting tips.
This article presents a detailed case study of how a manufacturing company replaced manual Excel‑based overseas logistics price lookups with an AI‑driven, serverless solution built on Amazon Bedrock AgentCore, Kiro, and Amazon Quick Suite, achieving rapid, precise quotations while eliminating operational overhead.
During a holiday break the author used AI programming assistants Kiro and OpenCode to create a complete Java‑backed, Jamstack‑based full‑stack application that scrapes Epic Games' free‑game listings, generates static JSON/HTML pages, and deploys automatically to Cloudflare Pages, demonstrating AI‑driven development efficiency.
A recent 13‑hour AWS service disruption was traced to the internal AI coding assistant Kiro, whose elevated permissions and lack of isolated approval mechanisms allowed it to delete critical resources, highlighting the need for stricter AI‑specific access controls in cloud operations.
The article explains Spec‑Driven Development (SDD) as a specification‑first paradigm, outlines its three implementation layers, examines key components like Specs and Memory Banks, compares three representative tools (Kiro, spec‑kit, Tessl), and discusses practical challenges and future directions for broader adoption.
This article provides a detailed overview of Kiro, Amazon's AI‑driven IDE that integrates Claude models to bring specification‑driven structure to vibe coding, covering its core concepts, installation steps, key features, workflow, pricing, and practical insights from a hands‑on experience.
This article explains how to replace the luck‑based Vibe Coding approach with a structured Spec workflow—using Kiro, Claude Code, or other AI IDEs—to turn vague prompts into clear requirements, designs, task lists, and incremental, reviewable code, dramatically improving productivity and quality.
The article contrasts the chaotic, prompt‑driven "Vibe coding" approach with Kiro's Spec‑driven development, explaining how a two‑session model—Vibe for creative exploration and Spec for deterministic engineering—structures AI projects from project‑level documentation to runtime execution, improving reliability and traceability.
