A daily tech reading list covering AI agents, software engineering trends, secure coding, and new developer tools like Gemini models and MCP SDKs.
A developer shares three key lessons from a week of 'vibe coding' with AI tools like GitHub Copilot, focusing on SDLC importance and tool improvements.
Explores the Ralph Wiggum Loop, an autonomous agent pattern for software development, with a practical example using IBM Bob.
Explores the long-term impact of LLMs on software development, focusing on code validation and the balance between disposable and durable software.
Learn how Amazon Q Developer AI assistant enhances software security and code quality through SCA, SAST, and DevSecOps integration.
Amazon Q Developer introduces an agentic coding experience within the IDE, allowing natural language control to read/write files, run commands, and build code.
AWS Developer Day 2025 highlights how generative AI tools from AWS are transforming and accelerating software development in the cloud.
Explores how AI-powered tools automate and improve code reviews by identifying bugs, vulnerabilities, and inconsistencies to enhance software quality.
A chalk talk on using Amazon CodeCatalyst to improve code quality through test plans, coverage, and dependency checks.
The author questions when 'Pull Request' became a formal SDLC stage, especially for testing, and critiques its common usage and meaning.
A guide to integrating generative AI tools like GitHub Copilot into the software development lifecycle, addressing adoption barriers and IP concerns.
Explores how Amazon CodeCatalyst facilitates team collaboration on software projects, tracking issues and changes through the SDLC.
Explains the 'shift left' approach to integrating security early in the DevOps software development lifecycle for better outcomes.
Using Python's pytm framework to threat model the security flaws in the fictional systems of Jurassic Park.
