Stumbling into AI: Part 4—Terminology Tidy-up (and a little rant)
A blog post exploring the differences between AI and ML, clarifying terminology and common misconceptions in the field.
A blog post exploring the differences between AI and ML, clarifying terminology and common misconceptions in the field.
Vivaldi browser's CEO announces the browser will remain AI-free, criticizing the industry's push of often-useless AI features into every tool.
How AI-assisted reverse engineering helps companies understand and modernize critical legacy systems that have become 'black boxes'.
How Thoughtworks used AI and a 'Research, Review, Rebuild' workflow to modernize the Bahmni hospital system's frontend, drastically cutting migration time.
A guide to building a custom CLI coding agent using the Pydantic-AI framework and Model Context Protocol for project-specific development tasks.
Explores the long-term impact of LLMs on software development, focusing on code validation and the balance between disposable and durable software.
A developer builds a personal AI workflow using LangGraph, focusing on integrating human-in-the-loop processes.
A developer shares how AI tools helped reverse-engineer and optimize a slow API endpoint, moving from a complex transaction script to a domain model.
A recap of major Generative AI developments in summer 2025, covering new models from Google, xAI, and Chinese firms, plus policy and security news.
A recap of organizing and speaking at Global Azure Quebec 2025, focusing on AI red teaming and securing generative AI workloads.
An analysis of Generative AI's impact on coding and writing, exploring its benefits, limitations, and potential consequences for human creativity.
A developer's personal crisis about the impact of Generative AI on software engineering careers, ethics, and the future of the industry.
Discusses how AI tools like GitHub Copilot are changing developer work, arguing they act as powerful assistants rather than replacements.
Martin Fowler shares three articles on Gen AI's impact on developers and reflections on meaningful work.
A Thoughtworks engineer argues that developers must still care about code quality and testing, even with advanced AI coding assistants.
A technical exploration of llmfs, a FUSE filesystem where all file operations are dynamically generated and controlled by an LLM.
A hands-on guide for JavaScript developers to learn Generative AI and LLMs through interactive lessons, projects, and a companion app.
Martin Fowler argues that LLMs represent a fundamental shift in software development, comparable to the move from assembler to high-level languages.
An engineer shares insights on how AI is transforming software development workflows and the rise of the AI-enhanced engineer.
Learn how Amazon Q Developer AI assistant enhances software security and code quality through SCA, SAST, and DevSecOps integration.