Over the past few years, the evolution of AI-driven tools like GitHub’s Copilot and other large language models (LLMs) has promised to revolutionise programming. By leveraging deep learning, these tools can generate code, suggest solutions, and even troubleshoot issues in real-time, saving developers hours of work. While these tools have obvious benefits in terms of productivity, there’s a growing concern that they may also have unintended consequences on the quality and skillset of programmers.
Devs gaining little (if anything) from AI coding assistants
Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.
Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
The rise of large language models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understanding, code generation, software testing, and program repair. As CodeLLMs are being employed toward automating these tasks, one question that arises, especially in enterprise settings, is whether these coding assistants and the code LLMs that power them are ready for real-world projects and enterprise use cases, and how do they impact the existing software engineering process and user experience. In this paper we survey 57 developers from different domains and with varying software engineering skill about their experience with AI coding assistants and CodeLLMs. We also reviewed 35 user surveys on the usage, experience and expectations of professionals and students using AI coding assistants and CodeLLMs. Based on our study findings and analysis of existing surveys, we discuss the requirements for AI-powered coding assistants.
Supermaven: Free AI Code Completion
The fastest copilot. Supermaven uses a 1 million token context window to provide the highest quality code completions.
I guess I'm AI-pilled now?
As I've mentioned before, I have pretty mixed feelings on AI. Like many things in life, more than one thing can be true. I'm also going to throw a caveat here up front that most of my examples use GitHub Copilot. I work for GitHub so I…
AI Coding Agents: Adoption Trends - The JetBrains Blog
How many developers use AI coding agents (Claude Code, Codex, Cursor, JetBrains Junie, and others)? Evidence from the Developer Ecosystem Survey 2026.
Visual Studio Code - The open source AI code editor
Visual Studio Code redefines AI-powered coding with GitHub Copilot for building and debugging modern web and cloud applications. Visual Studio Code is free and available on your favorite platform - Linux, macOS, and Windows.
Is GitHub Copilot Any Good? — Sympolymathesy, by Chris Krycho
Generative AI has a lot of hype right now, and GitHub Copilot has been hailed as revolutionary. Is it actually any good? (Betteridge’s Law applies, but the details might still interest you.)
Maintaining the love for coding in the time of AI
By Alex Band Over the last year, we have seen the profound effects Large Language Models (LLMs) have on our open-source software work at NLnet Labs. These can be grouped into two main areas: community contributions and security reports. Before we dive into this topic, let me first give
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Large Language Model (LLM) agents have been widely adopted in modern software development workflows. SWE-bench [13] and related works [23, 24, 22, 25, 15] establish the task of issue resolution as a de-facto standard for assessing their capability and usefulness. In this setting, an agent is given an entire codebase, a task description (e.g., a bug report or feature request) in natural language and is instructed to produce a code patch that resolves the issue and passes the repository’s test suite. These benchmarks have been instrumental in demonstrating both the substantial potential and the persistent limitations of current models as SWE agents.
How Cursor is building the future of AI coding with Claude
Talking to Windows’ Copilot AI makes a computer feel incompetent
Hey Copilot, are you useful yet?
'AI' Sucks the Joy Out of Programming
I’ve used spicy auto-complete, as well as agents running in my IDE, in my CLI, or on GitHub’s server-side. I’ve been experimenting enough with LLM/AI-driven programming to have an opinion on it. And it kind of sucks.
No Vibes Allowed: Solving Hard Problems in Complex Codebases – Dex Horthy, HumanLayer
AI coding wisdom from the people who would know
Essays and threads from experienced developers who've gone deep on AI-assisted coding.
Developers say AI coding tools work—and that's precisely what worries them
Ars spoke to several software devs about AI and found enthusiasm tempered by unease.
AI Code Is Producing a Quality Crisis Nobody Wants to Talk About
The productivity numbers look great. AI coding tools are everywhere.
