Software developers have spent the past two years watching AI coding tools evolve from advanced autocomplete into something that may, in some cases, construct entire applications from a text prompt. Tools like Anthropic’s Claude Code and OpenAI’s Codex can now work on software projects for hours at a time, writing code, running tests, and, with human supervision, fixing bugs. OpenAI says it now uses Codex to construct Codex itself, and the corporate recently published technical details about how the tool works under the hood. It has caused many to wonder: Is that this just more AI industry hype, or are things actually different this time?
To search out out, Ars reached out to several skilled developers on Bluesky to ask how they feel about these tools in practice, and the responses revealed a workforce that largely agrees the technology works, but stays divided on whether that’s entirely excellent news. It’s a small sample size that was self-selected by those that desired to participate, but their views are still instructive as working professionals within the space.
David Hagerty, a developer who works on point-of-sale systems, told Ars Technica up front that he’s skeptical of the marketing. “All the AI firms are hyping up the capabilities a lot,” he said. “Don’t get me improper—LLMs are revolutionary and can have an immense impact, but don’t expect them to ever write the following great American novel or anything. It’s not how they work.”
Roland Dreier, a software engineer who has contributed extensively to the Linux kernel prior to now, told Ars Technica that he acknowledges the presence of hype but has watched the progression of the AI space closely. “It appears like implausible hype, but state-of-the-art agents are only staggeringly good at once,” he said. Dreier described a “step-change” prior to now six months, particularly after Anthropic released Claude Opus 4.5. Where he once used AI for autocomplete and asking the occasional query, he now expects to inform an agent “this test is failing, debug it and fix it for me” and have it work. He estimated a 10x speed improvement for complex tasks like constructing a Rust backend service with Terraform deployment configuration and a Svelte frontend.
