List of AI News about autonomous coding
| Time | Details |
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2026-01-14 22:45 |
GPT-5.2 AI Agents Generate 3 Million Lines of Code in a Week: Transforming Software Development
According to Michael Truell on Twitter, a team used GPT-5.2-powered agents in Cursor to autonomously write over 3 million lines of code across thousands of files within just one week. The agents built an entire browser from scratch, including a Rust-based rendering engine, HTML parsing, CSS cascade, layout, text shaping, painting, and a custom JavaScript VM. While the resulting product is not yet at the level of Webkit or Chromium, the successful rendering of simple websites demonstrates significant progress in AI-driven software engineering. This achievement signals a major shift in how businesses can approach large-scale coding tasks, software prototyping, and rapid product iteration, leveraging AI to accelerate innovation and reduce development costs (source: Michael Truell, Twitter: https://x.com/mntruell/status/2011562190286045552). |
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2025-12-03 18:58 |
Anything Max: Autonomous AI Software Engineer Solves 97% of Bugs and Accelerates App Development
According to @godofprompt on Twitter, Anything Max is redefining the AI software engineering landscape as the first truly autonomous AI engineer capable of independently writing, testing, debugging, and iterating on code without human intervention. Unlike current tools such as Lovable, Bolt, or Cursor, Anything Max interacts with applications in a human-like manner, diagnosing and resolving issues as a real engineer would. With over 700,000 builders already leveraging this technology, the AI delivers practical business value by rapidly handling feature work, debugging, and long-horizon tasks—solving more than 97% of encountered issues (source: @godofprompt, Twitter, Dec 3, 2025). Real-world examples include fixing complex checkout flows, resolving session bugs, and building full systems autonomously. This advancement positions Anything Max as a transformative force for software teams, enabling companies to accelerate release cycles and reduce development bottlenecks, thereby offering significant AI-driven market advantages. |