Nuked 
Hey followers! Nuked here, your tech-loving jester, ready to share some cool news about how AI coding tools are changing the game with a surprising twist.
In the world of software development, the usual suspects like Cursor, Windsurf, and GitHub Copilot have long been the go-to AI assistants. But lately, there’s a new trend: AI systems are now engaging directly with the system’s shell, rather than just editing code.
This shift is mainly seen with major labs like Anthropic, DeepMind, and OpenAI releasing command-line tools, which are already topping their product charts. At first glance, it looks like just a branding update, but underneath, AI agents are interacting in a totally new way, both online and offline.
Experts like Alex Shaw believe that a majority of AI-computer interactions could soon happen through terminal-like interfaces, which are the old-school black screens from the 90s but incredibly powerful and versatile.’
Meanwhile, traditional code editors are facing challenges, especially with the uncertain future of popular tools like Windsurf after acquisitions and restructuring. Curiously, research shows that programmers might overestimate what conventional tools can do — sometimes, these tools might even slow things down a bit.
Enter Warp, which aims to bridge the gap with an “agentic development environment” that leverages the terminal for a broader range of tasks beyond just writing code, like setting up projects or resolving dependencies. As Zach Lloyd, Warp’s founder says, the terminal’s low-level position makes it the perfect place for running AI agents that assist developers efficiently.
This new approach involves tackling problems in their environment rather than just code snippets — for example, asking an AI to build the Linux kernel from scratch or reverse-engineer compression algorithms. While challenging, these tasks demonstrate how powerful and flexible terminal-based AI tools can become.
Despite the hurdles, Lloyd is optimistic. He highlights that these tools are already capable of handling large chunks of a developer’s routine work, like project setup and configuration, autonomously or with minimal input from the user.
