AI Coding Tools Shift to the Terminal: The Rise of Agentic Development in Software Engineering
AI-powered coding tools are undergoing a significant transition — moving away from traditional integrated development environments (IDEs) like Cursor, Windsurf, and GitHub Copilot, and into the command-line interface (CLI), or terminal. This shift is driven by the rise of “agentic” AI, capable of performing step-by-step reasoning and executing tasks beyond basic code generation. The terminal, long considered an old-school but powerful interface, is becoming the new frontier for AI interaction in software development.
Major AI labs such as Anthropic, DeepMind, and OpenAI have introduced terminal-based tools like Claude Code, Gemini CLI, and CLI Codex. Though they appear under familiar branding, these tools represent a major shift in how AI interacts with computing environments. Rather than focusing solely on fixing broken code, these tools handle broader system tasks — marking a new phase in the evolution of developer-AI collaboration.
This transition comes at a time when traditional code-editing tools are showing signs of stagnation. Windsurf, once a prominent player, is embroiled in corporate instability due to acquisitions and talent losses. Simultaneously, research from METR reveals a troubling discrepancy: developers using tools like Cursor Pro overestimate their productivity, when in fact, tasks often take longer. These factors have created space for terminal-centric platforms to take the lead.
Among them, Warp has emerged as a standout, topping the Terminal-Bench benchmark — a rigorous testing platform designed to evaluate agent performance in complex, real-world environments. Unlike code editors focused on isolated bug fixes, terminal-based agents tackle multifaceted system-level tasks, from compiling Linux kernels to solving compression challenges. These tasks simulate the broader scope of problems developers face in practice.
While no tool has fully mastered the complexities of the terminal, the progress is notable. Warp, for example, can now autonomously set up projects and identify configuration issues — something traditional editors struggle with. Developers and companies alike are increasingly seeing the terminal not just as a backend tool, but as the next logical interface for AI-driven development. As agentic models evolve, the command line could soon become the dominant medium for human-AI software engineering partnerships.
Source: Techcrunch