Cursor has been (almost) the hottest AI coding IDE since 2024, beloved for its intuitive graphical user interface (GUI). So it came as a surprise when they launched their own terminal interface tool, Cursor CLI, in August 2025!
The current landscape of CLI and terminal-based AI coding tools includes:
- Gemini CLI: Google’s open-source AI coding assistant powered by the robust Gemini 2.5 Pro model, supporting multimodal input and massive context windows for large codebases and complex tasks
- Claude Code: Anthropic’s CLI AI specializing in high-quality automated agent programming and multi-file editing
- OpenAI Codex CLI: Built on OpenAI’s GPT series, supporting local execution, code testing, and Git integration for rapid prototyping and private code management
- Aider: Focused on DevOps and CI/CD pipeline automation, helping developers accelerate deployment and batch operations in the terminal
- Warp: Emphasizes terminal and shell productivity enhancement through accelerated command input and auto-completion, though not specifically focused on complete AI-generated code
- Cursor CLI: Supports multi-model switching, connects GUI IDEs (like VSCode) with terminal environments, combining real-time coding assistance with Git context integration for hybrid workflows
- Rovo Dev: An emerging AI coding CLI tool emphasizing cross-platform compatibility and lightweight, efficient coding assistance for developers seeking rapid iteration
This presents a fascinating paradox: if GUI-based AI coding tools like Cursor are so powerful and user-friendly, why are big techs like Anthropic, Google, and OpenAI investing heavily in command-line versions of AI coding tools?
This phenomenon reflects evolving trends in software development needs, which sparked my curiosity to investigate further. Today, I’ll share my observations and insights that I believe will reshape your understanding of the AI coding tools market and inspire your choices about which new tools to learn.
Terminology clarification:
Terminal refers to the interface window where you interact with your computer, typically featuring white text on a black background. Terminals operate through text-based communication rather than mouse-driven GUI interactions. CLI stands for Command Line Interface: a method of operating computers through text-based commands. Think of the terminal as the phone itself, while CLI represents the conversation you have.
Since CLI operations primarily occur within terminals, this article will treat CLI and terminal as synonymous terms.
From IDE to CLI: The New Battleground of AI Coding Tools#
The Success Story of Cursor’s IDE-Based Tools#
First, let’s acknowledge that Cursor and similar Integrated Development Environment (IDE) AI coding tools have achieved remarkable success. Cursor gained millions of users within a year, with valuations skyrocketing into the billions. Cursor essentially equipped traditional code editors with AI intelligence, making programming as conversational as chatting with a friend. Beyond software engineers, designers, product managers, and others can now create functional software through Cursor.
For non-professional programmers, Cursor’s advantages are clear:
- Visual Interface: Beautiful graphical interface where a few mouse clicks and natural language input generate code, lowering psychological barriers
- Real-time Suggestions: Provides suggestions while coding, like having a programming instructor beside you. It’s perfect for learning new syntax
- User-Friendly: No special commands to learn; point and click to get started. I could create running programs on day one
Importantly, Cursor supports multiple large language models, including OpenAI, Anthropic, and Gemini, offering flexibility to choose the most suitable AI assistant for different tasks. It’s like having a toolbox filled with AI experts of various specializations.
Tech Giants’ “Counter-Intuitive” Investment#
While GUI/IDE tools enjoy widespread success, tech giants simultaneously invest heavily in seemingly more “primitive” command-line AI coding tools:
- Anthropic’s Claude Code: Operates in black-and-white terminals but delivers exceptionally powerful agent functionality
- Google’s Gemini CLI: Another command-line interface focused on optimizing developer workflows
- Cursor’s CLI Version: Also developing in this direction with significant R&D investment
At first glance, this resembles investing in flip phones during the iPhone era. However, this represents a strategically shrewd deployment:
The programming tools market is vast enough, with sufficiently diverse demands, to justify resource investment in serving different customer segments in a rapidly growing market.
According to market research, the AI coding tools market is projected to reach hundreds of billions by 2030, with annual growth rates of 20-25%. In this massive programming tools market, different developer types have vastly different needs and preferences. There’s no single tool type that can satisfy everyone.
The market demand for command-line tools (CLI) among professional developers is evident from observable indicators:
- NeoVim (a powerful terminal text editor operating purely through keyboard input) has over 90,000 GitHub stars
- tmux (enabling developers to run multiple sessions simultaneously in one terminal window) has nearly 40,000 stars
- Other modern CLI tools are rapidly rising, including Rust-based command-line tools like ripgrep (search), exa (file listing), and bat (file viewing), each garnering tens of thousands of GitHub stars
The active communities around various command-line development tools indicate substantial numbers of developers prefer terminal environments. These professional developers typically serve as key influencers in technical decisions, with their choices affecting entire teams or company tool adoption.
Simultaneously, programming’s fundamental nature is evolving: from “hand-coding” to “directing AI agents to code.” In this transformation, terminal-based pure text communication interfaces prove more suitable for deep AI collaboration.
These factors explain why tech giants invest in CLI AI coding tools, ensuring competitiveness across every market segment. From Cursor’s perspective, while successful in IDE/GUI space, they can’t ignore the CLI market opportunity. For instance, months ago when a Reddit user suggested Cursor should release a CLI, other users recommended switching to Claude Code or Warp instead. Cursor’s team likely observed this trend and couldn’t watch users leave due to lacking CLI interfaces!
At this point, users who love Cursor, Windsurf, or VS Code GUI tools naturally wonder: What’s so great about programming in terminals?
Advantages of Terminal Development#
Professional Developers’ Preferences#
A segment of developers genuinely loves frantically typing in terminals to write code, and they’re incredibly loyal!
According to the 2024 Stack Overflow Survey, while VS Code remains the most popular editor, 83% of NeoVim (terminal editor) users want to continue using it next year (higher than VS Code’s 77% loyalty rate). Terminal development interfaces have some die-hard fans!
(Source: Stack Overflow 2024)
Even as a Vim enthusiast myself, this data amazes me, revealing that many programming experts prefer terminal environments. Like professional chefs preferring traditional woks over modern non-stick pans, “primitive” tools don’t signify backwardness. Sometimes they represent more precise control and higher efficiency.
From my conversations with senior engineer friends, their reasons for choosing terminal development typically include:
- Speed Advantage: Pure keyboard operation vastly outpaces mouse clicking (I’ve been converted to Vim enthusiasm!)
- Automation Capabilities: Easy script writing for automating repetitive tasks
- System Integration: Direct system command access, seamless tool integration
- Low Resource Consumption: No complex GUI rendering required, smoother operation
- Freedom: Compatible with any editor, unrestricted by tools or environments
I particularly appreciate deep system integration functionality. Placing AI in terminals enables direct system command access (Git version control, database operations, file management), like giving AI “omnipotent hands” that can manipulate everything. For example, Claude Code not only writes code but automatically generates Git commit messages, pushes to remote repositories, and even creates Pull Requests. This end-to-end automation remains difficult (currently) in GUI tools.
Recognizing these demands, tech giants developing AI tools realize they can’t simply wait for all developers to adopt their graphical interfaces. Instead, they must proactively design CLI-based AI coding tools to meet specific software engineer communities’ terminal development needs.
First-Hand Insights from Claude Code’s Creator#
Claude Code undoubtedly leads CLI AI coding tools, so I particularly focused on their core development team’s perspectives. Boris Churney, Claude Code’s creator, stated in an interview that Claude Code’s design philosophy is crystal clear:
“You don’t have to adopt new tools, you don’t have to use new IDEs, you don’t have to use a particular website or anything.
—Claude Code works wherever you work.”
This sounds simple but represents profound philosophy. While many AI coding tools aspire to become the sole hegemon, Claude Code takes the opposite approach, seeking to become an invisible assistant through terminal integration.
Boris describes terminals this way:
“The terminal is almost like the most universal of all the interfaces in that it’s flexible, and it’s incorporated into everybody’s workflow already.”
His perspective made me reconsider what “advanced” means. Sometimes, the most advanced isn’t the most feature-rich or complex, but what best adapts to various environments, what naturally integrates into users’ work and life.
From my personal experience, this flexibility proves invaluable. I can write code in my preferred editor, then call Claude Code from the same terminal window to improve code, whether I’m in VS Code, R Studio, or PyCharm. I can always access Claude Code through the terminal. This seamless integration feels like having an invisible programming partner always ready but never intrusive to your workflow rhythm.
IDE vs. CLI: Choosing the Right AI Coding Tool for You#
IDE Tools: Perfect for Beginners and Visual-Oriented Workers#
IDE and CLI interface AI coding tools offer similar functionality but serve completely different user groups. If you fit the following situations, Cursor or Google Colab IDE/GUI tools would be better choices:
- Data Scientists: Using myself as an example, daily work primarily involves writing SQL analysis scripts and Python/R statistical models, requiring visual feedback for rapid result validation. When I use Google Colab for data visualization, I immediately see chart effects and adjust parameters in real-time. This instant feedback + modification loop proves essential for exploratory analysis.
- Product Managers and Business Personnel: Occasionally need to modify code or create prototype apps to validate ideas without learning excessive technical details. Cursor’s visual interface lets them focus on functional logic rather than programming syntax details. Cursor enables PMs to “communicate with engineers in the same language.”
- Entrepreneurs and Independent Developers: Want rapid MVP (Minimum Viable Product) creation (time is money 💰). Cursor enables entrepreneurs to see results quickly with low learning curves, avoiding distraction from complex command-line operations.
- Heavy Team Collaboration Users: If you frequently explain code logic to colleagues, Cursor’s visual diff views and real-time collaboration (Live Share) features facilitate easier communication.
(While this article uses Cursor as the IDE example, for data scientists, Google Colab offers not only graphical interfaces but also data analysis agents, making it an excellent AI coding and analysis tool)
CLI Tools: Perfect for Professional Developers and Efficiency Seekers#
If you fit the following situations, Claude Code or Gemini CLI terminal tools would better suit you:
- Backend Engineers and System Administrators: Comfortable working in terminal environments, daily interactions with servers, databases, and APIs. For these professionals, graphical interfaces might actually be burdensome.
- DevOps Engineers: Require extensive automation operations including continuous integration, containerized deployment, and infrastructure management. CLI tools’ scripting capabilities enable easy creation of complex automation workflows.
- Senior Full-Stack Developers: Full-stack capable developers typically have substantial experience with established development environments and tool chains, preferring not to be locked into specific IDEs. CLI tools’ flexibility allows compatibility with any editor (VS Code, Sublime Text, even Vim).
- Extreme Efficiency Seekers: If you’re already a heavy keyboard shortcut user who prefers pure keyboard operation, CLI tools will feel natural.
- This is me. I simply love keyboard typing! As mentioned in my previous article, pure keyboard terminal operation makes me feel mysteriously accomplished (?)
Conclusion: Embrace Change, Stay Curious#
Big techs simultaneously investing in both IDE/GUI and CLI AI coding interfaces reflects that no single tool can satisfy everyone’s needs. This teaches us that in our rapidly changing world, product design lacks universal standards—diversity and inclusivity matter more.
I believe those reading this article, like myself, are simply AI users. For us, what matters most isn’t debating which tool is superior, but maintaining open minds and choosing appropriate tools based on our needs. I’ve seen too many people harbor tool biases (even engaging in online flame wars), missing efficiency improvement opportunities. I’ve also seen many blindly pursue new tools while neglecting fundamental skill development.
True professionals flexibly choose tools based on specific situations rather than being enslaved by any single tool. I remember a senior engineer (whose source I’ve forgotten) once saying:
“The best tool is one that makes you forget it exists, letting you focus on solving problems”
Who knows? In two months, entirely unimaginable new AI coding tools might emerge! Perhaps someday we’ll code using VR headsets? Regardless, as the old saying goes: the only constant is change itself.