Gemini Code Assist Versions: IDE vs. CLI

Effective software development often involves using the right tool for the right job. We use specific libraries for specific tasks and different application testing frameworks. The same principle applies to how we should approach using AI-powered collaborators.

While Gemini Code Assist operates under a single name, it is best understood as a suite of specialized assistants, each designed to excel in a different development context. Gemini Code Assist is accessible through two primary interfaces:

• A highly-integrated assistant living directly within our Integrated Development Environment (IDE), offering immediate, visual assistance on the code right before us.

• A powerful, agent-like tool that operates from our command-line interface (CLI), built for broader, project-level tasks and automation.

Knowing how and when to use each is the key to unlocking maximum productivity. In this lesson, we aim to explore the unique strengths of the IDE and CLI versions. We will learn how to identify the right context for each, enabling us to make intelligent choices that enhance our development workflow.

The in-editor partner: Gemini in the IDE

Most of our time as developers is spent in the IDE—writing, navigating, and debugging code. One of the biggest benefits of Gemini Code Assist is that it runs right inside the editor. You don’t have to break focus by switching to a browser for answers or documentation. Gemini can see the code you’re working on, understand its context, and give you help in place so that you can stay focused and productive.

To bring this power directly into our workflow, Google has made Gemini Code Assist available as an extension in the most popular development environments used today.

• Visual Studio Code: As one of the most widely used code editors, this is a primary platform for Gemini. Its lightweight nature and vast extension ecosystem make it a versatile choice for many developers.

• JetBrains IDEs: For developers invested in the powerful JetBrains ecosystem, Gemini is available for IDEs like IntelliJ IDEA (for Java and other JVM languages) and PyCharm (for Python), providing the same capabilities within that familiar environment.

• Android Studio: As the official IDE for native Android development, the integration of Gemini provides specialized assistance for mobile developers building on Google’s platform.

Key characteristics

Using Gemini in the IDE comes with a few key features, similar to working with a pair programmer. These include:

• Visually integrated: The assistance is not just text; it is a natural extension of the editor’s graphical interface. This includes inline ghost text for code completions, interactive lightbulb menus that appear next to our code, and diff views that show proposed changes directly within our file. The entire interaction is woven into the visual workflow we are already used to.

• Aware of IDE diagnostics: Gemini is uniquely able to leverage the IDE’s built-in static analysis and linting engines. When the editor flags an error or warning with a squiggly underline, Gemini is aware of that specific diagnostic. This is what enables it to offer context-aware “Quick Fix” solutions, positioning itself as the intelligent problem-solver for issues the IDE has already identified.

• Immediate and responsive: The interaction feels fluid and happens in real-time. The feedback loop is tight—it’s proactive, offering suggestions as we type, and reactive, making smart actions instantly available the moment we select a piece of code. This immediacy helps maintain our focus and momentum.

• Focused on your active context: The IDE assistant’s primary worldview is the code we are actively working on. It excels at understanding the local context (the variables, functions, and classes within our open files) to provide highly relevant and accurate assistance for the task at hand. Its strength lies in its deep understanding of a narrow, immediate scope.

• Conversational and iterative: The integrated chat panel enables a back-and-forth dialogue. We can ask for a change, see the result, and then ask for a refinement or clarification in the same thread. This allows us to iterate on a solution collaboratively, much like we would with a human colleague.

When to choose the IDE assistant

The IDE assistant excels at micro-level or in-file tasks where our focus is on the code directly in front of us. We should reach for the IDE version when we are:

• Writing new code or refactoring existing logic within a specific file.

• Trying to understand a complex function or class we are currently viewing.

• Generating unit tests or documentation for a specific piece of code.

• Fixing a syntax error or a bug that the IDE has highlighted in a file.

Think of the IDE assistant as our immediate pair programmer, ready to help with the task at hand without ever needing to look away from the screen.

The command line agent: Gemini CLI

While the IDE is the perfect environment for working within our code, many crucial development tasks involve managing files, automating workflows, and orchestrating project-wide changes. For this, we turn to the terminal. The Gemini command line interface (CLI) is an open source AI agent designed to bring collaborative intelligence directly to our shell, empowering us to perform complex tasks from a text-first interface.

Installed as a global npm package, the Gemini CLI is designed for developers who are comfortable working in a terminal and want to leverage AI for automation and large-scale operations.

Key characteristics

The experience of using the Gemini CLI is fundamentally different from the visual, copilot nature of the IDE assistant. Its power lies in its autonomy and its native integration with the terminal environment.

• Autonomous and goal-oriented: This is the most significant difference. In the IDE, Gemini acts as a copilot, augmenting our direct actions in real time. We select code, we type, and it assists, making the process highly collaborative. The CLI, by contrast, operates as a delegate. We do not collaborate with it on a step-by-step basis; instead, we provide it with a high-level, end-state goal and empower it to determine the necessary steps to achieve that outcome on its own. The focus shifts from real-time assistance to autonomous execution.

• Powered by a ReAct loop: This autonomy is driven by a process called a ReAct (Reason and Act) loop. The model reasons about the goal we have given it and determines the best action to take. It executes that action, observes the outcome, and then repeats the cycle (reasoning about the new state and choosing the next action) until the overall goal is complete.

• System-level tooling: The actions in the ReAct loop are performed using a set of built-in tools that mirror the capabilities of a terminal. Gemini can execute shell commands (like grep or ls), read and write to files, and even perform a web search to find information. It uses the output of these tools to inform its next step. This is what allows it to work across an entire file system, not just the files open in an editor.

• Text-first, conversational interface: All interaction with the Gemini CLI is through text in the terminal. It presents its plan, shows the commands it’s running, and provides a summary upon completion. This makes it ideal for keyboard-centric developers, for use in remote SSH sessions, and for integration into scripts.

When to choose the CLI assistant

The Gemini CLI is the ideal choice when a task is better framed as a delegated, automated workflow rather than a real-time collaboration on a specific piece of code. While there is some overlap in project-wide capabilities with the IDE’s agent mode, the CLI’s native environment is the terminal, and it excels at tasks that leverage that environment’s unique strengths. We should reach for the CLI specifically when:

• Automating project-wide tasks, such as scaffolding a new component with multiple files or searching the entire codebase to perform a complex refactor.

• Running and orchestrating other command-line tools (like Git, Docker, or gcloud) using natural language instead of memorizing complex commands and flags.

• Working in an IDE-less environment, such as when connected to a remote server via SSH or inside a minimal Docker container.

• Performing system-level analysis, like asking it to summarize the purpose of files in a directory or find all configurations that match a certain criteria.

In essence, if the task can be described as a script we might write or a sequence of commands we would manually type into our terminal, the Gemini CLI is the right tool. Think of it as our personal automation engine.

IDE vs. CLI: A quick comparison

Now that we’ve explored the individual characteristics of both the IDE and CLI assistants, a direct side-by-side comparison can help solidify our understanding. The fundamental difference lies not just in their capabilities, but in their entire philosophy of interaction. The following table highlights these key distinctions to help us build a clear mental model for choosing the right tool.

This table serves as a quick reference guide. With these distinctions in mind, let’s see how they play out in a single, unified development workflow.

Scenario: From remote debugging to deployment

To see the difference between the two versions, let’s consider a scenario. Say we need to fix a bug that only shows up in the remote staging environment, not on our local machine. Since the bug is remote, our investigation must begin in the terminal by connecting to the server via SSH. In this IDE-less environment, the Gemini CLI is our indispensable tool. We can delegate investigative tasks like analyzing server logs for errors and inspecting remote configuration files to identify the root cause of the issue.

After the CLI identifies the faulty function, we switch back to the local machine and open the project in the IDE. Now it’s a focused code change—the kind of task where the IDE assistant is most useful. We can use chat and built-in actions to refactor the code, add a unit test to confirm the fix, and make sure everything runs correctly, all within the editor.

Finally, with the code fixed and verified, the last step is deployment. Tasks like committing the code and building a new container are easier to hand off to the Gemini CLI, which can handle the git and docker commands autonomously from the terminal. In this workflow, each tool plays to its strength: the CLI for remote investigation and automation, and the IDE for hands-on coding.

The underlying connection

While we’ve looked at the IDE and CLI assistants separately, they’re actually two interfaces for the same underlying engine. The agent mode features that let the IDE handle project-wide refactors are powered by the same system as the Gemini CLI. Thinking of them this way shows they’re not competing tools, but parts of one system that gives you help whether you prefer a visual editor or a text-based terminal.

Learning a new tool isn’t just about knowing the features—it’s about building intuition for when and why to use them. By understanding how the Gemini suite fits together, you can pick the right kind of AI assistance for the task at hand. That flexibility makes it easier to stay productive and use AI naturally across your workflow.