The ultimate guide to the terminal AI coding tool in 2025

Let’s be honest, the command line is cool again. For a while, it felt like fancy GUIs had taken over, but the terminal is making a comeback in a big way. And it’s not just for "cd"-ing through directories anymore. It’s now getting a serious AI boost, turning that familiar black-and-green window into a smart sidekick for developers.

More and more, developers are using a terminal AI coding tool to handle everything from spitting out boilerplate code to untangling complex bugs, all without ever having to switch windows.

This isn’t just about better autocomplete. The real magic comes from what people are calling "agentic AI." Think of these as little autonomous helpers that can understand your goal, map out a plan, and actually get the job done. This guide will walk you through the top tools out there, what they can (and can’t) do, and why you can’t just point them at any business problem, like customer support or IT tickets, and expect good results.

What is a terminal AI coding tool?

So, what are we actually talking about here? A terminal AI coding tool is a command-line application that uses a large language model (LLM) to help you write, fix, and manage your code right from the terminal. Instead of just guessing the next word you’re going to type, these tools feel more like having a junior developer you can bounce ideas off of in plain English.

Here’s a taste of what they can do for you:

• Code Generation: You can literally just tell it what you need. Ask for a function, a class, or even a whole file by describing its purpose, and it will generate the code for you.

• Debugging & Refactoring: If you’re stuck on a bug, you can ask the tool to take a look. It can often spot the problem, suggest a fix, or even help you clean up and restructure your code to make it more efficient.

• Automation: A lot of these tools can run commands for you, execute your test suite, and even manage your Git workflow. Some can write your commit messages or put together a whole pull request on their own.

This is a pretty big jump from the IDE extensions we’re used to. We’re moving beyond simple code suggestions to something that feels genuinely "agentic." These tools can understand the context of your entire project and string together multiple steps to help you get where you’re going, faster.

An overview of popular terminal AI coding tools

The scene for these tools is blowing up, but a few front-runners have already established themselves. Let’s take a look at the big names, what they’re good at, what they’re not so good at, and what they’ll cost you.

GitHub Copilot CLI

You’ve probably already heard of GitHub Copilot. Its CLI extension brings that same AI-powered help directly into your terminal. It’s less of an autonomous coding agent and more of an incredibly smart shell assistant that helps you wrangle commands more efficiently.

• Key Features:

  • It translates your plain-English requests into shell commands. For example, you can type "git log for the last 5 commits" and it will translate that into "git log -n 5".

  • It can explain what a confusing or unfamiliar command actually does before you run it, which is a lifesaver.

  • It integrates tightly with Git, suggesting commands and helping you write clear commit messages.

• Limitations: Copilot CLI is brilliant for navigating the command line and for Git tasks, but it’s not built to be an autonomous code editor. It helps you run commands, but it’s not going to refactor your entire app for you.

• Pricing:

  • Copilot Individual: $10 per month or $100 per year, which includes CLI access.

  • Copilot Business: $19 per user per month. This tier adds policy management for organizations.

  • Copilot Enterprise: $39 per user per month. You get more personalization and beefed-up security features.

Claude Code

Claude Code is Anthropic’s entry into the space, and it’s a dedicated, agentic terminal AI coding tool designed to handle messy, multi-step development work. It’s built to feel like a real pair programmer that can reason about your codebase and make some pretty significant changes.

• Key Features:

  • It can edit code across multiple files at the same time, all from a single prompt.

  • It has the ability to run tests and execute commands in your project’s environment to make sure its changes actually work.

  • It keeps the context of your entire codebase in mind, so you can ask it to do large-scale refactoring.

• Limitations: Claude Code is a premium tool, and it’s priced like one. Since it’s a closed-source product, you’re tied to their ecosystem. Developers have found that the pay-as-you-go API costs can creep up on you during a heavy coding session, which could be a problem for teams on a tight budget.

• Pricing: Pricing is based on Anthropic’s API usage. The latest Claude 3.5 Sonnet model runs at $3 per million input tokens and $15 per million output tokens. That can add up surprisingly fast when you’re going back and forth with the AI.

A view of the Claude Code terminal AI coding tool in action, showing how it interacts with the user within the command line.

Aider

Aider is a favorite in the open-source world. It’s a terminal AI coding tool that gives you the freedom to pair-program with a bunch of different LLMs. This is the tool for developers who want more control and flexibility.

• Key Features:

  • It works with your local codebase and automatically commits changes to Git with well-written, descriptive messages.

  • It’s super configurable. You can hook it up to models from OpenAI, Anthropic, Google, or even run local models on your own machine if you have the hardware.

  • It builds a map of your entire codebase, which gives the LLM much better context for making intelligent suggestions.

• Limitations: Being open-source, Aider takes a bit more effort to get running. You’ll need to install it and set up API keys for whichever model you want to use. The quality of its output also depends entirely on the LLM you choose and how good you are at writing prompts.

• Pricing: The tool itself is free to use. You only pay for the API fees from your chosen LLM provider, like OpenAI or Anthropic.

This video demonstrates how Claude Code, a powerful terminal AI coding tool, operates directly within the terminal to enhance coding workflows.

Limitations of terminal AI coding tools

These tools are genuinely incredible for software development. But the very thing that makes them so good at writing code, their specialization, is also their biggest weakness. The moment you try to use them for business problems outside of coding, you’ll hit a wall. They are simply the wrong tool for jobs in customer support, sales, or IT service management.

Here’s why.

Purpose-built for code, not conversations

The AI models behind these tools have been fed a diet of billions of lines of code from places like GitHub. They’re fluent in Python, JavaScript, and shell scripts, but they don’t have the slightest clue how to interpret a support ticket from a frustrated customer or an IT request from a confused employee. They speak programming languages, not the language your business runs on.

The integration gap

A terminal AI coding tool is designed to work with local files, Git, and shell commands. It doesn’t have the simple, one-click integrations needed to connect with the platforms that actually run your business. You can’t ask Aider to "find this customer’s order status in Shopify" or tell GitHub Copilot CLI to "figure out what’s going on with this urgent Zendesk ticket." Those systems just aren’t part of its world.

Lack of business-specific workflows

Support and IT work is about more than just generating text. It involves taking specific actions, like tagging a ticket correctly, escalating an issue to a senior team member, updating a customer’s details in a CRM, or drafting a new help center article after solving a problem. Coding agents aren’t built to handle these very specific, multi-step business tasks.

The simulation and safety problem

Unleashing an untested AI on your live customer support queue is a recipe for disaster. Coding agents don’t come with a "simulation mode" that lets you safely test how they’d handle thousands of your past support tickets. There’s no way to know what your resolution rates will look like, how accurate the AI will be, or where its knowledge gaps are before you let it talk to real customers.

Beyond the terminal: Applying agentic AI to support and IT with eesel

The good news is that the power of agentic AI isn’t stuck in the terminal. The same ideas of automation, context-awareness, and task execution can be applied to other parts of your business, but you need a tool that was built for that specific job.

eesel AI is basically the equivalent of a terminal AI coding tool, but designed from the ground up for support and IT teams. It lives where your team works, inside help desks like Zendesk and Freshdesk, or in chat tools like Slack, and it’s built to solve their unique problems.

Here’s how it tackles the limitations of the coding-focused tools:

It connects to your business stack in minutes

Instead of Git and compilers, eesel AI offers one-click integrations with the platforms that power your business, including Intercom, Confluence, and Google Docs. It’s a self-serve platform you can get up and running in a few minutes, not months, and you won’t need to pull a developer off a project to do it.

It learns from your unique business knowledge

While coding tools learn from public code repositories, eesel AI trains on your private business data. It digs into your past support tickets, internal wikis, help articles, and macros to learn your company’s voice, processes, and solutions right from the start.

It gives you total control with custom actions and workflows

With eesel AI’s fully customizable workflow engine, you can do a lot more than just send back text replies. You can create custom actions to look up order information via an API, triage tickets based on what they’re about, or automatically escalate complex problems to the right people. You get fine-grained control over exactly what the AI does and when.

It lets you test with confidence

This is a big one. eesel AI’s simulation mode lets you safely test your AI on thousands of your historical tickets. This gives you a clear forecast of your potential automation rate and shows you exactly how the AI will respond to customers before you flip the switch. It makes the whole process completely risk-free.

Final thoughts on the terminal AI coding tool

The rise of the terminal AI coding tool is proof that smart, agentic AI is here and is already changing how we work. These tools are completely reshaping how software gets made. But the real key to getting the most out of this technology is picking the right, purpose-built agent for the job at hand, whether that’s refactoring an old codebase or resolving a customer’s issue.

Take control of your support automation

Developers are using terminal AI to build things faster. Your support and IT teams deserve that same kind of power.

See how eesel AI can automate your frontline support and internal Q&A with a platform you can set up yourself in minutes. Try out the simulation mode and see what your ROI could look like today.

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