Posted on Jun 3

Beyond the Hype: A Look at 5+ AI Coding Agents for Your Terminal

If you're looking to supercharge your development workflow on the terminal, you've got options – lots of 'em. But which one's right for you? I've been tinkering with a bunch, and here's my take on some of the key players.

If you enjoy this post, give my project Uzi a star on GitHub – it's a CLI tool that helps you run multiple AI coding agents in parallel, making it easier to manage your coding tasks.

OpenAI Codex CLI & Anthropic's Claude Code

Alright, let's kick things off with the heavyweights. OpenAI and Anthropic, the multi-billion dollar giants, are throwing serious manpower and cash at these coding assistants. If you're not a hardcore terminal nerd and just want something that works and boosts your productivity ASAP, these are your first stop. OpenAI's gone open-source with Codex CLI, while Anthropic's keeping Claude Code under wraps. The community's been vibing more with Claude Code lately, but don't count Codex CLI out – that open-source muscle could mean big things as the community jumps in.

OpenAI Codex CLI (Open Source)

OpenAI's offering, Codex CLI, aims to bring their powerful reasoning models straight to your terminal. Being open source is a big plus here, opening the door for community contributions and transparency.

Key Functionality:

Zero‑setup installation: A quick npm install -g @openai/codex and you're off.
Multimodal inputs: Feed it text, screenshots, or diagrams.
Rich approvals workflow: Choose your level of hand-holding with Suggest, Auto Edit, or Full Auto modes.
Runs entirely in your terminal: No context switching needed for quick iterations.

Getting Started:

Install:
```
npm install -g @openai/codex 
```
Authenticate:
```
export OPENAI_API_KEY="<OAI_KEY>" 
```
Run:
```
codex "Explain this repo to me." 
```

While it has the potential to be more powerful and cheaper than some alternatives, the developer experience has been a bit rough around the edges, with some users (myself included) noting issues with model selection, API key management, and occasional crashes. Still, its open-source nature means it's one to watch.

Anthropic's Claude Code (Closed Source)

On the other side, we have Claude Code from Anthropic. This one's proprietary, but it has garnered a lot of praise for its design and usability.

Key Strengths (from community observations and my experience):

Well-designed and intuitive CLI: It just feels good to use.
Automatic codebase understanding: Gets up to speed with your project quickly.
Project settings can be saved: Speeds up future sessions.
Active internal development: Suggests a commitment to quality and future improvements.
Handles complex requests well: Especially in larger codebases, it seems to shine.

It's not without its downsides; being closed-source is a factor for many, and it can get pricey. However, if you're looking for a polished experience and deep codebase understanding out-of-the-box, Claude Code is a strong contender. Many, including myself, have found it particularly effective for more complex tasks.

Plandex & Aider

Now, if you're the type who loves to tinker and really get under the hood, Plandex and Aider are where things get interesting. These tools are definitely more opinionated. They demand a bit more from you upfront – expect a steeper learning curve as you dive into their docs and unique command sets. But master them, and you'll unlock some serious power. Keep in mind, these came onto the scene before the giants fully flexed their muscles with Codex and Claude, so it'll be fascinating to see how they adapt. My bet? They'll carve out niches by getting super precise and targeted. Both are open source, which is great for customizability.

Plandex v2 (Open Source)

Plandex is designed for large tasks and real-world projects, offering a terminal-based AI development tool that can plan and execute multi-step coding endeavors.

Standout Features:

Smart context management: Claims a 2M token effective context window and handles large projects/files well.
Cumulative diff review sandbox: Keeps AI changes separate until you're ready.
Model combination: Mix and match models from Anthropic, OpenAI, Google, etc.
Configurable autonomy: From full auto to fine-grained control.
Automated debugging: For terminal commands and even browser applications (with Chrome).
Project-aware chat mode: Flesh out ideas before implementation.
Git integration: With commit message generation.

Installation:

curl -sL https://plandex.ai/install.sh | bash

(Note: Windows support is via WSL.)

Plandex offers different hosting options, including a cloud service and self-hosting. It emphasizes resilience in large projects and a robust workflow. If you're tackling complex, sprawling tasks, Plandex aims to be your heavy lifter.

Aider (Open Source)

Aider lets you pair program with LLMs directly in your terminal, focusing on seamless integration with your existing codebase and Git workflow.

Core Features:

Broad LLM support: Works well with Claude 3.7 Sonnet, DeepSeek, OpenAI models, and can connect to local models.
Codebase mapping (repomap): Helps it understand context in larger projects.
Multi-language support: Python, JavaScript, Rust, Go, and many more.
Git integration: Automatically commits changes with sensible messages.
IDE integration: Use aider --watch to have it react to comments in your code.
Image and web page input: Provide visual context.
Voice-to-code: Speak your requests.
Linting & testing: Can automatically lint, test, and fix issues.

Getting Started:

python -m pip install aider-install aider-install # cd /to/your/project # Example with DeepSeek: # aider --model deepseek --api-key deepseek=<key>

Aider has a strong focus on transparency and developer control, making it easy to see what the LLM is thinking and doing. Its repomap feature is a clever way to give the LLM better context. For those who like a tight feedback loop and clear insight into the AI's process, Aider is a compelling choice.

Opencode (Open Source)

Opencode is playing a different game, and honestly, it's one to watch. These folks might not have the VC backing of the big players, but they've got something equally valuable: serious social capital. We're talking big names on X like @adamdotdev and @thdxr championing this project. They're building Opencode with a clear vision – a high-quality tool for devs who live and breathe the terminal, think Arch Linux users and the like. This focus, combined with the community buzz, gives me a hunch they've got a real shot at long-term success. I'd put them as the dark horse with the second-best odds. It's also open source.

Key Aspects:

TUI Focus: Built with Bubble Tea for a slick terminal user interface.
Multi-Provider Support: Works with OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Groq, Azure OpenAI, and OpenRouter.
Session Management: Save and manage conversation sessions.
Tool Integration: AI can execute commands, search files, and modify code.
Integrated Editor: Vim-like text input.
LSP Integration: For code intelligence.
File Change Tracking: Visualize changes during sessions.

Installation (one of many options):

curl -fsSL https://raw.githubusercontent.com/opencode-ai/opencode/refs/heads/main/install | bash

Or via Homebrew:

brew install opencode-ai/tap/opencode

And for Arch users:

yay -S opencode-ai-bin

Opencode feels like it's built by terminal lovers, for terminal lovers. If you appreciate a well-crafted TUI and want a versatile tool that integrates deeply into a command-line workflow, keep a close eye on Opencode.

Uzi (Open Source)

So, after looking at all these individual agents, you might be wondering where the real leverage is. My gut tells me that trying to out-build OpenAI or Anthropic on their core agent tech is a bit like bringing a knife to a gunfight. They're just too big, too fast. That's why I think the next frontier isn't about building another agent, but about orchestrating the ones we've got. And that's exactly where Uzi comes in. We're building Uzi because, frankly, managing multiple AI agents, even the good ones, can be a massive pain. If you've ever tried to run several agents in parallel, as I detailed in my post on Git worktrees and AI, you know it's powerful, but clunky. Uzi is our open-source answer to that.

The core idea is to make parallelization easy. Why run one agent when you can run five, each tackling the problem in an isolated Git worktree, managed by Tmux? Uzi is a lightweight CLI that wraps this whole process.

What Uzi Does:

🤖 Runs multiple AI coding agents in parallel.
🌳 Manages Git worktrees automatically for isolated development.
🖥️ Handles Tmux session management for each agent.
🚀 Sets up development servers with automatic port management.
📊 Provides real-time monitoring of agent status.
🔄 Automates handling of agent prompts and confirmations.
🎯 Makes checkpointing and merging agent changes straightforward.

Prerequisites:

Git: For version control and worktrees.
Tmux: For terminal session management.
Go: For installing Uzi.
Your AI tool of choice: Claude, Codex CLI, Aider, etc.

Installation:

go install github.com/devflowinc/uzi@latest

Make sure $HOME/go/bin is in your PATH:

export PATH="$PATH:$HOME/go/bin"

Configuration (uzi.yaml):
Create this in your project root:

devCommand: yarn dev --port $PORT # Example for a Node.js project portRange: 3000-3010

The devCommand is crucial – it should include all setup steps like npm install as each agent runs in a clean worktree.

Basic Workflow Example:

Start agents:

uzi prompt --agents claude:3,codex:2 "Implement a REST API for user management"

Automate confirmations:
```
uzi auto 
```
Monitor:
```
uzi ls -w 
```

Broadcast a follow-up:

uzi broadcast "Ensure all endpoints are documented"

Merge work:

uzi checkpoint <agent-name> "feat: add user management API"

I genuinely believe that the future of AI-assisted development lies in parallel execution and smart orchestration. Instead of betting on a single agent to nail it every time, Uzi lets you hedge your bets, increasing your chances of getting a great solution faster. It's about making the existing powerful agents even more effective by streamlining the meta-work around them.

The landscape of AI coding tools is evolving at lightning speed. Hopefully, this rundown gives you a better idea of what's out there and helps you pick the tools that best fit your style!