Introduction
The age of AI coding tools has fully arrived. Beyond terminal-first tools such as Claude Code, Gemini CLI, and Codex CLI, a wide range of AI editors and agents including Cursor, Kiro, Open Code, Jules, and Nano Banana are competing for developer attention. Each tool has a different philosophy and different strengths, so choosing the right one for your workflow matters.
This article compares the major tools based on hands-on use.
1. Cursor: The Front-Runner Among AI Coding Editors
Cursor is a fork of VS Code with deeply integrated AI capabilities. It was the first AI coding editor to reach broad adoption and, as of 2025, remains one of the most widely used.
Core Features
- Inline autocomplete: predicts and suggests the next line as you write code
- Chat: talk to the AI in a sidebar to modify or generate code
- Composer: request large multi-file changes in natural language
- Debug Mode: automatically analyzes runtime logs to trace bug causes
Key Points from Cursor 2.2
Released in December 2025, Cursor 2.2 introduced a new debugging paradigm:
- Debug Mode: collects and analyzes runtime error logs automatically, then proposes root causes and fixes
- Multi-Agent Judging: lets multiple models compete and selects the best result
- Visual Editor: visualizes code structure with Mermaid diagrams and supports visual editing
- Plan Mode: plans work and executes it step by step
Installation and Setup
After downloading from the official site, you can migrate your VS Code settings and extensions directly. In addition to the default models, you can connect your own API keys to use Claude, GPT, and others.
Finding the Best Settings
The best Cursor configuration depends on the project. In environments such as React projects, defining project-specific AI behavior in a .cursorrules file helps make outputs more consistent.
2. Kiro: Leading Spec-Driven Development
Kiro is an AI coding tool from Amazon (AWS) that proposes a distinct approach called Spec Driven Development (SDD).
What SDD Means
Traditional AI coding tools follow a "prompt -> code" workflow. Kiro instead follows "spec -> code":
- Write requirements in natural language
- Kiro converts them into a structured spec document
- Review and approve the spec
- Generate code from the approved spec
The advantage is that the team agrees on what to build before code generation begins. Compared with generating code directly from a one-line prompt, this usually produces results that are more accurate and better aligned with intent.
Agent Hooks and Steering
Kiro's Agent Hooks are similar to Claude Code Hooks: they define actions that run automatically on specific events. Steering configures the AI's behavioral direction and can be thought of as Kiro's equivalent of CLAUDE.md.
Real-World Example: Building a RAG Development Environment
A case study that used Kiro to build a RAG-based application environment showed a clear benefit: the spec document acts as a blueprint that keeps the project direction stable.
3. Open Code: A Free Open Source AI Coding Tool
Open Code (oh-my-opencode) is an open source AI coding CLI. Unlike Claude Code or Codex CLI, it is completely free as a tool and lets users connect a wide range of LLMs.
Core Advantages
- Free: the tool itself is fully free; you only pay for the LLM API you use
- Model freedom: supports open source or low-cost models such as Ollama, Qwen3, GLM-4, and MiniMax M2.1
- Multi-model support: also works with commercial models such as Claude, OpenAI, and Gemini through API keys
Installation
npx oh-my-opencode
Its base commands and slash-command UX are similar to Claude Code.
Z.ai GLM Integration
If you connect a Z.ai GLM model from China to Open Code, you can run AI coding workflows at very low cost. It is a practical alternative when Claude Code feels too expensive.
Recommended Use Cases
- Learning: experiment with AI coding without worrying about tool cost
- Low-cost projects: economical AI coding on small projects
- Open source model exploration: run local LLMs with Ollama and compare models
4. Jules: Google's AI Coding Agent
Jules is Google's AI coding agent built on Gemini models. Its defining characteristic is direct GitHub integration, letting it process issues automatically or generate pull requests.
5. Nano Banana: A Korean AI Coding Tool
Nano Banana is a Korean-developed AI coding tool optimized for Korean prompts. It is drawing attention in the Korean developer community, with Korean-language documentation and local community support as major strengths.
6. Overall Comparison
| Tool | Type | Strengths | Weaknesses | Cost |
|---|---|---|---|---|
| Cursor | Editor | VS Code-based, rich feature set | Subscription cost, dependent on VS Code | Paid ($20/month) |
| Claude Code | CLI | Skills, Memory, MCP, 1M context | Dependent on Anthropic | Included in Max plan |
| Kiro | Editor | SDD workflow, spec-based development | Still early-stage | Free (beta) |
| Open Code | CLI | Free, broad model support | Community-driven | Free |
| Codex CLI | CLI | OpenAI ecosystem, autonomous coding | Dependent on OpenAI | Paid |
| Gemini CLI | CLI | Google ecosystem, ADK integration | Dependent on Google | Has a free tier |
7. Which Tool Should You Choose?
Three criteria matter most:
- Ecosystem: if you already use Claude, Claude Code is a natural fit; if you are in the OpenAI stack, Codex CLI fits more naturally
- Cost: if budget is tight, start with Open Code plus open source models
- Development style: choose Cursor or Kiro for editor-centric work, and Claude Code or Codex CLI for terminal-first work
The important point is not to become locked into a single tool. We are entering a period where SKILL.md-style configuration works across multiple tools, so it is better to build the ability to switch tools based on project needs.
Closing
AI coding tools are no longer "nice to have." They are becoming table stakes. But the tool itself is less important than the ability to collaborate with AI effectively. No matter which tool you use, the core skill is the same: define the problem clearly and provide the AI with the right context.
If you are hesitant to start, Cursor is an easy first experience. If you later need deeper workflow integration, moving to Claude Code or Codex CLI is a practical next step.