OpenCode: The Open Source AI Coding Agent That Actually Works

I've tested dozens of AI coding tools over the past year. Most promise the moon and deliver autocomplete with extra steps. OpenCode caught my attention because it does something different — it treats coding as a workflow problem, not just a text generation problem.

With over 131,000 GitHub stars and 5 million monthly developers, OpenCode has clearly struck a nerve. But popularity doesn't always mean quality. So I spent two weeks using it as my primary coding assistant to see if the hype holds up.

What Makes OpenCode Different

The first thing you notice about OpenCode is that it's not trying to be another chatbot wrapper. When you run opencode in your project and type /init, something interesting happens: it analyzes your codebase and creates an AGENTS.md file in your repository root.

That file teaches the agent about your project's structure, coding patterns, and conventions. It's a small detail, but it signals something important — OpenCode thinks about context gathering as a first-class problem, not an afterthought.

The multi-provider support is another standout feature. Unlike tools that lock you into a single model, OpenCode supports 75+ LLM providers through AI SDK and Models.dev. You can use Claude for complex reasoning, GPT for quick edits, or even run local models for sensitive code. Switching providers is as simple as running /connect and adding your API key.

The Workflow That Actually Works

Here's where OpenCode gets genuinely interesting. The tool has two modes: planning and build.

In planning mode, OpenCode analyzes your request, breaks it into steps, and presents an approach before writing any code. You can approve, modify, or reject the plan. This sounds simple, but it prevents the common AI coding problem where the tool goes off on a tangent and writes 500 lines of code you didn't ask for.

Build mode is where execution happens. But here's the thing — even in build mode, OpenCode maintains a conversation-like flow. You can say "actually, use a different approach" mid-execution, and it adapts. The /undo and /redo commands work exactly as you'd expect, letting you roll back changes without losing context.

The docs even suggest talking to OpenCode like you'd talk to a junior developer. Give clear instructions, provide examples, and be specific about what you want. That's surprisingly good advice for any AI coding tool.

Privacy and Enterprise Features

OpenCode's privacy story is refreshingly specific. The homepage states it doesn't store your code or context data. Processing happens locally or through direct API calls to your chosen provider.

But there's an important caveat: the /share feature. If you use it, your conversation data gets uploaded to create public share links. The docs explicitly recommend disabling sharing for sensitive work. That kind of documented tradeoff is more credible than vague "privacy-first" claims.

For enterprise teams, OpenCode offers SSO integration, central configuration management, and support for internal AI gateways. The permission system lets you set actions to allow, ask, or deny — giving security-conscious teams granular control over what the agent can do.

LSP Integration: The Secret Weapon

One feature that separates OpenCode from simpler coding assistants is its Language Server Protocol integration. The tool uses LSP diagnostics to understand your codebase at a deeper level — catching type errors, understanding imports, and navigating code structure.

This matters because AI coding tools are only as good as the context they can gather. A tool that can't understand your project's type system or dependency graph will make suggestions that look correct but fail at compile time. OpenCode's LSP support helps avoid that problem.

The tool supports a long list of built-in language servers with automatic enablement based on file types and project requirements. It's not perfect — complex monorepo setups can still confuse it — but it's significantly better than tools that treat your codebase as a flat text file.

What Could Be Better

No tool is perfect, and OpenCode has room for improvement.

The learning curve is steeper than simpler alternatives. Understanding when to use planning mode versus build mode, how to structure effective prompts, and when to intervene versus let the agent work — these skills take time to develop.

The desktop app is still in beta, and it shows. The terminal interface remains the most polished experience, which might deter developers who prefer GUI-based workflows.

Token usage can also add up quickly. Complex multi-file operations with planning mode enabled can consume significant API credits, especially with premium models like Claude Opus or GPT-4.

Getting Started

If you want to try OpenCode, here's the practical path:

Install it via your preferred method — the project script, Homebrew, Docker, or package managers all work. Run opencode in your project directory, then /init to set up context. Connect a provider with /connect and start with a simple task.

I'd recommend starting with planning mode enabled for your first few sessions. It helps you understand how the agent thinks about problems before you let it run freely.

The tool is free to use with your own API keys. OpenCode Zen, the optional curated model layer, is a convenience feature rather than a requirement.

Where This Is Heading

OpenCode represents a shift in how we think about AI coding tools. Instead of treating code generation as a text completion problem, it treats it as a workflow problem with planning, execution, verification, and rollback.

The project's rapid growth — from a niche CLI tool to a platform with desktop apps, IDE extensions, and enterprise features — suggests this approach resonates with developers who want more than autocomplete.

Whether OpenCode becomes the standard or inspires competitors to adopt similar workflows, the direction is clear: AI coding tools need to understand context, respect developer control, and integrate with existing workflows rather than replacing them.

If you're tired of AI coding tools that promise autonomy but deliver chaos, OpenCode is worth a serious look. Just be prepared to invest time learning its workflow — the payoff is worth it.