Zed AI is a terminal-based AI coding assistant that pairs with the Zed editor, and here's how to actually use it without getting in your own way.
Zed AI has been gaining traction among full-stack developers who want AI assistance without leaving their editor. Unlike cloud-based tools that require context-switching, Zed AI runs inside the editor's native interface, giving you inline completions, chat, and agentic edits where you're already working. I've been testing it against my daily TypeScript and Node.js workflows, and it holds up surprisingly well for a tool that's still evolving.
Why Zed AI Matters (and When to Skip It)
Zed AI matters because it compresses the feedback loop. You ask for a change, see the diff inline, and accept or reject it without opening a browser tab. That's genuinely faster for mechanical refactors and boilerplate generation.
But skip it if you're on a shared machine or a strict security posture. Zed AI sends code snippets to its servers for processing, and that's a dealbreaker for some enterprise environments. Also, if you're already heavily invested in GitHub Copilot's multi-file suggestions or Cursor's agentic workflows, Zed AI might feel redundant rather than complementary.
Getting Started with Zed AI
You'll need the Zed editor installed—Zed AI is a feature of the editor, not a standalone CLI. Here's the minimal setup:
# Install Zed on macOS (Linux/Windows builds are on the roadmap)
brew install --cask zed
# Open Zed, then install the AI extension from the Extensions panel
# You'll need an OpenAI API key or an Anthropic API key
# Set it in: Settings > AI > API Key
Once configured, open a TypeScript file and try your first inline edit. Select a function, press Cmd+K, and type a natural-language instruction:
// Select this function and ask Zed AI to "add input validation"
export async function createUser(email: string, password: string) {
const response = await fetch("/api/users", {
method: "POST",
body: JSON.stringify({ email, password }),
});
return response.json();
}
Zed AI will generate a diff you can accept or reject with a single keystroke. That's the core loop—fast, inline, and reversible.
Core Zed AI Concepts Every Developer Should Know
Inline edits are the bread and butter. They work on selections, not whole files. For a full-stack dev, that means you can target a single route handler or a single database query without worrying about the AI rewriting your entire file.
// Select this and ask: "convert to async/await"
function getUser(id: string) {
return db.query("SELECT * FROM users WHERE id = $1", [id]).then(r => r.rows[0]);
}
// Zed AI produces:
async function getUser(id: string) {
const result = await db.query("SELECT * FROM users WHERE id = $1", [id]);
return result.rows[0];
}
The chat panel is for broader questions. Press Cmd+Shift+K to open it. You can reference your current file, paste errors, or ask about architecture. It's less powerful than a standalone LLM chat because it's context-aware but not infinite-context.
Agentic mode is the risky one. Zed AI can execute multi-step changes across files when you give it a high-level task. Use it sparingly—it's great for "add pagination to all list endpoints" but it can also introduce subtle bugs across your codebase.
Context is everything. Zed AI uses your open files, selection, and recent edits as context. If you want better suggestions, keep relevant files open in adjacent tabs. That's a habit worth building.
Common Zed AI Mistakes and How to Fix Them
Mistake 1: Not reviewing diffs before accepting. I've seen devs accept a refactor that silently changed a === to == because they trusted the AI. Always scan the diff—it takes two seconds and saves you a debugging session.
Mistake 2: Using agentic mode for critical paths. If a file touches authentication, payments, or data migration, don't let Zed AI rewrite it unsupervised. Use inline edits there and reserve agentic mode for scaffolding or tests.
Mistake 3: Ignoring the context window. Zed AI doesn't see your whole repo. If you ask it to refactor a function that depends on a utility in another file, it'll hallucinate a fix. Keep the dependency file open, or paste the relevant snippet into your prompt.
When Should You Use Zed AI?
Use Zed AI when you're doing repetitive, well-defined transformations—converting callbacks to async/await, generating test stubs, or renaming variables across a file. It's also solid for writing boilerplate CRUD endpoints if you give it a clear schema.
Skip it when you need deep architectural reasoning, when you're working with legacy code that has non-obvious invariants, or when you're in a flow state writing novel logic. The interruption cost of AI suggestions can outweigh the speed gain.
Zed AI in Production
For real projects, keep these three tips in mind:
First, pin your model version. Zed AI lets you choose between GPT-4o and Claude, but if you don't pin it, you'll get silent upgrades that change behavior mid-sprint. Pin it in your project's .zed/settings.json:
{
"ai": {
"model": "gpt-4o",
"inline_edits": true
}
}
Second, write a .zed/ai.md file in your repo root. This gives Zed AI project-specific instructions—your coding style, your linting rules, your testing conventions. It's like a system prompt for your codebase.
Third, use Zed AI for code review, not just generation. Paste a diff into the chat panel and ask "what edge cases am I missing here?" It's surprisingly good at catching null-pointer dereferences and race conditions you've glossed over.
One more thing: if you're building a team tool, check out suhailroushan.com for patterns on integrating AI assistants into CI pipelines—there's overlap between what Zed AI does locally and what you can automate server-side.
The takeaway: adopt Zed AI for inline edits and code review, keep agentic mode off for critical paths, and pin your model version on every production project.