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Zed + AI Zed + AI interface screenshot

Zed integrates AI to generate, transform, and analyze code with “Agentic Editing” and an inline assistant.

Pricing: Free with optional paid features API: Yes Rating: 4.40 Updated: 1 month ago
Ideal forDevelopers who value a snappy editor with multiplayer and lightweight, grounded AI help
Workflow stageOpen repo ? Chat/complete inline
Watch forUsage and model access may vary

Quick info about Zed + AI

Agentic editing

Work with agents to plan and apply code changes.

Inline assistant

Chat over selections and apply edits instantly.

Multiplayer

120fps real-time collaboration.

Is this the right AI tool for you?

0 / 500

Where Zed + AI shines

Zed is a fast, multiplayer code editor; Zed + AI adds repo-aware chat and completions that keep up with Zed’s speed. You can ask questions about your codebase, generate small functions/tests, and collaborate live with teammates while AI suggests edits—useful when you want instant feedback with minimal latency.

Common use cases:
Inline completions and small edits that match project style
Ask the assistant to explain files, types, and call chains with links
Draft tests and refactors, then pair-review in a live session
Summarize diffs and PRs before review
Onboard new teammates with guided “where is X?” queries
Strengths and sweet spots

Zed’s core strengths—low latency, minimal UI friction, and multiplayer editing—carry into its AI features. Completions arrive quickly and respect nearby code, while chat can cite files and jump you to definitions. In a live session, teammates see the same context and can co-edit while discussing AI suggestions, which shortens review cycles for small features and bug fixes. The editor’s tight terminal and Git integration keep you in flow: write, run, fix, commit.

For day-to-day work, Zed + AI is great at glue code (parsers, adapters), tests, and documentation updates, particularly when you ask for behavior first and let the model fill the mechanics.

Where it fits in your stack

Use Zed + AI as your everyday companion in a fast editor. Upstream, write intent in comments and TODOs, keep linters/types on, and pin toolchain versions so suggestions compile. Midstream, accept small changes you understand, run tests often, and use multiplayer sessions for pair programming and code review with context shared. Downstream, create clean PRs and keep the AI-generated parts clearly documented. For unknown areas, ask the assistant to map the call chain and to produce a short “how this module works” note for your docs.

If you work in a monorepo, combine Zed’s search with AI chat to jump between packages quickly and avoid dead ends.

What to watch out for

As with any LLM assistant, treat outputs as drafts. Enforce security and performance checks (input validation, SQL parameters, memory/allocations). Keep secrets out of prompts and repos. Large automated sweeps can create noisy diffs; prefer targeted changes. Ensure license policy compliance for generated code. For teams, agree on where AI is allowed (e.g., not in crypto/auth modules) and keep review standards unchanged.

At a glance

ic_fluent_system_24_filled Created with Sketch. Platforms

macOS (primary)others vary over time

API

public

Integrations

Built-in terminal and GitGitHub/GitLab PR flowscollaborative sessions with voice/text.

Export formats

Code diffsPR summarieschat notes

Coverage & data

Sources

  • Local files
  • repo search results
  • build/test outputs
  • user prompts.

Coverage

Fast completions

Update frequency

Frequent

Plans & limits

Free plan

Individual usage limits; some multiplayer/AI features may be gated.

Pro features

Team workspaces, longer context windows, admin controls, and higher AI quotas depending on plan.

Ads / tracking

Yes

Community signal

Mentions

Favored by developers who prioritize speed and pair programming; AI adds helpful context and drafting.

Compared to similar tools

Zed + AI couples a very fast, multiplayer editor with grounded assistance. Windsurf adds agentic planning/execution; Cody emphasizes search/citations over large repos; Copilot focuses on ubiquitous inline completion.

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