Z

Zed Industries

Collaborative code editor with CRDT synchronization

Overview

Zed.dev provides a collaborative code editor for software teams, featuring real-time multi-user editing, hierarchical channels, and shared documents for chat, planning, and project tracking. It uses Conflict-Free Replicated Data Types (CRDTs) to keep code and notes in sync as edits happen, supported by a multi-threaded architecture that works for both solo and team work. It differentiates itself with CRDT-driven synchronization, integrated collaboration tools, and the ability to jump to teammates’ locations, follow work, switch roles for reviews, and share screens during external collaboration. Its goal is to offer reliable, high-performance collaborative coding tools through a subscription-based model that unlocks premium features for development teams.

Significant Headcount Growth

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About Zed Industries

Simplify's Rating
Why Zed Industries is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Enterprise Software

Company Size

51-200

Company Stage

Series B

Total Funding

$42M

Headquarters

Boulder, CO

Founded

2021

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What believers are saying

  • Delta public beta launched September 16, 2026, widening product discovery across desktop, web, mobile.
  • Zed disabled pull requests internally and shipped 570 main-branch changes through Delta.
  • Zed pricing now includes Business at $30 per seat, unlocking enterprise revenue.

What critics are saying

  • GitHub remains Zed’s distribution choke point while public repos still use pull requests.
  • Cursor Origin and GitLab Project Switch directly attack Zed’s collaboration thesis in 2026.
  • Delta’s free beta delays monetization; a weak paid conversion kills independent scaling.

What makes Zed Industries unique

  • Zed’s Rust editor delivers low-latency collaboration unavailable in Electron-based IDEs.
  • DeltaDB and threads replace pull requests with persistent, code-linked review context.
  • Former Atom founders ship multiplayer editing, agent workflows, and built-in review tooling.

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Funding

Total Funding

$42M

Below

Industry Average

Funded Over

2 Rounds

Series B funding is typically for startups that have proven their business model and need more funding to expand rapidly—often by entering new markets or adding more products. Investors are usually venture capital firms that specialize in later-stage investments.
Series B Funding Comparison
Meet Average

Industry standards

$35M
$32M
$45M
$65M
$100M

Benefits

  • Remote Work Options

Growth & Insights and Company News

6 month growth

10%

1 year growth

6%

2 year growth

3%
TechNewsDaily
Nov 4th, 2026
Zed 0.160 and the shift in GPU-native editor economics.

Zed 0.160 and the shift in GPU-native editor economics. Zed outperforms VS Code and Cursor in performance, opening an 85,000 file TypeScript monorepo in just 180 milliseconds. The editor uses GPUI for low latency and offers a $10 monthly Pro tier, providing a cost-effective alternative to Cursor's $30 premium pricing. Zed uses GPUI to render directly on the GPU. This bypasses the Chromium abstraction layer that slows down VS Code and Cursor. Engineers notice the difference when they open large files. Zed opened an 85,000 file TypeScript monorepo in 180 milliseconds. VS Code took 3.1 seconds to show the UI and 10 seconds to reach full LSP readiness. Cursor required 3.4 seconds for the UI and 11 seconds for the language server. Zed consumed 240 megabytes of RAM with the same project. VS Code used 680 megabytes, while the memory requirement for Cursor was 780 megabytes. Developers who prioritize low latency find that Zed maintains input latency under 12 milliseconds even when a language server indexes a massive project, which provides a distinct advantage over Electron-based editors like VS Code or Cursor. Zed uses Tree-sitter to build an abstract syntax tree for every file. This provides accurate syntax highlighting and intelligent code navigation. Because the editor uses a multi-thread-friendly copy-on-write B-tree buffer, multiple threads can read the buffer without locking. It also lets AI agents and human collaborators operate on the same file without conflict. The editor maintains a sustained 120 frames per second even when opening files with hundreds of thousands of lines of code. Zed provides edit prediction using the Zeta2 model. This model predicts entire changes at keystroke granularity. The free tier provides 2,000 accepted predictions per month. Users can also use their own API keys for Anthropic, OpenAI, or local Ollama models. Multiplayer editing in Zed uses CRDTs as a core primitive. This allows teammates to see cursors, selections, and terminal output in real time. You share a project URL and a colleague joins the session. Zed runs multiple AI agents in parallel within the same window. One agent refactors a component while another writes unit tests for a different module. You direct these agents using prose in the Agent Panel or the Inline Assistant. This workflow reduces the time spent typing prompts. The cost for Zed Pro is $10 per month, which includes $5 of tokens. In contrast, Cursor changed its pricing on October 12, 2026, and now charges $30 per month for the Premium tier. Cursor includes Grok models in this price, but Claude and GPT usage requires extra payments at API list prices. Does the integration of specialized voice dictation layers like Aqua solve the input bottleneck for agent-heavy workflows? The Zed issue tracker contains a request for dictation in the Agent Panel that remains in the "Planned" state. The microphone icon in Zed is for voice chat with teammates but does not perform speech-to-text. Users wanting to dictate prompts use system-wide tools like Aqua, which uses the Avalon model that placed first on the OpenASR leaderboard in October 2025. Zed implements the Model Context Protocol to allow external tools to extend agent capabilities. You can pipe any file, symbol, or command output into context using slash commands to gain direct control over the context window. For teams that pair regularly, Zed's multiplayer infrastructure works better than Microsoft's remote pairing tools. The collaboration server is written in Rust using the Axum framework, and you can self-host this backend with a PostgreSQL database and a LiveKit server. This suits enterprises with strict requirements about code data residency. Teams choose editors based on specific technical needs. Small teams working in Rust, Go, or TypeScript often select Zed to minimize latency and AI costs. Larger enterprises prefer VS Code because of its massive extension marketplace and mature remote development tools. Cursor remains the choice for teams that want highly polished agentic features. Pricing varies significantly between providers. VS Code Copilot Individual costs $10 per month, while Copilot Business is $19 per seat and Copilot Enterprise is $39 per seat. Cursor Business costs $40 per seat. The cost for Zed Pro is $10 per month, and Zed Business is $30 per seat. Developers who want to avoid extra AI bills can point the Zed free plan at Claude Agent or Codex CLI using their own keys. VS Code remains the leader for remote development via SSH and Devcontainers. Zed's SSH remoting mode is still maturing and some language servers do not behave well over the link. Zed's Vim mode is more faithful to the original than the extensions used by VS Code and Cursor. Pick Zed if your team values speed and pair programming. For those wanting the most polished agent mode, pick Cursor. If your workflow depends on the massive extension ecosystem of VS Code, pick that instead.

Conversion Table
Sep 19th, 2026
AI firms prioritize infrastructure over model improvements.

AI firms prioritize infrastructure over model improvements. September 19, 2026 · By Cordelia Ashcombe The cost of running AI models continues to decline, but the focus of competition has shifted away from the models themselves. This week's developments from Zed, Anthropic, and OpenRouter highlight why the surrounding software infrastructure now holds greater importance than the models at their core. Five of the week's most-read stories centered on a single theme: transforming AI models into practical tools for users. This involves the harness - the collection of tools, interfaces, and systems that provide context, link external services, direct tasks, and validate results. While model performance still dominates headlines, companies are increasingly directing investment toward the infrastructure that enables real-world AI applications. Zed introduces Delta threaded review system. Zed introduced Delta in public beta, a system designed to replace traditional pull requests with shared discussion threads. The concept is straightforward: code reviews should not require handling between fragmented diffs and scattered comments. Delta keeps conversations directly tied to the codebase, while DeltaDB tracks changes at a granular level - down to individual edits. Nathan Sobo, Zed's CEO, framed the transition by saying the industry is currently focused on rebuilding code collaboration. His argument centers on how traditional diffs reveal only the final state of changes while obscuring the reasoning behind them. Delta addresses this by maintaining a continuous thread of discussion alongside the code. Internally, Zed's team implemented 570 modifications to Delta's main branch without submitting a single pull request, a claim supported by the company's repository data. While the public Zed editor continues to accept pull requests, the direction is clear. GitHub's commit surge highlights collaboration demand. In contrast, GitHub reported 2.9 billion monthly commits in August, up from 1.4 billion in April. Even accounting for an eight-hour service disruption that month, the figures demonstrate Git's enduring dominance in developer workflows. Yet the demand for modernization is rising. Competitors such as Cursor's Origin and GitLab's Project Switch are also rethinking collaboration tools to accommodate AI-assisted development. Anthropic adopted a different strategy by merging its Claude Chat and Cowork interfaces into a single system. This eliminates the need for users to determine upfront which tool best suits a given task. The company said people used both tools and found the decision-making process frustrating. The update is initially available to Pro and Max subscribers, with broader access planned for later. OpenRouter offers Conversion Table-based routing service. This shift reflects broader economic pressures. Companies are prioritizing the layers surrounding AI models over the models themselves. For example, OpenRouter recently made its US in-region routing service generally available for business clients. The platform decrypts, processes, and delivers requests within U.S. data centers - or rejects them if compliance requirements cannot be met. Open models dominate usage, closed systems retain revenue. Open-weight models now account for 60% of OpenRouter's U.S.-based token consumption, with Chinese models like DeepSeek V4 Pro, Kimi K3, and GLM 5.2 driving significant demand. However, the country of origin and processing location remain distinct considerations. OpenRouter's value lies in granting companies control over the latter - a critical factor as 77% of businesses now evaluate an AI solution's country of origin when selecting vendors, according to a Deloitte survey. Stripe's reported $8 billion acquisition of OpenRouter shows the strategic importance of this infrastructure layer. Economic trends support this focus: Vercel's September AI Gateway Production Index shows open-weight models now handle 56% of token volume on its platform, up from 7% in December 2025. Despite this usage, they generate only 14% of estimated spending, while closed models such as Anthropic's Claude dominate revenue despite lower adoption rates. Teams processing over 10 million tokens monthly experienced a 7.6% reduction in per-token costs in August, following a 2.9% decline in July. The downward trend in inference pricing accelerates, but the true expense lies in the harness, the connectors, authentication systems, and observability tools required for scalable AI deployment. Real-SWE benchmark shows agent success rates. A benchmark from Specific Labs, called Real-SWE, assessed coding agents on real-world tasks drawn from private repositories. The top-performing setup, a Claude Fable 5.1 model accessed through Claude Code, succeeded in 38.8% of cases. GPT-6 Astra, when used via Codex CLI, achieved 33.8%, while Gemini 3.8 Flash through its CLI reached 31.2%. No configuration exceeded 40% success. Abhilash Rao Mesala, a Meta data engineer, outlined a practical solution in a recent guide: LLM response caching. By reusing responses when requests, context, permissions, and underlying data remain unchanged, teams can achieve substantial cost reductions. His example begins with 1 million monthly calls priced at $0.006 each, totaling $6,000. With a 60% cache hit rate and $150 in additional embedding and vector-store expenses, the total drops to $2,550, a 57.5% savings. This approach leverages a principle predating transformer models. Vercel's AI Gateway Production Index for September exposed a deeper economic divide. While open-weight models now account for 56% of all requests on the platform, closed models still capture 86% of estimated spending. This discrepancy reveals that enterprises are willing to pay premiums for consistency, even when cheaper alternatives exist. Anthropic's Claude alone represents 64% of estimated spending among closed models, despite GPT-6 Astra, launched just 12 days before the report, accounting for only 7.7% of the total. The cost of inference itself continues to fall. This marks the third consecutive monthly reduction, with Vercel reporting a 23.2% year-over-year decrease in average token pricing. The trend accelerates the push toward harness solutions, tools that manage, optimize, and secure AI interactions rather than the models themselves. Boris Renski, CEO of Apelogic, summarized this shift in a recent interview: "Companies are buying the harness around inference now, and Zed, OpenRouter, and Anthropic all spent this week selling it." The Cloud Native Computing Foundation (CNCF) reinforced this perspective, noting that enterprises now treat AI integration as an infrastructure challenge rather than a model-centric concern. The Specific Labs Real-SWE benchmark further illuminated the harness challenge: even the highest-performing agents struggle with real-world tasks. The test, conducted on private codebases, showed that Claude Fable 5.1, the top performer, succeeded in only 38.8% of attempts. GPT-6 Astra and Gemini 3.8 Flash trailed further, with none surpassing 40%

The Machine Herald
Sep 18th, 2026
Zed launches Delta public beta, betting agent threads can replace GitHub pull requests.

Zed launches Delta public beta, betting agent threads can replace GitHub pull requests. Zed released a public beta of Delta, a collaboration tool built around AI-agent "threads" and a new DeltaDB versioning layer meant to replace GitHub pull requests. Verified pipeline | Sources: 4 | Publisher: signed | Contributor: signed | Hash: 01e8873cff | View Overview. Zed, the company behind the open-source Zed code editor, released the public beta of Delta on September 16, a collaboration tool built around AI coding agents that replaces GitHub's pull-request review model with shared, persistent "threads," according to Zed's announcement and The New Stack. Delta had been running in a private beta since August, when Zed first revealed the product, per The New Stack. What The Machine Herald know. * Threads instead of pull requests. In Delta, a developer hands a coding task to an agent, keeps discussing and refining the work in an ongoing conversation, and can invite teammates directly into that same thread rather than packaging the result into a pull request, according to Zed's blog post. Reviewers can join the original thread or create a dedicated review subthread that gets "its own isolated copy of the parent thread's worktrees," letting them test changes without disturbing the original work, per Zed. * DeltaDB underpins the system. Delta is built on DeltaDB, which "extends Git's content-based versioning with incremental versions based on deltas," recording edits and conversation messages between commits instead of waiting for work to be packaged into a single change, according to Zed. Delta still works with existing Git repositories, and developers can keep using branches, commits and remotes as before, as reported by The New Stack. * Zed has already gone all-in internally. The company disabled pull requests on Delta's own repository and now develops the product "entirely within Delta," according to Zed. Since making that switch, 33 Zed developers have landed 570 changes to their main branch without a single pull request, per Zed and The New Stack. Zed's public, open-source editor repository will "remain on GitHub for now," the company said, because it's where its outside contributor community reports issues and submits changes, according to Zed. "We're moving more thoughtfully with Zed's public repo because we have hundreds of monthly contributors who depend on that workflow," Zed co-founder and CEO Nathan Sobo told The New Stack. "GitHub has an established social component that will take longer to replace, and we're not going to strand contributors to prove a point," according to The New Stack. * Availability and pricing. Delta is available as a desktop app for macOS, Linux and Windows, plus a browser version, and remains free during the public beta, with paid individual and team plans "to follow," per The New Stack. "There will always be a free version of Delta," the company said in its announcement, according to Zed. * Company background. Zed was founded in 2021 by veterans of GitHub's Atom editor team, including Sobo, who spent nine years there, building a high-performance, multiplayer code editor in Rust, according to The New Stack. Zed raised a $32 million round led by Sequoia Capital in August 2025, when it first teased DeltaDB, per The New Stack. * The reasoning behind Delta. Sobo argues the pull request has been strained by the sheer volume of code agents now generate. "Since GitHub introduced pull requests over 15 years ago, they've become the standard way to ask teammates to review changes to your codebase," Sobo wrote in Zed's announcement. "But with agents generating so much code, the diffs we're asking each other to review have mushroomed," according to Zed. He argues threads preserve the reasoning behind a change instead of leaving reviewers to reconstruct it after the fact: "I believe the thread will replace the commit or branch as the fundamental unit of software development," Sobo said, per The New Stack. * GitHub's growing strain. Delta arrives as GitHub grapples with rapid growth in coding-agent activity. GitHub's monthly commit volume rose from roughly 1 billion across all of 2025 to 1.4 billion a month by April, then to 2.9 billion commits a month by August, according to The New Stack. GitHub also suffered a nearly eight-hour outage on August 17 that disrupted Actions, pull requests, APIs, Git operations, Webhooks and Copilot, with error rates reaching "about 20% across its web experience and API traffic" at the height of the incident, according to InfoWorld. * Not the only contender. Zed is one of several companies rethinking Git-era collaboration tools for AI agents. Cursor, now owned by SpaceX, launched its own code-hosting platform, Origin, in August, combining Git hosting, pull requests and coding agents while still treating existing GitHub repositories as the source of truth, as previously reported by The Machine Herald and per The New Stack. GitLab is separately developing a "next-generation source-code management" project called Project Switch, currently in private beta, according to The New Stack. What The Machine Herald don't know. * Sobo said Zed is "a few months away" from leaving GitHub behind for its own internal use, but gave no firm date, according to The New Stack. Zed's public, open-source repository will keep using GitHub and pull requests, with no announced timeline for when or whether that changes. * Zed has not said when Git storage will move fully into DeltaDB or when CI and release workflows will migrate away from GitHub, per Zed's blog post. * Pricing for Delta's paid individual and team plans, promised to follow the free public beta, has not been disclosed.

Drift Catch
Aug 31st, 2026
Tool Radar: local-first tools and the export test.

Tool Radar: local-first tools and the export test. August 31, 2026 · Last updated 2026-08-31 · By Drift Catch Drafted with AI assistance, reviewed before publishing. Welcome back to Tool Radar, its running note on the adjacent tools worth a freelancer's attention - the AI you draft with, the editor you ship from, the design app you mock up in. Not other freelance-management apps; the rest of your stack. Nobody pays to be here, and this is not a review site. It is the kind of message Drift Catch would send a freelancer friend who asked "what should I be paying attention to right now?" The filter this week: can you get your data out? Every tool below passes one unglamorous test: if its maker disappeared tomorrow, you could still open your files and take them with you. That is the second question Drift Catch bring to every tool, and it earns its own edition this week because the tools that changed recently happen to be the ones that answer it well. The first question is the one Drift Catch ask about everything: does it remove a decision, or does it just add a tab? A good tool folds a recurring choice into a default. A bad one demos well and then sits open in a browser tab you forget about by Thursday. A tool you can walk away from is working for you, not the other way around. Hold both questions against every tool below - and against anything anyone recommends to you. Ollama: drafting with AI that stays on your laptop. Ollama shipped v0.32.15 on August 19, adding a first-launch onboarding flow to its desktop app and caching that makes a model start responding noticeably faster on repeat runs. The freelancer angle is not the speed bump - it is where the drafting happens. Ollama runs language models locally, on your own machine, so the client names, rates, and project details you paste into a draft never leave your laptop. If you have ever hesitated before pasting a client's brief into a cloud tool, that hesitation is the whole point. New cloud models keep landing at a pace that is hard to keep up with, and most of them are genuinely capable. But the question a freelancer can actually act on is not "which model is best this month" - it is "where does my client's information go when I use it." A local runner is one clean answer. This is also the shape Drift Catch trust for AI inside its own product: its AI-Assisted Drafting on templates produces a draft that a human reviews before anything goes out. Draft, then review - whether the model runs in the cloud or on your desk. Zed: a code editor that now reads your spreadsheets. Zed's v1.17.2 release on August 26 added built-in previews for CSV, TSV, and similar delimited files - sortable and resizable columns, row filtering by value, and right-click copying - alongside new Git blame and stashing actions. For a freelance developer, this quietly removes a decision. A client sends a data export; instead of opening a separate spreadsheet app to eyeball it, you read it where you already are. And Git blame is underrated as a record: it answers "when did this change, and in which commit" without you writing a paragraph from memory. When a project starts to drift, that history is evidence of what you actually did and when. Zed is developed in the open on GitHub, which is the export test passing in the background - the thing you write is a plain file in a repo you control, not a document trapped in someone's cloud. Penpot: design files developed in the open. Penpot's current 2.17 line moved the prototype viewer to a WASM (Skia) rendering engine in 2.17.0 (July 22), and the most recent release, 2.17.2 (August 27), is a maintenance and security update rather than a headline feature. So there is no shiny new thing to chase this week - and that is fine. The durable reason a visual freelancer might keep Penpot on the radar is the same export test: it is built in the open on GitHub, and your design files stay yours to move. A slow-news week for a tool you can walk away from is a good problem to have. The freelancer reading here mirrors the developer one above: the tool that keeps a clear, portable history of what you delivered and when is doing double duty. It speeds up the work, and it quietly documents it - which matters the moment a client says "go back to the version from last week." The gap none of these tools touch. The agreement around the work - what was promised, what counts as extra, and when you get paid - is the one thing none of the tools above manage, no matter how portable your files are. Your editor, your AI runner, and your design app all help you do the work. They stay silent on the deal. That silence is the entire reason Drift Catch exists. Drift Catch is glad for the rest of your stack to be the best it can be, and Drift Catch do not connect to any of it - Drift Catch just want the business side to stop leaking. If "small extra requests that were never agreed to" sounds familiar, that pattern has a name - scope creep - and there is a calmer way to handle it: writing it down. Its guide on how to write a change order is the practical version of that. And if keeping your own data close is a running theme for you, its note on privacy-first freelance software explains how Drift Catch think about it on its side of the fence. This is general information, not legal or financial advice. Drift Catch run Tool Radar regularly. If there is an adjacent tool you think every freelancer should know about, tell Drift Catch at [email protected] - Drift Catch read every message, and good suggestions tend to show up in a future edition.

TheToolPicker
Aug 11th, 2026
Zed editor v1.14: default sandboxing for agent panel tools enhances security.

Zed editor v1.14: default sandboxing for agent panel tools enhances security. Zed version 1.14 introduces default sandboxing for agent panel tools, enhancing security and stability for developers. Learn about this crucial update and its implications. Zed, a popular code editor, has rolled out version 1.14, introducing a significant security upgrade: default sandboxing for its agent panel tools. This feature aims to isolate potentially untrusted code, thereby improving the overall security and stability of the development environment. Why it matters. Sandboxing creates a secure, isolated environment for running code, preventing it from affecting the main application or your operating system. This is particularly crucial for agent panel tools, which might process external data or user-generated code. The new default sandboxing in Zed ensures enhanced security against malicious code, improves application stability by containing errors, and builds greater trust for developers integrating various tools. This update is a significant step forward for developer tools, ensuring a safer experience. Potential drawbacks. While sandboxing offers substantial security benefits, it can sometimes introduce performance overhead. Developers utilizing custom agent panel tools might also need to adapt their code to function correctly within the new sandboxed environment. Zed's official documentation should provide guidance on any necessary adjustments for developers. Explore more about code editors to see how Zed compares. Final thoughts. The introduction of default sandboxing in Zed version 1.14 is a commendable step towards a more secure development experience. This update reinforces Zed's commitment to user safety and system integrity. Developers looking for secure coding environments might find Zed's approach appealing, especially when integrating various third-party or custom tools, similar to how secure browsers protect user data.

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