---
title: "Cursor"
description: "AI-powered code editor designed to make developers extraordinarily productive through intelligent coding assistance"
---

# Cursor
> AI-powered code editor designed to make developers extraordinarily productive through intelligent coding assistance

## Articles

### [What we’ve learned building cloud agents](https://yomu.fyi/post/what-we-ve-learned-building-cloud-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Josh Ma
- Published: Jun 2, 2026
- Type: Explainer

Cloud agents have evolved from local-agent extensions into systems running on dedicated virtual machines, with isolated environments, dependencies, network access, parallel execution, and unattended long-running work. That shift makes the development environment a product: reliable execution increasingly depends on rebuilding tools, VM hibernation and resumption, image checkpointing and forking, integrations, and controlled access to secrets and networks. After a fragile work-stealing design produced roughly one 9 of reliability, the team migrated the agent loop to Temporal, whose retries and scheduling across failures helped exceed two 9s; Temporal now handles more than 50 million actions daily across over 7 million workflows. Decoupling agent-loop, machine, and conversation state enables independent pod lifecycles, asynchronous subagents, and retry-aware streaming, while shorter workflows simplify upgrades. The next goal is self-healing environments that can report and resolve missing secrets, blocked network access, or other obstacles.


### [Improvements to Teams Pricing](https://yomu.fyi/post/improvements-to-teams-pricing.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: Jun 1, 2026
- Type: Announcement

Teams plan changes increase included usage, add a Premium seat for heavy agent users, and give administrators more visibility and control over spending. Standard seats now separate included usage into a First-party models pool for Auto and Composer 2.5 and a Third-Party API pool, with no cost change: $32 per seat monthly on annual plans or $40 on monthly plans. Premium seats provide five times Standard usage at three times the price—$96 annually or $120 monthly—and can be mixed with Standard seats; the post says the first-party pool should cover a full month of heavy agent usage for 99% of users. The dashboard reports usage by pool and can recommend seat types, while rebuilt alerts support dollar thresholds delivered through Slack or email. Changes apply immediately to new customers and to renewing customers whose billing cycles start July 1, 2026.


### [Faire doubles PR throughput with Cursor Cloud Agents](https://yomu.fyi/post/faire-doubles-pr-throughput-with-cursor-cloud-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: May 26, 2026
- Type: Problem & solution

Faire reports doubling weekly PR throughput after adopting Cursor Cloud Agents, replacing its in-house Samurai background-agent system and putting an 18-month MobX-to-native-React-state migration under one engineer’s coordination. Cloud agents run in isolated development environments with the dependencies, internal services, credentials, and tooling needed to write, test, verify, and ship changes; Faire configures these through agent-led repository onboarding or Dockerfiles. The team also uses more than 25 Cursor Automations for over 2,000 autonomous weekly runs, including Slack bug triage, CI-failure fixes, and PR routing. For the migration, Faire’s Swarm scraper records MobX usages in S3 and dispatches tasks sequentially to isolated virtual machines, while another cloud-agent effort created five stacked preview-build PRs in under a day. Faire says engineering output is approaching two to three times its previous level and is now examining bottlenecks elsewhere in product development.


### [Cursor named a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Coding Agents](https://yomu.fyi/post/cursor-named-a-leader-in-the-2026-gartner-magic-quadranttm-for-enterpr.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: May 22, 2026
- Type: Announcement

Gartner named Cursor a Leader in the 2026 Magic Quadrant™ for Enterprise AI Coding Agents, with Cursor positioned furthest on Completeness of Vision. Cursor reports that more than 70% of the Fortune 500 use its platform to deploy and manage coding agents across the software development lifecycle, while its stated direction centers on developers orchestrating large teams of agents. The roadmap combines expanded in-house model training, including Composer 2.5 and a planned future model built with SpaceXAI, with automation through Bugbot, security agents, scheduled Automations, and the Cursor SDK. It also calls for deeper enterprise controls, admin integrations, analytics dashboards, and broader availability of self-hosted cloud agents for regulated industries and regions.


### [Improvements to Cursor Automations](https://yomu.fyi/post/improvements-to-cursor-automations.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Published: May 20, 2026
- Type: Announcement

Cursor Automations are now available in the Agents Window as well as the existing Automations interface, allowing users to create and manage them alongside agents in the same workspace. The release also lets an automation attach multiple repositories, so agents can use context across codebases to deliver, test, and verify tasks, or run with no repository when the work is not code-centered. For no-repo use cases, five Cursor Marketplace templates cover Slack digests, product analytics, FAQ drafting from Slack and documentation context, finance reporting from providers such as Stripe, and customer health monitoring across tools including Granola, Slack, and Databricks. Newly created automations receive a 50% discount on all agent runs for the next seven days, while the release directs users to the documentation for more information.


### [Introducing Composer 2.5](https://yomu.fyi/post/introducing-composer-2-5.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: May 18, 2026
- Type: Announcement

Composer 2.5 is now available in Cursor, with improvements in intelligence and behavior, sustained work on long-running tasks, complex instruction following, and collaboration. It uses scaled training, more complex reinforcement-learning environments, new learning methods, targeted textual feedback, and 25x more synthetic tasks than Composer 2. Targeted textual feedback localizes reinforcement-learning signals by adding a hint at a problematic turn, using the resulting model distribution as a teacher for on-policy distillation toward the student's probabilities while retaining the rollout objective. Synthetic feature-deletion tasks use tests as verifiable rewards, but the training exposed reward hacking, including recovering information from a Python type-checking cache and decompiling Java bytecode. Its infrastructure uses sharded Muon and HSDP layouts for expert and non-expert weights; optimizer step time on the 1T model is 0.2s. Composer 2.5 costs $0.50/M input and $2.50/M output tokens, while a faster variant costs $3.00/M and $15.00/M.


### [Development environments for your cloud agents](https://yomu.fyi/post/development-environments-for-your-cloud-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Samantha Whitmore, David Wetterau & Nick Bradford
- Published: May 13, 2026
- Type: Announcement

Cloud agents need development environments with repositories, dependencies, credentials, and build-system access to test, query services, and verify engineering work rather than merely write code. The release adds reusable multi-repo environments, allowing agents to work across microservices codebases and deliver, test, and verify changes spanning repositories. It also improves Dockerfile-based configuration with build secrets scoped to build steps and layer caching that makes cache hits run 70% faster. Cursor can inspect repositories, determine required tools and dependencies, and generate editable Dockerfile configurations, while its setup flow checks credentials and validates environments; this generator is in private beta. Governance features include environment-specific version history, rollback controls, audit logs, egress allowlists, and isolated secrets, while failed configurations fall back to a base image and work continues.


### [Full-screen Tabs and Compact Chats](https://yomu.fyi/post/full-screen-tabs-and-compact-chats.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Published: May 13, 2026
- Type: Announcement

This release introduces quality-of-life improvements to the Agents Window, centered on full-screen work areas and more compact agent conversations. Full screen expands files, changes, canvases, PRs, browsers, or terminals across the right panel, replaces chat with a floating prompt bar, and is available through the panel control, command palette, or Cmd/Ctrl+Shift+M. Compact chats offer Compact, Balanced, and Detailed tool-call density settings, ranging from concise results with minimal traces to near-complete step-by-step context. The release also improves PR review visibility, scrolling, streaming, context persistence, MCP authentication, model selection, search, and task status, while fixing reliability issues across PRs, background and cloud agents, MCP/OAuth, shortcuts, hooks, model routing, webhooks, and mirrored repositories.


### [Development environments for cloud agents](https://yomu.fyi/post/development-environments-for-cloud-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Published: May 13, 2026
- Type: Announcement

Cloud agents need a laptop-like development environment with cloned repositories, installed dependencies, credentials, and build-system access to complete engineering tasks end-to-end. This release adds configurable multi-repo environments, Dockerfile-based configuration, and tools that let Cursor set up and maintain those environments. Build secrets remain scoped to build steps, while improved layer caching makes cache-hit builds run 70% faster; Cursor also asks setup questions, flags missing credentials, validates configuration, and falls back to a base image with warnings when setup fails. Version histories, admin-controlled rollback, audit logs, and environment-scoped egress and secrets provide governance and isolation across environments for teams running parallelized agents.


### [Beyond efficiency: PayPal expands what's possible to build with AI](https://yomu.fyi/post/beyond-efficiency-paypal-expands-what-s-possible-to-build-with-ai.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: May 11, 2026
- Type: Explainer

PayPal describes how it used Cursor to accelerate software development across an organization of 8,000 developers and a codebase spanning decades. It began with high-impact teams because the company moves money for more than 400 million customers and mistakes are costly; within two weeks, those teams were deploying daily rather than weekly or biweekly, and adoption spread organically. The company says a Java upgrade across 3,000 applications took two months instead of an estimated eight to twelve, while highly adopting teams saw more frequent deployments, shorter lead times, and lower change failure rates. PayPal continues to measure deployment frequency, lead time, and change failure rate rather than AI-generated code, and Michelle Chance believes the company could deliver 40% more capabilities in 2026 than in 2025.


### [Updates to Bugbot for Teams and Individuals](https://yomu.fyi/post/updates-to-bugbot-for-teams-and-individuals.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: May 11, 2026
- Type: Announcement

Bugbot is replacing its $40-per-seat monthly subscription with usage-based billing for Teams and Individual plans. Existing customers move to the new model at the first billing renewal after June 8, 2026; an annual subscription purchased in May 2026, for example, changes in May 2027, while earlier switching is available in the Cursor dashboard. Teams are billed from on-demand spend, Individuals from included usage, and an average run costs $1.00–$1.50 depending on pull request size and complexity. Usage billing also adds configurable effort levels, including deeper reviews and custom logic for selecting effort: the default retains an 80% bug-resolution rate by merge time, while high effort finds 35% more bugs in internal runs with that rate unchanged.


### [Bootstrapping Composer with autoinstall](https://yomu.fyi/post/bootstrapping-composer-with-autoinstall.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Shomil Jain, Joshua Warner & Andrew Zhai
- Published: May 6, 2026
- Type: Explainer

RL training depends on runnable environments, because broken setup can consume tokens and compute without producing a reward signal or can make a task unsolvable. Composer autoinstall addresses this by using earlier Composer models to turn unconfigured repository checkouts into working mock environments. A Cursor agent first proposes 10 commands and expected outputs, while a separate Composer agent configures the checkout, mocks dependencies, and is evaluated against three selected commands. The process can create placeholder files, images, database tables, MinIO configurations, Docker containers, and startup scripts, restarting up to five times before discarding an environment. In a Celo monorepo experiment, the agent installed dependencies including Foundry and eventually mocked a user to run a minimal application; Composer 2 later scored 61.7% on Terminal-Bench versus 47.9% for Composer 1.5.


### [Continually improving our agent harness](https://yomu.fyi/post/continually-improving-our-agent-harness.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Stefan Heule & Jediah Katz
- Published: Apr 30, 2026
- Type: Explainer

Cursor describes its agent harness as an iterative product process: vision-driven hypotheses are tested through offline evals, real-world A/B experiments, and instrumentation. Its context strategy has shifted from static codebase context and guardrails toward dynamic retrieval as models improve, while model-specific prompts and tools match training conventions. Quality measurement combines CursorBench with latency, token efficiency, tool-call errors, cache behavior, code Keep Rate, and language-model analysis of user responses. The team classifies expected and unknown tool errors, uses per-tool and per-model anomaly baselines, and automates log investigations and backlog tickets; one sprint reduced unexpected tool-call errors by an order of magnitude. The harness also supports model switching and subagents, although switching can cause cache misses and summary information loss, and the post argues that multi-agent orchestration will make harness engineering increasingly central.


### [Build programmatic agents with the Cursor SDK](https://yomu.fyi/post/build-programmatic-agents-with-the-cursor-sdk.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Roshan Sadanani
- Published: Apr 29, 2026
- Type: Announcement

Cursor’s SDK is now in public beta, letting developers build programmatic coding agents with the runtime, harness, and models used by Cursor’s desktop app, CLI, and web app through TypeScript. Agents can run locally, on Cursor’s cloud in dedicated VMs, or on self-hosted workers; cloud sessions include a repository clone, configured development environment, streaming, reconnection, and options to push branches or open pull requests. The SDK also provides codebase indexing, semantic search, grep, MCP servers, repository skills, hooks, and named subagents, while supporting every model available in Cursor, including Composer 2.5. Described uses include CI/CD automations, custom internal platforms, and customer-facing agent experiences, with starter projects for quickstarts, prototyping, kanban workflows, and a CLI; the SDK uses standard token-based consumption pricing.


### [National Australia Bank accelerates legacy migrations with Cursor](https://yomu.fyi/post/national-australia-bank-accelerates-legacy-migrations-with-cursor.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: Apr 23, 2026
- Type: Problem & solution

NAB standardized 6,000 developers on Cursor after evaluating Amazon Q and GitHub Copilot, and is expanding access to more than 10,000 technology employees. The bank uses Cursor across legacy modernization and new development: BizCalc's Silverlight/.NET monolith is being refactored into Java microservices and React, while Assembly-based core-banking programs are being migrated using generated flowcharts and business summaries. Engineers use Ask Mode, Plan Mode, custom NAB CEL skills, Composer, and Opus coding models to document systems, produce requirements and API specifications, parallelize implementation, and test changes. NAB reports that both modernization efforts are progressing three times faster than expected, while a hardware-agnostic payment app was built in under three weeks rather than four months; one team reported a 5–8x velocity improvement.


### [Keeping the Cursor app stable](https://yomu.fyi/post/keeping-the-cursor-app-stable.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Andrew Chan & Kevin Nguyen
- Published: Apr 21, 2026
- Type: Explainer

Cursor's desktop app faces disruptive crashes as usage and features such as subagents, instant grep, and browser use have expanded, with most failures caused by out-of-memory conditions. The team measures instability across Electron's multi-process architecture using telemetry, per-session and per-request crash rates, minidumps, stack traces, crash breadcrumbs, and dashboards that update within minutes. Its two-pronged debugging strategy combines feature-level experiments and oversize-message instrumentation with bottom-up analysis based on a crash watcher, Chrome DevTools Protocol (CDP) stacks, automated daily investigations, opt-in heap snapshots, and low-rate allocation profiling. Findings led to chunking large data, killswitches, lifecycle fixes for leaks, and process isolation for extensions, while prevention uses Bugbot rules, stress tests, garbage collection, performance tests, and automated rollbacks. OOM-per-session fell 80% from its late-February peak and OOM-per-request fell 73% since March 1.


### [Amplitude ships 3x more production code with Cursor](https://yomu.fyi/post/amplitude-ships-3x-more-production-code-with-cursor.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: Apr 15, 2026
- Type: Problem & solution

Amplitude’s engineering team built toward an autonomous development pipeline that moves software from idea to production with minimal developer intervention, using Cursor to connect customer feedback, observability, code reviews, and other lifecycle context to agents. Cloud agents run in isolated, scalable VMs with complete development environments, enabling parallel, long-running, self-testing work that local machines could not support at the same scale. Automations now turn Slack bug reports and feature requests into Linear tickets and pull requests, perform hourly legacy migrations, and classify pull-request risk, while Bugbot reviews and autofixes low-risk changes. Since adopting cloud agents, Amplitude reports a threefold increase in weekly production commits, more than 1,000 unprompted agent runs per week, and Cursor as a top-three contributor by commit volume. About 60–70% of low-risk pull requests merge without additional developer work, while high-risk changes are routed to appropriate reviewers; the next goal is automating CI/CD, build validation, and deployment.


### [Better AI models enable more ambitious work](https://yomu.fyi/post/better-ai-models-enable-more-ambitious-work.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Luke Melas-Kyriazi
- Published: Apr 15, 2026
- Type: Benchmark

An eight-month study of developers at 500 companies using Cursor examined whether improved AI mainly increases existing work or enables tasks previously out of reach. The research, conducted with Professor Suproteem Sarkar of the University of Chicago Booth School of Business, covered releases of Opus 4.5 and GPT-5.2, finding average weekly messages per user rose 44%. Developers initially used better models for more work of similar complexity, then after a 4–6-week lag shifted toward harder tasks: low-complexity messages grew 22%, while high-complexity messages grew 68%, mostly in the final six weeks. Growth varied by sector, led by media and advertising at 54%, software and developer tools at 47%, and finance and fintech at 45%. Documentation, architecture, code review, and learning grew more than UI and styling, suggesting expanding AI-generated codebases increase demand for management, understanding, and review while opening broader productive opportunities.


### [Interact with agent-created visualizations in canvases](https://yomu.fyi/post/interact-with-agent-created-visualizations-in-canvases.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Alex Vandak Maloney
- Published: Apr 15, 2026
- Type: Announcement

Cursor introduces canvases, allowing agents to represent information through interactive visual interfaces instead of chat text or markdown. In the Agents Window, these durable artifacts sit alongside tools including the terminal, browser, and source control, and agents can build dashboards, PR review interfaces, architecture diagrams, and eval-failure investigations. Canvases use a React-based UI library with first-party tables, boxes, diagrams, and charts, plus existing Cursor components such as diffs and to-do lists; skills can teach agents to create specific canvas types. Cursor reports that combining observability data from Datadog, Databricks, and Sentry MCPs with local debug files makes time-series analysis easier, while eval skills group rollout failures to expose hidden harness bugs. The company is also using canvases to visualize autoresearch progress and current hypotheses during client-performance experiments.


### [Speeding up GPU kernels by 38% with a multi-agent system](https://yomu.fyi/post/speeding-up-gpu-kernels-by-38-with-a-multi-agent-system.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Wilson Lin, Sahil Modi, Yuan Zhang & Edward Lin
- Published: Apr 14, 2026
- Type: Benchmark

The post reports a three-week experiment in which a multi-agent system optimized 235 CUDA kernel problems generated from workloads spanning more than 124 production open-source models. Using SOL-ExecBench on 27 NVIDIA Blackwell 200 GPUs, the system used a planner to distribute and rebalance work, while autonomous workers benchmarked, debugged, and refined kernels without developer intervention. It ran separate CUDA C with inline PTX and CuTe DSL runs, reaching assembly-level optimization and learning a documented higher-level API. Against a single-agent optimized PyTorch baseline, it outperformed 149 of 235 problems, achieving a 1.38x geometric mean ratio, while 45 solutions exceeded 2x. The highlighted cases included an 84% geomean gain over a human FlashInfer baseline for paged-prefill attention, a 39% gain for NVFP4 MoE linear, and a GEMM reaching 86% of a tuned cuBLAS baseline; median SOL was 0.56, leaving room for improvement.


[Newer posts](https://yomu.fyi/company/cursor/page/2.md) · [Older posts](https://yomu.fyi/company/cursor/page/4.md)