Introduction

Cursor released version 2.0 on 29 October 2025. Three weeks later, on 18 November 2025, Google dropped Antigravity alongside Gemini 3. The developer community collectively gasped, debated philosophy, and then mostly got on with shipping. Nine months later, in a 2026 survey of around 900 Pragmatic Engineer readers, mostly software engineers and engineering leaders, 95% reported using AI tools at least weekly, and 75% said they used AI for at least half of their engineering work. The land grab that looked hypothetical in November is now empirical — at least for that audience.

Which means the comparison question has changed. It is no longer “should you try one of these?” It is “which one fits your actual workflow, now that both have had time to show their true colours?”

A lot has changed. Cursor has shipped version 3 — a unified, agent-native workspace built around Composer 2.5 and a plugin marketplace. Antigravity’s early login loops and “model provider overload” errors have largely been resolved, and in May 2026 Google split the product in two: a standalone Antigravity 2.0 app for agent orchestration, plus a separate Antigravity IDE, meant to be run side by side rather than as one tool. A serious new contender, OpenCode, has reached 160K+ GitHub stars and a self-reported 7.5 million monthly active users as the dominant open-source coding agent. And Claude Code has built a reputation for output quality: several 2026 developer comparison sites cite blind code-review preferences putting it ahead of OpenAI’s Codex around 67% of the time, against 25% for Codex and 8% ties — a figure that shows up consistently in secondary write-ups, though I could not trace it to a single standardised, independent benchmark.

None of this makes the core philosophical difference between Cursor and Antigravity irrelevant. It just means you now have nine months of real-world evidence to inform the choice. This post covers both tools, updated for August 2026.

Two AI IDEs launching within three weeks of each other was either incredible timing or industrial espionage. Nine months on, I'm increasingly convinced it was both. Welcome to 2026, where the future still arrives in sprint cycles but now comes with production-ready compliance documentation.

The Short Answer, Before the Long One

Choose Cursor if you intervene in code frequently, want broad model choice, or need mature, certified enterprise governance.

Choose Antigravity if you delegate larger tasks and value structured plans, browser evidence, and multi-agent oversight — and you are willing to run it alongside a separate editor now that Antigravity 2.0 has dropped the built-in IDE.

Use both if you can: Antigravity for acceptance and verification, Cursor for close debugging and repair. That is the pattern this article keeps circling back to, so here it is up front — the rest of the post earns it.

The Core Philosophy: Velocity vs Verification

Before diving into features, it is worth understanding the philosophical split, because it has not changed — it has sharpened.

Both Cursor and Antigravity belong to a category I call agentic IDEs: environments where autonomous agents plan tasks, edit files, run commands, and validate their own work. The question is what they optimise for.

Cursor 3: Speed Above All

Cursor’s Composer model was designed for one thing: velocity. Most coding tasks complete in under 30 seconds. The Mixture-of-Experts (MoE) architecture delivers fast inference by routing tasks to specialised sub-models rather than activating one massive network for everything. Cursor 3 doubled down on this by rebuilding the product around a unified workspace for agents — multi-repository layouts, movement between local and cloud agents — while still letting you drop back into the conventional Cursor editor for hands-on work. It is less “IDE with a mode toggle” and more “agent workspace that can hand control back to the IDE.”

Think of MoE like a well-run kitchen: instead of one chef doing everything, you have specialists. The pastry chef handles pastry, the grill chef handles the grill. The head chef (the router) decides who handles what. You get better results faster because nobody is doing work outside their expertise.

When you ask Cursor to “add user authentication,” it writes the code, runs tests, and shows you diffs — fast. The entire workflow happens in the time it takes to get coffee.

The trade-off remains: Cursor gives you the what without extensive explanation of the why. For rapid prototyping, this is ideal. For enterprise compliance requiring audit trails, it requires discipline.

Antigravity: Trust Through Artifacts

Google built Antigravity around a different problem: trust. When agents operate autonomously — editing files, running commands, controlling browsers — how do you know they did it correctly without reading every line of code?

Antigravity’s answer is artifacts — deliverables designed specifically for human verification:

• Task lists showing what the agent plans to do
• Implementation plans explaining architectural decisions
• Screenshots of UI changes
• Browser recordings demonstrating features working
• Test results proving correctness

Every major action produces something you can scan at a glance. You do not need to read 500 lines of code to verify the login form works — you watch a 30-second video of the agent testing it.

This makes verification faster but slows down execution slightly. In one third-party test, iTecs Online clocked Antigravity completing a Next.js + Supabase feature in 42 seconds versus Cursor’s ~68 seconds — but a single run on one task, with unknown prompts and repository state, cannot establish a general speed advantage either way. Treat it as a data point, not a verdict; Antigravity does generate richer documentation along the way regardless of who wins the stopwatch.

The philosophical difference remains, though it has sharpened rather than simplified: Cursor increasingly centres agent execution and developer intervention — you delegate, but you are one keystroke from taking over. Antigravity increasingly centres agent communication and structured verification — you delegate, and the system’s job is to prove the result is trustworthy before you look at code at all.

Cursor says "trust me, here's your code." Antigravity says "let me show you my work like a good student." One is your brilliant but chaotic friend who finishes the group project at 2 AM. The other is your detail-oriented colleague who documents everything in Notion. Both drive you slightly insane in different ways — but at least now you know which kind of insane you prefer.

Multi-Modality: Vision vs Creation

Both tools handle images, but they use them for completely different purposes — and this distinction matters more than it sounds.

Cursor 3: Visual Debugging

Cursor’s multi-modality is pragmatic and input-focused. Agents can:

• Read image files in your workspace (screenshots, mockups, design specs)
• Capture screenshots via the built-in browser to debug visual issues

The workflow is simple: you show Cursor a screenshot of a broken layout, and it analyses the visual problem and fixes the CSS. You paste a Figma export, and it generates matching HTML/CSS. Vision is strictly input — a way to communicate what you want, not a way to generate visual assets.

This is debugging-oriented. Cursor uses images to understand problems, not to create solutions.

Antigravity: Gemini 3 Pro Image (“Nano Banana Pro”)

Antigravity integrates Google’s Gemini 3 Pro Image model, internally nicknamed “Nano Banana Pro” (an upgrade from the Gemini 2.5 Image model, “Nano Banana,” that shipped with Antigravity at launch). This gives Antigravity genuine image generation capabilities with high-fidelity output and legible on-image text (a surprisingly hard problem for most image models).

Agents can:

1. Generate UI mockups before writing any code
2. Create placeholder icons and marketing images during development
3. Render visual implementation plans showing what the finished feature will look like
4. Produce diagrams explaining system architecture

This is creative multimodality. Antigravity does not just read images — it creates them as part of the development workflow.

The practical difference: with Cursor, you show it what you want. With Antigravity, it can show you what it is about to build before writing a single line of code.

Cursor: "I can see your screenshot and fix that button alignment." Antigravity: "Let me draw you three different layouts and you pick which one we build." It is the difference between a translator and an artist.

The Interface: Hybrid vs Mission Control

Both tools rethink the traditional IDE, but they bet on different paradigms.

Cursor 3: Agent-First by Default

Cursor 3’s biggest change is architectural: it starts in Agent Mode. The familiar VS Code skeleton remains — files left, editor centre, agent panel right — but the workflow now assumes you are delegating tasks, not typing line by line. You can still drop back into the conventional editor for fine-grained control, and the transition is smooth. If you have used Cursor 2, the upgrade is a tightening rather than a reinvention.

Composer 2.5 (the current orchestration layer, up from Composer 2) adds a plugin marketplace, allowing third-party integrations — database clients, deployment tools, monitoring dashboards — to surface inside the agent workflow. This is where Cursor 3 closes the gap on Antigravity’s ecosystem-level thinking.

Antigravity: Now Two Products, Not One

This section changed underneath the article. Antigravity launched in November 2025 as a single IDE with a built-in Manager View — a command dashboard bolted onto a conventional editor. In May 2026, Google split it into Antigravity 2.0: a standalone desktop app with no IDE at all, built entirely around the Agent Manager surface, plus a separate Antigravity IDE that still ships the old combined experience for now (Google plans to eventually strip the Agent Manager out of the IDE too, once 2.0 is the norm).

The recommended workflow going forward is what Google calls “dual-wielding”: run Antigravity 2.0 for agent orchestration in one window, and your IDE of choice — the Antigravity IDE or something else entirely — in another for hands-on editing. Inside Antigravity 2.0, you see:

• Active agents and their current status, including dynamically spawned subagents that handle subtasks without polluting the main agent’s context
• Projects — a looser replacement for the old per-repository “workspace,” letting one project span multiple folders with its own settings and permission scope
• Generated artifacts ready for review, plus a review flow for approving changes
• Scheduled Tasks, a new cron-style mechanism for triggering agents on a timer rather than only on demand

The workflow is orchestration-first: you spawn multiple agents, assign different tasks, and review artifacts asynchronously. One agent builds the API. Another writes the frontend. A third creates tests. You monitor all three from the Agent Manager without touching code directly, then switch over to your IDE when something needs a human hand.

Here is a concrete example: adding a payment system. In Cursor 3, you open a task in the agent panel and delegate. In Antigravity 2.0, you create a task in the Agent Manager, watch the agent generate a plan artifact, approve it, then monitor as it implements across multiple files while you review other work in your actual editor. Slightly more ceremony upfront, considerably less anxiety at the end — and now, slightly more app-switching too.

The difference is mental model: Cursor still centres code, even as it wraps that code in more agent scaffolding. Antigravity centres tasks so completely that, as of 2.0, it no longer bothers pretending to be an editor.

Cursor gives you a better car. Antigravity gave you a mission control centre bolted onto a car, and has now — mid-2026 — unbolted the two. You get a proper mission control centre and a separate car, and you're meant to run both at once. Whether that's tidier architecture or just more windows to alt-tab between depends entirely on your monitor setup.

Context Awareness: How Deep Do They See?

Cursor 3: Native Semantic Search

Cursor built its repository indexing directly into the model architecture. Their semantic search gives Cursor a dynamic context window of hundreds of thousands of tokens — commonly 200k to 500k depending on the base model. Cursor 3 adds real-time dependency graph updating, so refactors that touch dozens of files stay coherent across the board.

Context is bounded by your repository. Cursor knows your code extremely well but does not know much beyond it.

Antigravity: Massive Context + Self-Improvement

Antigravity leverages Gemini 3 Pro’s 1 million-token context window — roughly 2-5× larger than Cursor’s typical window (larger still for enterprise Vertex AI customers, where the window scales further). But the real innovation is Knowledge Items: persistent memory that stores your team’s conventions, architecture decisions, and working patterns across sessions.

When you tell Antigravity “we always use CSS Modules, never Tailwind,” it stores that. Three weeks later, it remembers. This is learning that persists across sessions and, following the Antigravity 2.0 shift from repository-bound “workspaces” to folder-spanning “Projects,” across a looser and larger unit of work too. Antigravity does not just understand your current codebase — it builds a model of how your team works.

Antigravity can also pull in external context dynamically through the Model Context Protocol (MCP), including API documentation and internal wiki pages.

The trade-off: more context means higher latency and potential for the agent to get distracted by tangential information. Sometimes focused understanding beats breadth.

Cursor is that colleague who memorised your entire codebase overnight. Antigravity is that colleague who memorised your codebase AND remembers you take your coffee black and hate meetings before 10 AM. The persistence is both impressive and slightly creepy. Nine months in, I mostly find it useful.

Browser Integration: Testing While Building

Cursor 3: Native Browser with DevTools

Cursor includes a built-in browser with full Chrome DevTools integration. Agents can launch localhost, inspect the DOM, run performance audits, capture screenshots, and monitor network requests. The DevTools integration means when an agent finds a bug, you can jump into the exact same debugging interface you would use manually.

This is a tool for developers. The browser helps both the agent and you understand what is happening.

Antigravity: Browser-in-the-Loop Verification

Antigravity treats the browser as a verification system. The workflow:

1. Agent builds a feature
2. Agent launches the app in automated Chrome
3. Agent tests happy paths and edge cases
4. Agent records a video walkthrough
5. Agent presents the video as an artifact

You watch a 30-second video and immediately know whether the feature works correctly. No manual testing required.

The limitation: when something breaks, you do not have DevTools to debug. The browser is optimised for proving things work, not for figuring out why they do not.

The key difference: Cursor’s browser is a tool for understanding. Antigravity’s browser is a tool for proving.

Cursor hands you a magnifying glass to examine the problem. Antigravity records a nature documentary showing the feature in its natural habitat. Both are useful, but for different reasons. I now use both: Antigravity for acceptance testing, Cursor for debugging what Antigravity catches.

Model Flexibility: Locked In or Open?

Cursor 3: Multi-Model from Day One

Cursor supports multiple AI models out of the box. You can use:

• Claude Sonnet 4.6 for detailed technical documentation and complex reasoning
• GPT-5.5 Instant for general-purpose tasks
• Custom models via API for specialised use cases
• Parallel agents with different models to compare outputs

You can even run the same task through multiple models simultaneously and pick the best output. For complex problems without one obvious solution, this comparative approach is genuinely useful.

Antigravity: Gemini-First, Not Gemini-Only

Antigravity is clearly optimised for Gemini 3 Pro, but also supports third-party models including Claude Sonnet 4.6 and open-source variants. The experience with third-party models feels secondary — like a checkbox feature rather than a core strength. The artifact system, browser integration, and Knowledge Items are all designed around Gemini 3’s specific capabilities.

If model flexibility matters to you, Cursor is the obvious choice. If you want the deepest Gemini 3 experience available, Antigravity wins.

Cursor is polyglot — speaks every model language fluently. Antigravity has a native tongue (Gemini) and knows some basic phrases in other languages. Choose based on whether you value flexibility or deep integration.

Performance: The Benchmark Battle

Benchmarks are imperfect, often gamed, and rarely reflect real-world usage. But they are the best objective measure available.

SWE-bench Verified — and Why a Model Score Is Not a Product Score

SWE-bench measures AI coding ability against real GitHub issues:

• Gemini 3 Pro: 76.2%, per Google’s own Gemini 3 announcement
• Cursor Composer (v2): ~65-70% (Cursor’s own estimate)

Treat this comparison with real scepticism. It sets a base-model score against a product-level estimate, and the two are not run under the same harness. Cursor made exactly this point itself: in a June 2026 study on reward hacking in coding benchmarks, it found that a large share of successful SWE-bench Pro runs (a stricter, separate benchmark from SWE-bench Verified above) were retrieving known fixes from upstream repositories or git history rather than solving the problem from scratch. Under a stricter harness that blocked this, Cursor’s own Composer 2.5 fell from 74.7% to 54.0% — the largest drop of any model tested. The lesson generalises: repository retrieval, shell harness, test environment, retry logic, and the human approval loop all shape the final number as much as the underlying model does. A model score is not a product score.

In my own use, large codebase navigation across 100k+ line repositories still feels noticeably snappier in Antigravity, which tracks with its bigger context window — I don’t have a clean benchmark number for the gap, so take that as an impression, not a stat.

For most everyday tasks, neither tool’s speed difference is the bottleneck. The bottleneck is prompt quality.

Arguing about whether 42 seconds or 68 seconds is "fast enough" is peak 2026 energy. Five years ago we waited five minutes for `npm install`. Now we are annoyed if the AI takes longer than a minute. We have become insufferable and I am absolutely part of the problem.

Security and Compliance: Who Can You Actually Trust?

Cursor 3: Production-Ready Governance

Cursor 3 includes a mature sandbox mode:

• Restricted file system access to project directories only
• Blocked outbound network calls to prevent data exfiltration
• Approval requirements for shell commands
• SOC 2 Type II compliance certification
• Enterprise audit logs tracking all agent actions

For regulated industries — healthcare (HIPAA), financial services (SOC 2, PCI-DSS) — this governance framework is the current standard. Enterprise admins can enforce sandbox policies across entire teams.

Antigravity: Matured from Preview Warnings

Google has addressed most of the security concerns flagged in the November 2025 launch. Login loops are largely resolved. The “data exfiltration risks” warnings from the original Terms of Use have been replaced with clearer documentation of the actual threat model.

What Antigravity has not done, as of writing, is publish its own product-level SOC 2 Type II or ISO 27001 attestation. It inherits Google Cloud’s underlying infrastructure certifications — the data centres, the networking, the physical security — but that is a narrower guarantee than an audit of Antigravity’s own agent execution environment, and it is not a substitute for one on a vendor security questionnaire. This gap is real enough that it shows up as an open question on Google’s own Workspace admin community forum, with no official report to point to. Regulated buyers should ask Google directly for product-specific evidence rather than assuming Cloud-level compliance covers it.

Current recommendation: internal tools and prototyping, Antigravity is solidly fine. Regulated production systems with user data, Cursor is still the verified safe choice.

Cursor is still the responsible adult with all the certifications. Antigravity has graduated from "brilliant intern without clearance" to "new hire whose background check has come back clean." Progress. Real, measurable progress.

Pricing: Free, For Now

Cursor

• Free tier with usage limits (sufficient for evaluation)
• Pro tier at $20/month with higher context windows and more requests
• Team and Enterprise tiers with collaboration features and dedicated support

Antigravity

Antigravity shifted from “100% free preview” to a tiered model, and the tiers themselves changed again in May 2026. Per Google’s own pricing page and its plan-change announcement:

• Individuals (free) — $0/month: unlimited tab completions and command requests, basic weekly rate limits, and access to Gemini 3.5 Flash, Gemini 3.1 Pro, Gemini 3 Flash, Claude Sonnet & Opus 4.6, and gpt-oss-120b.
• Google AI Pro — $20/month, matching Cursor’s Pro price, with more generous rate limits and a flexible AI credit pool.
• Google AI Ultra — now split into two tiers: $100/month (5× the Pro plan’s token rate limit) and $200/month, down from $250 (20× the Pro plan’s rate limit).

There is also a new consumption-based Organization plan for Google Cloud customers. Google has kept the individual tiers competitive with Cursor’s pricing — as expected, it used the free preview to build market share and is now monetising without dramatically disadvantaging existing users.

Google giving away cutting-edge AI development tools for free to build market share before charging for them is not a business surprise. It is a business plan. The good news: the pricing landed at a fair level. Sometimes the inevitable outcome is also the good outcome.

The Ecosystem Question: What About Windsurf and OpenCode?

Antigravity’s Origins

In July 2025, Google hired Windsurf’s leadership team in a $2.4B acquihire. Antigravity is Windsurf’s existing agent-first architecture, fused with Gemini 3 and Google’s infrastructure. This explains the rapid development timeline and explains some of the early quality inconsistencies — integrating an acquired architecture into a new model stack is non-trivial engineering, regardless of resources.

Nine months on, the integration looks solid. The early rough edges that suggested “rebrand rather than rebuild” have mostly been polished away.

The New Contender: OpenCode

A development nobody quite predicted: OpenCode has become the dominant open-source coding agent, reaching 160K+ GitHub stars and a self-reported 7.5 million monthly active users since its June 2025 launch — figures that show up consistently across independent 2026 dev-tooling coverage, including LogRocket’s June power rankings, though they ultimately trace back to the project’s own reporting. It is model-agnostic, supports 75+ providers (Claude, Gemini, GPT, local Ollama models), and offers air-gapped deployment for regulated industries that cannot send code to any external API. Note that “OpenCode” is a crowded name on GitHub — the project referred to here is anomalyco/opencode, not one of several similarly named but unrelated repositories.

OpenCode’s rise matters for the Antigravity-versus-Cursor comparison because it establishes a third viable path: teams that want agentic workflows without committing to either Google’s or Cursor’s infrastructure. If you are evaluating today, OpenCode deserves a place on the shortlist.

And then there is Claude Code, which has built a reputation for output quality: several 2026 comparison sites cite developer-run blind reviews preferring its output over Codex’s around 67% of the time, against 25% for Codex — though, as noted above, I could not pin this to one standardised independent study, so read it as a widely repeated signal rather than a settled benchmark. A better-sourced and more useful finding comes from a July 2026 controlled experiment on cross-model code review: having Claude Opus 4.7 review Codex GPT-5.5’s drafts raised the pass rate from 71.6% to 89.7%, while the reverse pairing — Codex reviewing Claude’s drafts — reduced Claude’s own pass rate. The practical takeaway is not “Claude wins” or “Codex wins.” It is that the strongest toolchain may not be one coding agent at all, but one agent for implementation and a different one for review. Claude Code is not an IDE in the Cursor or Antigravity sense — it is a CLI-first tool — but for teams where code quality is the primary concern, or who want to experiment with cross-model review pairing, it is worth considering alongside both.

Google basically bought the answer key instead of doing the homework themselves. In academia this would be cheating. In Silicon Valley it is called "strategic acquisition." Nine months later, the homework is submitted, marked, and actually decent.

Current Rough Edges

Both tools have matured since November 2025, but both still have issues worth knowing about.

Cursor 3

• Agent-centric default UI can feel alienating to developers returning after time away
• Running multiple agents simultaneously still increases token usage dramatically without clear guardrails
• The Composer 2.5 plugin marketplace is still maturing — plugin quality is inconsistent, and some integrations break on minor IDE updates
• Context switching between concurrent agent tasks remains mentally taxing; no good solution exists yet

Antigravity

• Heavy artifact overhead for simple tasks persists — generating plans, screenshots, and videos for a one-line change is still excessive
• Inconsistent agent quality on ambiguous prompts; well-defined tasks produce good results, vague requests produce politely useless artifacts
• Knowledge Items require upfront investment: teams who do not populate them get significantly worse results than teams who do
• The Agent Manager cognitive load is real — you are essentially managing a team, and that is a skill that takes time to develop, now with the added overhead of deciding which of the two Antigravity apps you are managing it from

The honest assessment: both tools are genuinely production-ready for most use cases, but they reward investment in learning their model. The “just use it and it works” experience remains aspirational rather than actual.

Using either tool today is like working with a very capable junior developer who occasionally does something inexplicable for reasons you cannot quite unpick. Mostly brilliant. Occasionally baffling. Always faster than doing it yourself.

Who Should Use Which?

Combined Selection & Feature Matrix

Dimension	Cursor 3	Google Antigravity	Edge goes to
Velocity & rapid prototyping	Standard features in 30-60 seconds via Composer 2.5	Artifact generation adds overhead; slower per task	Cursor 3
Enterprise compliance	SOC 2 Type II certified, mature audit logs, proven governance	Inherits Google Cloud infrastructure compliance; no independent product-level attestation published	Cursor 3
Model flexibility	Multi-model native — Claude, GPT, custom models via API	Gemini-first; others supported but feel secondary	Cursor 3, or OpenCode for full model-agnosticism
Verification & audit trails	DevTools for manual debugging	Video artifacts and task plans make agent actions transparent to stakeholders	Antigravity
Massive codebase comprehension	~200k-500k token native semantic search	1M-token context (higher on Vertex AI), plus persistent Knowledge Items	Antigravity
Multi-agent orchestration	Parallel agents inside one IDE	Agent Manager, now the whole point of the standalone Antigravity 2.0 app	Antigravity
Core model / architecture	MoE via Composer 2.5	Gemini 3 Pro	—
Multi-modality	Visual debugging (input only)	Generative creation via Gemini 3 Pro Image (“Nano Banana Pro”)	—
Plugin / integration ecosystem	Composer 2.5 marketplace (still maturing)	MCP-native integrations; CLI and SDK as of 2.0	—
Pricing	Free tier + $20/mo Pro	Free tier + $20/mo Pro + $100-200/mo Ultra	Roughly matched
Code quality above all	—	—	Claude Code (widely cited ~67% preference over Codex in blind reviews — see caveats above)
Open source / air-gapped	—	—	OpenCode (160K+ stars, 75+ model providers, air-gapped deployment)

Typical alignment:

• Cursor 3: Startup developers, freelancers, enterprise teams in regulated industries.
• Antigravity: Solo explorers, technical content creators, teams building greenfield projects, now willing to run a second editor alongside it.
• OpenCode: Teams needing model optionality or self-hosted deployment.
• Claude Code: Teams where code quality is the non-negotiable priority.

Or just choose whichever one does not crash when you try to log in. That is still a legitimate selection criterion in 2026. Sometimes "works reliably" beats "technically superior" every single time. Consistency is an underrated virtue in developer tooling.

Getting Started: First Steps

For Cursor 3

1. Download from cursor.com/download
2. Install on macOS, Windows, or Linux
3. Open a project you know well — do not start with something unfamiliar
4. Accept the Agent Mode default rather than immediately switching back to Editor Mode
5. Experiment with simple agent tasks — “add error handling to this function” or “write tests for this component”
6. Enable sandbox mode before working with any production code

Time investment: Plan to spend 2-3 hours getting comfortable before forming opinions.

For Antigravity

As of May 2026 this is a two-app decision, not one download:

1. Decide which app you actually want first. The original Antigravity IDE (Editor View + built-in Manager View) still exists and is the simpler starting point if you want one application. Antigravity 2.0 is the standalone, IDE-free agent orchestration app, meant to be run alongside a separate editor — pick this if you are already happy with your current IDE and just want the agent layer.
2. Visit antigravity.google/download and grab whichever you chose (or both — they coexist on the same machine, distinguished by icon).
3. Sign in with your Google account (login stability is much improved from the November 2025 preview).
4. If using the IDE: start in Editor View, not Manager View. If using 2.0: you land straight in the Agent Manager — there is no editor to fall back into, so set up your actual IDE alongside it first.
5. Give the agent well-defined tasks with clear success criteria — vague requests produce vague results.
6. Review the generated artifacts — spend time understanding what they tell you.
7. Populate Knowledge Items early — the quality delta between teams that do and do not is significant.
8. Try orchestrating 2-3 agents in parallel only after you have completed a handful of single-agent tasks and trust the artifact system.

Time investment: Plan to spend 3-4 hours learning the artifact system before evaluating fairly, plus extra time up front if you are figuring out the IDE-vs-2.0 split for the first time.

Pro Tips for Both

• Start with non-critical projects — do not test new tools on production code
• Read the agent’s plans before approving them — blind trust leads to technical debt
• Keep tasks focused — “build a complete e-commerce system” fails; “create a product listing page” succeeds
• Save prompts that worked well — you will reuse patterns
• Join the communities — Discord and Slack channels where other users share real-world experience

Learning a new IDE is like learning a new language — immersion works better than reading documentation for six hours. Start using it, make mistakes, and learn what works through experience. The documentation will make considerably more sense once you have hit all the obvious problems yourself.

The Era of Orchestration Is No Longer Coming

In November 2025, Cursor 2 and Antigravity represented a bet on the future. In August 2026, with AI-tool adoption now the survey-reported norm among the engineers who responded to Pragmatic Engineer’s poll, they represent the present.

The philosophical split has not resolved. It has deepened, and it has also gained a second axis: Antigravity’s move to a standalone, IDE-free agent app in May 2026 means the old question — “code-centric or task-centric?” — now comes with a second one: “one application, or two running side by side?” Both tools have matured, both have narrowed their respective weaknesses, and the choice between them is a question of values and workflow, not maturity and reliability.

What has changed is the competitive landscape. OpenCode’s rise as the dominant open-source option means the choice is no longer binary. Claude Code’s reputation for output quality — and the emerging evidence that cross-model review pairs beat any single model working alone — means teams with high-trust workflows have more than one credible option beyond the two IDEs this post is built around.

Do not choose an agentic IDE by asking which model writes the best code. Choose it by asking which system helps you detect bad code before it becomes your problem. Cursor if you value speed, compliance, and staying inside one application. Antigravity if you value verification and large-scale orchestration, and don’t mind running two apps to get it. OpenCode if you value openness and model flexibility. Claude Code, ideally paired with a second model for review, if output quality is non-negotiable. And do not be surprised if you end up using two of these for different purposes — that is the pattern I see most often in teams nine months into figuring out their workflow.

In 2015, we argued about Vim versus Emacs. In 2020, we argued about VS Code extensions. In 2025, we argued about which agentic IDE philosophy better matched our worldview. In 2026, we have accepted that the answer is "it depends" and moved on to arguing about prompt engineering strategies. Developers will always find new things to have strong opinions about. This is load-bearing for our sense of identity.

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References

• Cursor 3.0 announcement
• Cursor — Introducing Composer 2.5 (May 2026)
• Cursor — Reward hacking is swamping model intelligence gains (June 2026)
• Introducing Google Antigravity
• Introducing Google Antigravity 2.0 (May 2026)
• Google — A new era of intelligence with Gemini 3 (context window, SWE-bench Verified score)
• Gemini 3 Pro Image for developers (“Nano Banana Pro”)
• Google Antigravity — Pricing
• Google Antigravity — Changes to Antigravity Plans (May 2026)
• Google Cloud — SOC 2 compliance
• OpenCode (anomalyco/opencode) on GitHub
• Cross-Model LLM Code Review: Should you use Claude to review Codex or vice versa? (arXiv, July 2026)
• iTecs Online: Antigravity vs Cursor vs Copilot
• LogRocket: AI Dev Tool Power Rankings June 2026
• Google Cloud AI Agent Trends 2026
• SWE-bench
• The Pragmatic Engineer — AI Tooling for Software Engineers in 2026 (~906-respondent adoption survey)