Antigravity vs Windsurf: Google Agent-First or Cognition Cascade?

Antigravity is the better choice for greenfield parallel prototyping, and Windsurf is the better choice for production refactoring. Antigravity is built around multi-agent dispatch, while Windsurf centers on reversible, human-reviewed Cascade flows. For enterprise teams managing multi-repository workflows, neither tool combines spec-driven coordination, broad model flexibility, and the compliance posture some organizations require, based on reviewed Windsurf documentation, Windsurf security controls, Google's Antigravity announcement, and Antigravity codelabs.

Why Agent Architecture Determines Your Workflow

Picking the wrong agent architecture for your workflow means either babysitting an agent that should be autonomous or discovering that an autonomous agent made the wrong call 40 minutes into an unsupervised run. Antigravity uses an agent-manager with specialized subagents, while Windsurf Cascade uses resumable Flows with persistent context. The architecture shapes where you spend your review time and how expensive mistakes are to unwind.

Antigravity: Multi-Agent Parallel Orchestration

Antigravity's defining feature is its dual-view design. The Editor View functions as a traditional VS Code-based IDE with an AI sidebar. The Manager View acts as mission control for dispatching multiple autonomous agents simultaneously. The Copilot vs Antigravity comparison highlights how this dispatch model differs from suggest-first assistants.

The reviewed public materials describe these core subagent roles:

• Browser Subagent: web research, documentation lookup, visual verification of UI implementations
• Terminal Subagent: command-line operations, test execution, build processes
• Editor Subagent: file system interactions, code modifications, refactoring

What the docs describe and what works reliably in practice are different questions. The browser subagent handles visual verification, but the reviewed materials do not clarify how it handles responsive layout edge cases or cross-browser inconsistencies. The terminal subagent runs tests, but flaky test suites are a known challenge for autonomous agents because intermittent failures create noisy signal that agents struggle to interpret correctly. Enterprise teams should test these capabilities against their own codebases before committing.

Google's agent documentation describes Antigravity's agent layer as responsible for orchestration and Gemini as the core reasoning model, with a main model handling higher-level reasoning while specialized tools execute tasks through the agent stack.

Agents produce artifacts for asynchronous review, including planning modes, artifact reviews, code diffs, and browser-based validation workflows, as described in the agent docs and codelabs.

Windsurf: Persistent Flow-Based Agent with Explicit Limits

Windsurf's Cascade operates as a persistent agent that reads the codebase, builds a project model, and executes multi-step plans. The critical design difference is explicit execution control: Cascade enforces a 20-call limit per prompt, which constrains runaway autonomous execution by design.

That 20-call cap has practical implications the docs do not fully address. A multi-file refactoring task that touches 8-10 files with test updates can consume most of those calls in a single prompt. When the limit is reached, the flow stops and the developer must issue a new prompt to continue, which resets the call counter but risks losing momentum on the original plan. For small, focused tasks this constraint is barely noticeable. For larger cross-service changes, it forces artificial breakpoints that fragment what should be a single logical operation.

Cascade's context retrieval draws on real-time flow awareness (tracking file edits, terminal commands, and related activity), RAG indexing (including M-Query retrieval and context pinning), and a memory bank (global rules, workspace rules in .windsurfrules, and autonomously generated memories). The mechanism names sound comprehensive, but the critical question for large codebases is whether RAG indexing keeps up as repository size grows. A related concern is whether the memory bank creates stale references that mislead the agent on subsequent prompts. Teams should evaluate both against their own repository sizes before purchase.

Where Antigravity dispatches agents and reviews artifacts, Windsurf keeps the developer in a continuous feedback loop. Cascade workflows are processed sequentially in the working session, with progress tracked through features like Todo lists and transcripts.

Architecture Comparison

The following table summarizes the structural differences that shape daily developer experience in each tool.

The row that matters most for day-to-day experience is the execution cap. Antigravity's lack of a documented limit means agents can run longer without interruption, which is useful for exploration but creates real operational risk when an agent makes a wrong decision early and compounds it over dozens of subsequent steps. Windsurf's 20-call cap forces regular human checkpoints, which slows throughput but limits how much damage accumulates before a developer notices.

My honest take: the codelabs support the view that Antigravity is optimized for parallel greenfield work, while the Cascade docs support the view that Windsurf is optimized for iterative, review-heavy work inside existing codebases.

How Each Architecture Handles a Service Split

To make the architectural difference concrete, consider a representative task: splitting a monolithic Express endpoint into two separate services with shared validation logic. Based on each tool's documented capabilities, here is the sequence of steps a developer would follow.

In Antigravity, the Manager View would let you dispatch agents across the task, but the sequencing matters. The shared validation library needs to be extracted first, since both the new service and the updated original endpoint depend on it. A practical approach would be to dispatch one agent to handle the extraction, then once that completes, dispatch two agents in parallel: one to scaffold the new service using the extracted library, and the other to update the original endpoint. The Editor Subagent modifies files, the Terminal Subagent runs tests after each change, and the Browser Subagent can verify the API responses visually. Because there is no documented execution cap, these agents can work through their respective tasks without forced interruptions. The developer reviews artifacts asynchronously once the agents finish, which means the first full review happens after the parallel agents have completed their work. If the scaffolding agent's integration approach is incompatible with the update agent's assumptions about the extracted library's interface, you discover the conflict at review time, not during execution.

In Windsurf, the developer would describe the split to Cascade as a single prompt. Cascade reads the codebase, plans the extraction sequence, and begins executing. With 8-10 files to modify, test files to update, and a new service to scaffold, a task this size can approach or exceed the 20-call limit in a single prompt. When the cap hits, the developer must continue with a new prompt, which means reviewing partial progress and re-establishing intent. The benefit is that the developer sees and approves each diff inline, catching misaligned assumptions in real time. The cost is that a task one tool handles as a single autonomous run, the other fragments across two or three prompts.

The divergence point is clear: Antigravity collapses review into a single post-execution pass, which is faster when the agents get it right and more expensive when they do not. Windsurf distributes review throughout execution, which is slower overall but catches errors earlier. Neither approach is universally better; the right choice depends on whether your codebase has enough documented conventions and test coverage for an unsupervised agent to make sound decisions on its own.

Autonomy Level: Full Auto vs. Human-in-the-Loop

Antigravity and Windsurf both support autonomous agent execution, but they diverge on governance defaults. Antigravity gives teams four configurable modes that determine how much human oversight the agent expects. Windsurf builds checkpoint reversion and per-step approval directly into the Cascade workflow. The choice between them is a team governance decision: how much control does your organization want to encode into the tool versus enforce through process?

Google's codelab states that Antigravity's architecture "presupposes that the AI is not just a tool for writing code but an autonomous actor capable of planning, executing, validating, and iterating on complex engineering tasks with minimal human intervention." The four configurable modes each combine specific terminal execution, review, and JavaScript execution policies:

The reviewed Google materials document support for autonomous runs, but I did not locate an official published time cap or an official source for the frequently repeated 200+ minute unsupervised-session claim. Teams considering Agent-driven mode should have a clear policy for how often they review agent output regardless of the mode's default behavior, because an uncapped agent that misreads a requirement early in a run will keep building on that wrong assumption until someone checks.

Windsurf takes the opposite approach. Developers can revert to a previous step in the conversation to undo code changes made after that point, and they can create named snapshots/checkpoints to return to later. The reversion capability has a meaningful boundary, though: it covers file-system changes the IDE tracks, but it cannot roll back side effects that escape the IDE's scope. Database migrations that ran during a Cascade step, deployed services, external API calls, and state changes in third-party systems all fall outside the reversion boundary. Teams relying on checkpoint reversion for safety should understand that it protects code, not infrastructure state.

Here is how these differences play out in practice:

• Antigravity optimizes for longer autonomous execution with fewer interruptions, making it a better fit for exploratory greenfield work where the cost of a wrong turn is low.
• Windsurf optimizes for tighter review loops and faster rollback within IDE scope, making it a better fit for teams working in production codebases where a wrong change has downstream consequences.

Model Lock-In: Gemini, SWE-1, or Bring Your Own

The Autonomy section covers how much control you have during execution. Model lock-in is about how much control you have over the infrastructure underneath: whether your context carries over when you switch models, whether every feature still works, and how much rework switching requires. Antigravity offers some model choice inside Google's platform, while Windsurf offers model choice inside Cascade.

Antigravity's model documentation lists Claude Sonnet 4.6, Claude Opus 4.6, and GPT-OSS-120B alongside the Gemini family. That is real model choice, but the switching cost is high because the model sits inside Google's orchestration layer. Selecting a different model does not reduce platform dependency; project memory, agent routing, subagent coordination, and artifact management all remain Google-specific. The reviewed docs also do not clarify whether non-Gemini models have access to the full subagent stack or whether certain capabilities are Gemini-only. Teams evaluating Antigravity's model flexibility should test non-Gemini models against their specific workflows before assuming feature parity.

Windsurf offers model switching within Cascade, and its documentation indicates models can be selected per task. Windsurf also offers its proprietary SWE-1.5, a "Fast Agent" model developed with Cerebras. It achieves near-SOTA coding performance at up to 950 tokens per second. The switching cost is lower at runtime because the developer can change models without changing platforms. Leaving Windsurf entirely is a different question. The .windsurfrules files are human-readable configuration, so you can extract the logic, but they follow a Windsurf-specific schema and would need to be rewritten for any other tool's rule system. The memory bank stores autonomously generated context alongside global and workspace rules, but there is no documented export format. Migration from Windsurf would realistically require manual re-implementation of workflow rules, re-indexing in the new tool, and rebuilding whatever accumulated memory the agent had developed. Windsurf's context system is documented in Cascade's architecture and context overview.

Security: Documented Gaps vs. Formal CVE Process

Security posture is easier to evaluate when a vendor has public disclosures, formal vulnerability records, and published enterprise controls. On the public record I reviewed, Windsurf is easier to diligence because it has both a public security page and CVE records, while Antigravity remains thinner on product-specific security documentation. Both tools also carry privacy and data-handling risks common to cloud-based AI coding assistants.

Antigravity: No Formal CVE Entries Located in Authoritative Databases

Searches of the NVD and MITRE CVE database returned no Antigravity-specific results during research. Google had also not published a dedicated Antigravity advisory on its security blog at the time of review.

The early-launch vulnerability reporting I found relied on non-primary journalism sources, so I am not using those reports as technical support here. In summary: no formal Antigravity CVE entries and no dedicated official Google security advisory for the product were located during review.

Windsurf: Formal CVEs and Documented Security Program

Windsurf has public vulnerability records and a documented security program:

• CVE-2025-52882: NVD entry describing a WebSocket vulnerability affecting Claude Code extensions in VS Code and forks including Windsurf

Note on CVE-2025-62353: A CVE entry for a path traversal issue reportedly affecting the Windsurf IDE was referenced during research, but the NVD link returned a generic redirect and the entry could not be independently confirmed in authoritative databases at the time of review. Enterprise teams should check current NVD and MITRE records directly for the latest status of this entry.

Windsurf publishes vendor-stated enterprise security controls including SOC 2 Type II and annual third-party penetration testing on its security page.

Security Posture Comparison

The table below captures the key differences in what each vendor makes publicly verifiable today.

Antigravity's lack of product-specific CVEs does not mean the product is more secure than Windsurf. Fewer product-level CVEs means less product-level security information is publicly verifiable. Antigravity inherits Google Cloud's platform-level security posture, which includes SOC 2, ISO 27001, and FedRAMP certifications at the infrastructure layer. Whether those platform certifications cover Antigravity-specific data handling, agent execution boundaries, and prompt-injection mitigations is a question enterprise buyers should raise directly with Google.

Windsurf's formal CVE trail and security documentation make it easier to diligence at the product level, even though having CVEs on record means vulnerabilities were found. Regulated teams evaluating either tool should understand the SOC 2 Type II requirements that apply to AI development tools before starting procurement.

Enterprise Readiness: Preview vs. Procurement-Ready

What procurement, security, and IT can verify in public documents matters more than feature demos when evaluating enterprise readiness. Based on reviewed public materials, Windsurf is easier to evaluate for purchase today because it publishes pricing, admin controls, and security documentation, while Antigravity's enterprise-specific pricing and compliance documentation remain limited.

Windsurf's compliance and admin claims above are sourced from its security page and admin guide. Antigravity now publishes individual-tier pricing: a free tier, a Pro tier at $20/month (tied to Google AI Pro subscriptions), and an Ultra tier at $249.99/month. Enterprise-specific pricing, compliance certifications, and documented admin controls remain unavailable in the reviewed public materials.

Windsurf's pricing changed on March 18, 2026, replacing its credit-based system with daily and weekly quotas. The new tiers are Free, Pro ($20/month, up from $15), Max ($200/month, a new tier for power users), and Teams ($40/user/month). Enterprise pricing requires contacting sales. The admin guide describes RBAC, SSO enforcement, SCIM provisioning, and centralized usage analytics. Because the billing model shifted from monthly credit pools to rate-limited quotas, previous per-developer cost estimates based on credits no longer apply. Teams evaluating Windsurf should model costs against the new quota structure, as daily and weekly caps change the economics for power users compared to the old system. Neither vendor's public materials make it easy to model real per-developer consumption at scale, which means actual costs could differ from sticker pricing.

Ownership Risk: Google Ecosystem vs. Cognition Acquisition

Ownership and platform dependence affect outage risk, contract continuity, and migration cost. Antigravity carries platform dependency on Google's agent stack, while Windsurf carries post-acquisition continuity questions under Cognition ownership.

Antigravity: Google Ecosystem Dependency

Antigravity runs on Google infrastructure. The reviewed public materials do not provide a detailed public incident history for the product, so the primary concern here is platform dependence rather than any documented reliability record.

The product uses ~/.gemini/ for global rules and workflows, while workspace-specific knowledge is stored in .agents/ directories and related spec files. That project memory is product-specific, so teams should not assume straightforward portability into other tools.

Windsurf: Post-Acquisition Uncertainty

Windsurf's ownership changed in 2025. Cognition signed a definitive agreement to acquire Windsurf in July 2025, and the company continues publishing updates through its changelog. Windsurf's founding CEO and co-founder left for Google as part of a separate $2.4 billion deal, and Cognition subsequently laid off some Windsurf employees while offering buyouts to others.

The question every current Windsurf user has is whether the product has changed since the acquisition. I did not find enough post-acquisition data to answer definitively, but the risk factors are concrete: founding leadership left, headcount was reduced, and ownership transferred to a company (Cognition) whose primary product (Devin) occupies a different market position. Teams signing contracts today should treat feature velocity, support response times, and certification maintenance as open questions, and negotiate accordingly.

Enterprise buyers should verify three things directly with the vendor:

• Long-term product roadmap under current ownership
• Continuity of certifications and support terms
• Current data handling and privacy commitments

I did not locate any official post-acquisition update announcing changed data ownership policies or revised privacy terms in the reviewed Windsurf materials. That absence does not prove no change occurred; it means buyers should verify the current documents directly with the vendor.

Who Should Choose Which Tool

The strongest buying signal here is which tool matches the constraints your team operates under today. Antigravity favors autonomy and parallelism, while Windsurf favors reviewability and control. Most teams do both greenfield and production work, so the real question is which failure mode you can tolerate more often.

Choose Antigravity If:

• You are a small team building throwaway prototypes or MVPs where the cost of an agent making a wrong turn is low, and parallel agents can cut iteration cycles. Expect to check agent output before anything touches a shared branch, since the lack of a documented execution cap means errors can compound before you notice.
• Your team is exploring a new technical direction: evaluating frameworks, spiking integrations, building demo apps for stakeholder feedback. You need to spin up parallel experiments fast, and the work lives in isolated branches where a wrong turn means deleting a branch, not rolling back production.
• You are in a hackathon, research, or pre-product phase where speed of exploration matters more than stability guarantees. Public preview limitations are acceptable because the work itself is experimental.
• You operate outside regulated environments that require SOC 2, ISO 27001, or similar procurement documentation today.

Choose Windsurf If:

• Your primary workflow is maintaining a production monolith or multi-service codebase where a bad refactor has downstream consequences. Cascade's per-step reversion protects file-system state; just remember it does not roll back database migrations, deployed services, or external API calls.
• You need explicit approval gates and your team culture values reviewing each step over throughput speed.
• Your procurement process requires SOC 2 Type II and ISO 27001 documentation today, subject to verifying that certifications remain current post-acquisition.
• You accept ownership transition risk and will independently verify current policies, roadmap, and support terms with the vendor.

When Cross-Repo Coordination Is the Real Bottleneck

If your main bottleneck is keeping multiple repositories aligned to an evolving plan rather than single-repo refactoring or greenfield exploration, it can make sense to evaluate a separate orchestration layer alongside these tools. Intent provides a spec-centered workflow with coordinated agents, isolated workspaces, and role-based delegation. The living-spec model means the plan updates as agents complete work. Every contributor stays aligned without manual status checks.

On the governance side, Augment Code holds ISO/IEC 42001 certification from Coalfire, and published SWE-bench results provide additional benchmark context. Teams should still map those results to their own procurement requirements and validate current commercial terms directly.

Windsurf is usually the more direct fit for single-repo refactoring. Antigravity is more aligned with autonomous exploration in a new codebase. For teams whose primary challenge is keeping multiple agents and repositories synchronized to an evolving specification, a dedicated coordination workspace is worth evaluating as an adjacent category.

What We Couldn't Verify

Both vendors leave gaps in what they make publicly verifiable. Rather than scatter these caveats across the article, here is what procurement teams should ask about directly:

• Antigravity: No product-specific compliance certifications, no formal CVE process, no documented execution caps, no public clarity on whether non-Gemini models have full subagent feature parity, and enterprise-specific pricing remains undocumented (individual tiers are now published). Google's platform-level certifications exist but their coverage of Antigravity-specific data handling is unconfirmed.
• Windsurf: Post-acquisition certification continuity unverified, ownership transition impact on product velocity and support undocumented, real consumption rates under the new quota-based billing model not publicly modeled, and checkpoint reversion scope limited to IDE-tracked file changes. One referenced CVE (CVE-2025-62353) could not be independently verified at the time of review.

If you are running a formal procurement process, treat this list as a starting point for your vendor questionnaire.

Match Your Agent Architecture to Your Compliance Requirements

Choose based on the constraints you need to satisfy next quarter. If you need autonomous parallel exploration in lower-risk environments, validate whether Antigravity's preview limitations are acceptable. If you need tighter review loops, published pricing, and more public procurement documentation, push Windsurf through a live security and admin review with your own requirements list.

If cross-repository coordination is the real blocker, add that requirement explicitly to your evaluation rubric before you buy either tool.

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