Skydive Review: AI Agents That Live in the Cloud

What Is Skydive?

The platform is the second product from Anything, the San Francisco startup behind an AI app builder used by more than a million people. Anything reports it automated much of its own operations with over 150 agents before packaging the approach as a product, and it was launched publicly in August 2026 after a closed beta with more than 20 companies.

The defining idea is that agents should be coworkers, not chatbots. Instead of opening a chat window and prompting each time, you name an agent, give it a role, and it runs on its own cloud computer — with a browser, file system, and terminal — using your tools and remembering what it learns. The company is backed by Footwork, Uncork, Bessemer, and M13, with a reported $100 million valuation.

How Skydive Agents Work

An agent is created by describing the job you want done. There is no workflow wiring, no prompt engineering, and no code: you say what the outcome should be, and the platform provisions an agent with its own browser, file system, and terminal, then connects it to the tools your company already uses.

The agent executes end-to-end tasks independently: browsing the web, creating and organizing files, calling tools, and checking back with you when it gets stuck. Because the work happens on the cloud computer, tasks continue even with your laptop closed.

Over time the agent updates its tools, skills, and memory around the job. Anything describes this as natural self-improvement — the agent gets sharper as it sees more data, like a person learning a routine rather than a script being patched.

• Describe the job to create a working agent in minutes
• Each agent gets a browser, file system, and terminal
• Tasks run continuously on the cloud, even offline
• Agents update their own tools, skills, and memory

Skydive Channels and Integrations

The platform connects to more than 600 integrations including Gmail, GitHub, Notion, and Linear, and agents work directly inside those tools rather than dumping results back into a chat. An agent can own a ticket in your project manager, draft inside your editor, and publish where the work actually lives.

Channels matter because agents meet you where you already work. Agents operate across Slack, email, iMessage, desktop, and the web with one identity and one memory, so you can hand the same agent a task from any surface and it picks up the same context. Schedules can be set so recurring jobs run on their own, which turns daily upkeep into work that quietly happens in the background.

Model choice is an option rather than a lock-in. The platform supports more than 170 frontier and open-weight models, which matters for teams that want to run cost-effective open models for routine work and reserve frontier models for harder tasks.

Access is granted on demand rather than configured up front. When an agent hits a task that needs a service it does not have, it asks for exactly what it needs and you approve with one click. Credentials are stored securely and injected at the network layer through a proxy, so the raw token never appears in the agent's prompts, logs, or memory — you grant real access without handing over keys.

• 600+ integrations including Gmail, GitHub, Notion, and Linear
• Agents act directly inside the tools teams use
• One agent identity across Slack, email, iMessage, and the web
• Support for 170+ frontier and open-weight models
• One-click service approval; credentials injected via proxy, never leaked

Building and Managing Skydive Agents

Everything is designed for the employee closest to the work, not a centralized AI team. Templates for customer support, SEO, bug investigation, and chief-of-staff-style work give teams a starting point, and each template adapts to company-specific tools and processes.

Administration is centralized around governance. The platform handles model access, computing sandboxes, permissions, security, and infrastructure, while administrators centrally manage access, data, AI usage, and spending. Employees build freely within those rails, which spreads agent creation without creating chaos.

The realism check is that any autonomous agent touching business systems needs oversight. Reviews of what an agent did, spending controls, and clear permissions are prerequisites, and the platform exposes each of those surfaces to admins rather than hiding them.

Enterprise security has substance behind it. Each agent runs on its own dedicated virtual machine in the cloud that no other agent shares or can access, and the vendor reports a completed SOC 2 Type 1 audit plus a CASA (Cloud Application Security Assessment) validated by an independent third party against the OWASP ASVS standard. VPC or single-tenant deployment keeps the whole workspace inside your network for buyers on sales-assisted plans.

• Job templates for support, SEO, bug investigation, and more
• Built for employees closest to the workflow, no AI team required
• Central admin rails for access, data, usage, and spending
• Oversight features for agents acting on business systems
• Dedicated VM per agent; SOC 2 Type 1 and CASA audit reported

Who Skydive Is For

The platform fits teams that have repetitive, multi-step work with clear outcomes and existing tooling to attach agents to. Customer support triage, recurring reporting, ticket classification, and inbox management are the kinds of jobs an agent can own end to end, provided the expected result is easy to state and easy to check.

It matters less for teams whose work is unstructured creative judgment or where the risk of an agent acting without review outweighs the automation gains. A legal review or a client-facing contract step probably is not the first job to hand to an autonomous agent.

The no-code creation model also means adoption can spread from a single team. Once one agent works, the pattern tends to spread because the cost of building the next one is low — which is exactly how Anything describes its own rollout.

• Best for clear, multi-step, tool-heavy work
• Support, reporting, and inbox triage are natural fits
• Less suited to unstructured judgment or high-risk steps
• No-code model lets successful agents spread across teams

Skydive Alternatives

Several agent platforms already live in this directory. OpenComputer offers AI with a computer-like interface, while Manus builds general-purpose research and task agents. Both compete on autonomy, though the platform's edge is the breadth of channel and tool integrations plus creation-by-description.

Genspark and ChatGPT Agent cover agent-style assistance within broader assistants. ChatGPT Agent lets you spin up agents for specific jobs inside OpenAI's ecosystem, and Genspark bundles autonomous research agents with its search product.

The practical difference is where the agent lives. The platform emphasizes a persistent cloud workspace with its own files and memory connected to your real tools, while many alternatives run as sessions inside a chat product. Teams that want work to continue in the background across Slack and email will lean toward a workspace-first model, which is the philosophy here.

• OpenComputer and Manus — autonomous general-purpose agents
• Genspark and ChatGPT Agent — agents inside broader assistants
• The platform leans on persistent cloud workspaces and 600+ integrations
• Choice depends on where you want the agent to live and act

Skydive Pricing

Free sign-up with usage-based billing for the AI models and compute each agent consumes. Optional Starter ($20/month) and Team ($200/month) plans add admin and security controls, a self-serve Enterprise tier starts from a $10,000 annual commit, and sales-assisted Enterprise adds custom terms and VPC deployment. No seat licenses and no markup on model costs.

Best For

Recommended use cases and scenarios where Skydive shines.

Frequently Asked Questions

Common questions about Skydive, answered.