Skydive

About Skydive

Skydive is a cloud AI agent platform from Anything. It is designed for teams that want software agents to carry out multi-step work rather than only answer questions in a chat window. A user describes a role or outcome in plain language, gives the agent permission to use selected tools, and can continue the same conversation through the web, Slack, email, iMessage, a desktop application or a command-line interface. Each agent receives a cloud computer with a browser, terminal and file system, allowing it to move between websites, applications and files while a task is in progress. Skydive launched publicly in August 2026 and was featured on Product Hunt on August 27, 2026.

What does Skydive do?

Skydive creates persistent software agents for business work. Instead of requiring a user to draw a fixed automation flow, the platform asks for the desired job or result. The agent then determines the steps, works through connected applications and returns the output. Anything says an agent can browse websites, complete forms, create and organize files, run code, download reports and upload finished work. When a login, approval, captcha or two-factor authentication step requires a person, the user can take control of the shared browser and then return control to the agent.

Every agent has a role, identity and memory. Corrections, preferences and company knowledge can carry into later conversations, which is intended to reduce repeated briefing. Users can also create routines for recurring work. These routines continue in the cloud when the user's laptop is closed and report results on a schedule.

Where can teams work with Skydive agents?

The same Skydive agent can be reached through several interfaces. The official launch materials list Slack, email, iMessage and the web, while the company also offers a desktop application and a command-line interface. Conversations retain the same agent identity and memory across those surfaces. This makes the product relevant to teams whose work begins in one channel but finishes in another.

Skydive also connects with business tools such as Gmail, GitHub, Notion, Linear, Intercom, Google Calendar and Google Drive. Anything states that the platform can connect to hundreds of tools. Where a clean OAuth, API or MCP connection is unavailable, the agent may use its browser like a person would, subject to the access granted by the user.

How does Skydive support multiple agents?

Skydive is designed to support a team of specialized agents rather than a single general assistant. Each agent can have its own scope and cloud environment. Agents can share context and hand work to one another, allowing one agent's result to become the starting point for another. For example, a research agent may prepare a prospect list before another agent updates a CRM and a third drafts outreach.

This model may suit work that crosses departments or applications, but buyers should define permissions and review points carefully. More autonomous execution increases the importance of access controls, auditability, data handling rules and human approval for consequential actions.

Who is Skydive for?

Skydive is aimed at founders, operators and teams that manage recurring work across multiple tools. The company provides examples covering customer support, software engineering, marketing, operations, recruiting, finance and executive assistance. Templates are available for roles such as chief of staff, customer support, SEO and bug investigation, so a non-technical user can begin from a defined job rather than an empty automation canvas.

The product is especially relevant when a task lasts longer than one conversation, needs a browser or file system, or must continue after the user's computer is offline. A conventional chatbot may be sufficient when the requirement is limited to drafting, summarizing or answering questions without taking action in external systems.

Who worked on Skydive?

Product Hunt identifies the people who contributed to the Skydive launch across company leadership, engineering, design, marketing, customer support and people operations. The listed makers are Amy Fraser, Marcus Lowe, James Pulec, Dhruv Amin, Joshua Nam, Arnav Surve, Brendan Teo, Philip Kim, Vento Li, Rain Dong, Eldar Gilmanov, Leo Acevedo, Genevieve Tankosich, Dylan and Zaria Zinn.

Roles explicitly shown on the Product Hunt team page include Dhruv Amin as co-founder of Anything, James Pulec as a full-stack developer, Brendan Teo as a frontend engineer at Anything, Philip Kim as a mobile engineer working with Anything and Skydive, Vento Li as a software engineer at Anything, Rain Dong as a designer, Genevieve Tankosich as social media manager, Dylan in customer success and support, Amy Fraser in people operations, and Zaria Zinn as head of marketing at Skydive. Product Hunt does not display a specific role beside every listed maker, so BrandLigo does not infer missing job titles.

How much does Skydive cost?

Pricing checked on August 28, 2026. The official Skydive start page lists Starter from $20 per month, including unlimited agents, up to five users and pay-as-you-go usage without a markup on AI model costs. Team is listed at $200 per month with additional usage and priority support. Model and compute consumption is billed according to use.

Enterprise pricing is custom. Skydive lists security administration, audit logs, model controls, integration controls, network controls and support options for enterprise customers. Its self-service Enterprise offer starts with a $10,000 annual commitment, while sales-assisted arrangements are intended for larger deployments or organizations needing tailored terms, invoicing, a single-tenant environment or a virtual private cloud deployment. Buyers should confirm current prices and usage charges directly before purchasing.

What security and control questions should buyers ask?

Skydive says Enterprise customers receive usage tracking, spend controls, audit logs and administrative controls over models, integrations and networks. It also states that data is encrypted at rest, Enterprise customer data is not used to train models, and the service is SOC 2 certified. Organizations should still review the current trust documentation and contract because an agent may receive access to email, source code, customer systems and internal files.

A practical evaluation should begin with a narrowly scoped role. Teams should check which credentials the agent receives, what actions require approval, how access can be revoked, where files persist, how long data is retained and whether the selected AI model meets internal privacy requirements.

How is Skydive different from chatbots and workflow builders?

A chatbot commonly produces an answer and leaves the user to perform the work. A workflow builder can take actions, but usually requires someone to define and maintain each step. Skydive positions itself between those models: the user describes an outcome, and a persistent agent decides how to work through the task using its cloud computer and connected tools.

That flexibility can reduce setup work for changing processes, but it also produces a different risk profile from a fixed automation. Teams that need deterministic execution, strict step-by-step validation or a simple connection between two applications may prefer a conventional automation platform. Teams that need research, judgment, browser interaction and work across several systems may find the agent model more appropriate.

Who should choose something else?

Choose a standard chatbot when the main need is writing, analysis or question answering and no external action is required. Choose a workflow platform such as Zapier or Make when the process is stable, every step should be explicit and predictable, and administrators want a visual record of the automation. A dedicated coding agent may be a better fit when all work stays inside a software repository and developers do not need the same agent in email or business applications.

Skydive should not be adopted only because a task can be automated. It is best evaluated where persistent memory, multi-application work, scheduled execution and agent collaboration provide a clear operational benefit. Start with low-risk tasks, compare the delivered output with the existing process, and expand access only after reliability and governance meet the organization's requirements.