Follow the Sun

Your distributed team runs AI agents around the clock — but every shift change kills the context. Helix makes agent handoff between developers zero-friction, across any time zone.

The context dies at every shift change

Your team hasn't written code manually in months. Every developer runs an AI coding agent — Claude Code, Codex, Gemini CLI — and the output is good. Features that took weeks now take hours.

But what happens when the developer's shift ends?

The agent has been working all day. It's accumulated context — dozens of prompts, hundreds of responses, an understanding of the codebase, knowledge of what it tried and what failed, a running application it's been testing in the browser. The developer closes their laptop. All of that context is gone.

Within minutes, a developer halfway around the world opens their own machine. Fresh agent. No context. They start from scratch.

The handoff tax

The workaround is always some version of the same thing.

A developer finishes their shift. They spend 20–30 minutes writing a summary: what they worked on, what the agent did, what's left to do, what to watch out for. They post it in Slack or Teams or a shared doc. The next developer reads the summary, opens a fresh agent session, and spends another 30–60 minutes re-prompting the agent to reconstruct the context that the previous developer's agent already had.

Multiply that by every task, every shift change, every day. For a team spanning three time zones, that's six handoffs per task per day. Each one loses context. Each one costs time. A human summary of an agent session is never as complete as the actual session.

The agents are fast. The handoff is slow. For teams fully committed to AI-assisted development, the handoff is the bottleneck.

Cloud dev environments weren't built for agents

Cloud development environments — Microsoft Dev Box, GitHub Codespaces, Amazon WorkSpaces, Google Cloud Workstations, Citrix DaaS, Gitpod — were designed for a world where humans write code. They give each developer a private, isolated workspace. That isolation makes sense when humans are the ones typing. It becomes a problem when agents are doing the work.

These tools have no concept of agents:

• No shared agent context. Every workspace is private. The agent's conversation history, its accumulated understanding of the task, its running state — all trapped on one developer's machine.
• No multiplayer. Two developers can't watch the same agent work, let alone both direct it.
• No workflow layer. No specs, no kanban board, no review gates. Just a blank desktop and whatever the developer decides to do with it.
• No handoff mechanism. When the shift changes, the incoming developer gets nothing except whatever their colleague remembered to write down.

These tools were built for developers who work alone on their own machines. That model breaks down with AI-first distributed teams.

What changes when the agent lives on the server

Helix runs agents in sandboxed agent computers on the server — not on developer laptops. Every agent gets a full GPU-accelerated streaming desktop with a browser, terminal, filesystem, and the AI coding agent running inside it. The agent computer persists independently of who's managing it.

When a developer in Tokyo finishes their shift, they close their browser tab. The agent computer keeps running. The agent's full conversation history, the spec it's working from, the running application, the entire environment — all of it stays where it is.

When a developer in London starts their day, they open the same task. Same desktop. Same chat history. Same running app. Same agent. They pick up where Tokyo left off. No reconstruction. No re-prompting. No context loss.

Multiplayer by default

Multiple developers can be inside the same agent environment simultaneously — watching the agent work, sending it instructions, interacting with the running application. One developer might review what the agent built overnight while another directs it to fix a bug. The full chat history shows every instruction from every developer who's touched the task.

In a live demo, two Helix team members — one in the US, one in the UK — both interacted with the same agent desktop at the same time. One added a user to the app the agent had built. The other watched it happen in real time and continued directing the agent. No setup. No configuration. Just open the task.

Specs, not summaries

The reason handoff works isn't just "persistent desktop." The agent works from a spec — a structured plan that's reviewed and approved before implementation begins. The spec is stored in git. It's visible on the kanban board. It describes what the agent is building, why, and how.

When a new developer picks up a task, they don't need a summary from the previous developer. They read the spec. They see the agent's progress. They review the chat history. The work is legible because it's spec-driven — not a pile of ad-hoc prompts that only made sense to the person who typed them.

Agents that keep working between shifts

Because the agent computer lives on the server, the agent can continue working when no human is watching. It executes against the approved spec, runs tests, makes progress. The incoming developer reviews what the agent accomplished, approves or corrects course, and directs the next phase. The agent works. Humans across time zones take turns reviewing and directing.

What your project manager sees

Every task is a card on the kanban board. The board shows every task across every time zone — Backlog, Design Review, Implementation Review, Done. No chasing developers across time zones for status updates. Open the board and see where everything stands.

Specs are reviewed before implementation begins. PRs require human sign-off before merge. The board moves. The manager manages the flow — regardless of whether the developer working the task right now is in Kyiv, Karachi, or Kansas City.

Cloud dev environments vs. Helix

24 hours of development

For teams with developers in Japan, the US, Europe, Ukraine, Pakistan, Serbia, Georgia — development doesn't have to stop when a shift ends. The agent keeps working, and humans across time zones take turns directing it.

One developer in Asia finishes their day. A developer in Europe picks up the same task, same environment, no transition. Eight hours later, a developer in the Americas takes over. The agent has been working the entire time. Context compounds instead of resetting.

This is what AI-first distributed teams are already trying to do — writing summaries in Slack, re-prompting agents from scratch, losing hours every day to context reconstruction. Helix removes that step. The handoff is opening a browser tab.

Runs on your infrastructure

Distributed teams with private codebases need this on their own infrastructure — not sending source code and agent conversations through a third-party SaaS. Helix deploys on your Kubernetes cluster, your VMs, or any cloud provider: OVH, Azure, AWS, Hetzner, GCP. Your agents, your code, your network.

For teams that prefer managed infrastructure, Helix Cloud offers the same capabilities as a SaaS service — zero setup, we handle the GPUs.

Either way, Helix integrates with the tools you already use. Azure DevOps, GitHub, GitLab, Slack, Teams, and any MCP-compatible service. Your existing CI/CD pipelines, your existing identity provider (Active Directory, OIDC), your existing workflows.

Get started

Self-hosted: Deploy Helix on your infrastructure — Kubernetes, bare metal, or any cloud. RBAC, SSO, audit logging, unlimited agent desktops. Full control, full privacy. Talk to us about an enterprise pilot →

Helix Cloud: Managed infrastructure, zero setup. Same capabilities — shared agent environments, multiplayer, spec-driven workflows, kanban board. We handle the GPUs. Join the waitlist →