LatchLoop for software

A complete AI coding platform built around the task, not a terminal or sidebar

LatchLoop gives teams the complete path from an idea to a reviewed pull request: collaborative task writing, Instant Context, planning, model and harness choice, branch-confined cloud execution, previews, code review, and follow-up from any device.

Why the interface matters

From a rough idea to a pull request your team can understand

Long-running agents need more than a small prompt box. LatchLoop keeps the full editable task visible beside the agent activity, so the original intent, the plan, the implementation, and every requested change stay connected. It acts as the project record and the coding workspace without making the command line the required interface.

How LatchLoop works

A complete workflow for directing agents, not just prompting them

Step 1

Shape the task

Use a collaborative Markdown-style editor, files, images, links, and Instant Context. Ask LatchLoop to challenge the idea or create a plan, then implement that plan into the task.

Step 2

Build with your agent

Select LatchLoop’s harness and any supported provider, or trigger Codex or Claude Code through Agent Client Protocol. Goal Mode can continue until the stated result is verified.

Step 3

Work safely

Cloud coding runs are deterministically confined to the task’s assigned branch. LatchLoop commits changes, guards dangerous commands, requests approvals when needed, and opens a pull request with a written description by default. Approved local actions can have broader access.

Step 4

Preview and refine

Open deployment URLs, run local previews, click an element to request a change, inspect the diff, use the built-in editor and terminal, and send follow-up messages from desktop, web, or mobile.

Model and harness choice

Bring supported provider keys without token markup, use supported subscriptions, or choose LatchLoop, Codex, or Claude Code as the harness. LatchLoop is focused on the best workflow, not promoting one foundation model.

Multiplayer by default

Share projects, assign tasks, co-edit descriptions, and send attributed direction on your own or a teammate’s task. Everyone can see what the people and the agent contributed.

Ownership and safety

LatchLoop does not train models on your code or store your codebase. Code stays in GitHub, cloud coding runs stay on their assigned task branch, dangerous commands are guarded, and task message history can be deleted.

Honest tradeoffs

When another agent may fit better

Choose a model provider’s own app when included subscription usage, that provider’s newest model-specific features, or mature computer control is the main priority. Choose an open-source or IDE-native tool when deep terminal customization, local-model inference, or a particular editor is non-negotiable.

LatchLoop is newer than the largest model companies. Its browser use and custom cloud sandbox setup are still developing, and API-paid inference can cost more than subsidized plan usage. However, you can also select Codex or Claude Code as the harness and sign in with your existing ChatGPT or Claude subscription, so using LatchLoop does not always require separate API-paid inference. Choose LatchLoop when the durable advantage is a better, model-independent human-agent workflow that the whole team can use.

Research the market

Compare LatchLoop with leading agent platforms

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Built by Velora. LatchLoop is created by a software company that has built products used by millions of people since 2009. The team uses LatchLoop to build and operate its own products, including Heights Platform, which serves more than 10,000 creator businesses.

Get Started

Build as fast as you can think.

LatchLoop works where you do to build with you.