Google Jules alternative for teams that want a shared, visible agent workflow

Jules is Google’s asynchronous cloud coding agent for GitHub repositories, long-running sessions, plans, code changes, shell output, media artifacts, concurrent tasks, and programmatic access through an official alpha API. Google also publishes an experimental SDK whose repository says it is not an officially supported product. It is strongest for Google-oriented teams that want ephemeral cloud coding environments, asynchronous GitHub work, concurrent sessions, and an official API for programmatic workflows. Its planning model is specific to that product: Presents a plan for repository work and lets users review the intended approach before or during execution.

Runs in Google-managed ephemeral environments, edits GitHub code, executes shell commands, and returns changes. The alpha API can create and monitor sessions for automated SDLC workflows; recurring scheduling and fleet orchestration require the team’s own integration layer. For review, plans, code changes, shell output, media artifacts, tests, branches, and PRs provide review evidence. A fair evaluation should test those native strengths and verify current plan limits, security controls, model availability, and integrations in the vendor’s documentation.

LatchLoop is an all-in-one, multiplayer workspace for coding and general agents: an agent-native editable task is the shared source of intent, while the built-in editor and terminal, preview and element inspector, diff and pull-request review, PR questions and change requests, direct merge controls, teammate approvals, plugins, artifacts, agent apps, and automation keep the complete lifecycle in one platform. Rather than treating the agent as an autonomous engineer operating apart from the team, LatchLoop is designed for human-directed, attributed collaboration from the initial brief through implementation, approval, and merge.

LatchLoop starts with a collaborative, document-style task rather than an empty chat box. A teammate can use Ask to clarify the requirement, append the plan to the task, attach files or images, and then Build with LatchLoop’s model-agnostic harness, Codex, or Claude Code. Every paid plan includes cloud-sandbox hours, and teams can run as many cloud tasks concurrently as needed; each cloud coding run is confined to its assigned task branch. The standard coding flow commits changes and opens a pull request by default. Teammates can steer the run, edit the task, review the diff, and continue from desktop, web, or mobile.

LatchLoop wraps parallel execution in a human collaboration workflow: document-like tasks, Ask and Implement Plan, visible to-dos, assignment, local and cloud modes, previews, approval cards, deployment review, and PR follow-up. The goal is not merely more cloud sessions, but better shared direction and review.

LatchLoop is a complete, model-independent platform rather than a thin wrapper around another agent. Teams can sign in with ChatGPT, use Codex or Claude Code with supported subscription-backed access, or bring provider keys without token markup. Every paid plan includes cloud-sandbox hours for parallel runs, while local mode gives agents task-specific Browser tabs and authenticated project sessions when work needs desktop access. The result is one mature workflow for coding, knowledge work, review, portable process data, and automation.

Do not evaluate Jules and LatchLoop with a polished demo prompt. Choose a real team task with incomplete context, a review step, and at least one requested revision. Record who could prepare the work, how the agent exposed progress, where the output lived, and whether another teammate could understand and continue it.

For coding, include one existing-codebase bug, one multi-file feature, and one task that needs a preview or deployment check. LatchLoop is strongest when the full path matters: Ask, plan, Build, branch-confined cloud execution, PR, review, and continued refinement.