Captain task coordination
Turns one request into tasks for agents that suit the work, while the Captain checks progress against the original ask and can steer agents back when they drift, skip tests, or stop short.
Parallax
Parallax is Conifer’s tool for coordinating multiple AI coding agents and reviewing their work against the original task, not just the final diff. It helps developers run agents in parallel, verify findings with tests, and receive eligible fixes as pull requests.
AI coding-agent orchestration and review
Parallax is a coding-agent orchestration and review tool from Conifer. It lets developers run agents such as Claude Code, Codex, Cursor, Gemini CLI, OpenCode, Amp, and Capy side by side, while the Captain coordinates tasks against the user's original request.
When a session ends, Parallax captures the session context and asks the Conifer router to select reviewers from other model labs. Those reviewers inspect the work in a throwaway copy of the repository, verify eligible findings with tests, and return review results and, where supported, a fix pull request. The product is intended for developers who want parallel agent work with review tied to the full session rather than only the final diff.
Core features
Session-aware review
Records what the session was asked to do, what the agent read and changed, and what it claimed, then reviews the completed work against that session context rather than only its diff.
Cross-lab reviewers
Selects reviewers from other model labs through the Conifer router, so the models reviewing a session are not the same lab that wrote the code.
Evidence-based findings
Investigates bugs, security holes, dead code, and slower-than-needed code in a throwaway copy of the repository. Findings are labeled by the verification result.
Verified fix pull requests
Creates one fix pull request per review for eligible proven or suite-green patches, with GitHub checks that annotate proven mechanisms. Other findings remain in the review summary and console.
Subscription switching
Can connect several Claude and Codex subscriptions and move active work to another subscription when one reaches its limit. Conifer credit can also be used when configured plans are unavailable.
Use cases
Parallel feature implementation
Give one feature request to the Captain and distribute suitable subtasks across Claude Code, Codex, Cursor, or other connected agents, then collect the resulting pull requests.
Requirement-focused code review
Use a session-aware review after an agent finishes a change. Reviewers inspect the broader task context and can catch behavior that appears acceptable in the final diff but does not satisfy the request.
Pre-merge risk checking
Run independent checks for defects, security issues, dead code, or performance regressions, with tests in a throwaway repository copy separating reproduced findings from unverified claims.
Long-running agent work
Keep an in-progress task moving by connecting multiple Claude or Codex subscriptions and allowing Parallax to switch to another available subscription when one reaches its usage limit.
Evidence-based maintenance
Use the generated review summary, GitHub annotations, and fix pull request to triage verified changes before merging them into a repository.
Pros and Cons
Pros
- Coordinates multiple coding agents around one request instead of requiring each task to be managed separately.
- Reviews session context as well as code changes, helping surface problems that a diff-only review may miss.
- Uses tests and sandbox verification to distinguish proven findings from claims that could not be established.
- Can return eligible fixes as pull requests and annotate proven mechanisms in GitHub checks.
- Supports switching among connected Claude and Codex subscriptions when a limit is reached.
Cons
- The available evidence does not document detailed agent-by-agent compatibility, configuration options, or team administration workflows.
- Linux access is currently browser-based through a local daemon rather than a native window.
- Review quality and available model choices depend on the configured agents, subscriptions, Conifer routing, and repository testability.
FAQ
How does a Parallax review work?
Parallax records the coding-agent session as it ends, including what was requested, read, changed, and claimed. It then sends the task to reviewers selected by the Conifer router from other model labs.
What does Parallax check?
Reviewers inspect the completed work for bugs, security holes, dead code, and slower-than-needed code. Findings are tested in a throwaway copy of the repository and labeled according to the evidence, such as proven, suite green, unverified, could not run, or refuted.
When is a problem considered proven?
A finding is labeled proven only when a reviewer writes a test that fails on the current code and passes with the proposed fix. The broader test suite is also run with the fix, and patches that regress the suite are not offered as one-click suggestions.
What does Parallax produce after a review?
Parallax can produce a fix pull request containing eligible proven or suite-green patches. GitHub checks annotate proven mechanisms, while other findings remain in the review summary and console.
Which platforms can run Parallax?
The product page provides a macOS download and setup flow. It also documents a Linux build that runs as a daemon and is accessed at http://127.0.0.1:7878; there is no native Linux window yet.
Quick Facts
- Category
- Developer Tool
- Primary platform
- macOS; Linux via local daemon and browser
- Primary users
- Developers using AI coding agents
- Supported agents named on the product page
- Claude Code, Codex, Cursor, Gemini CLI, OpenCode, Amp, and Capy
- Review output
- Evidence-labeled findings and eligible fix pull requests
- Free onboarding offer
- New GitHub sign-ups receive $50 of Conifer credit and 5 free reviews; review credits are separate from gateway credits
Alternatives à Parallax
ByteAsk
ByteAsk is a terminal-first AI coding agent for C and C++ that edits repositories and verifies changes with the real compiler, debugger, sanitizers, and tests before showing a diff. It offers a free tier plus paid plans, with editor connectors and zero-retention handling described in the source.
GitBot
GitBot is a local browser-based workspace for creating reusable coding bots powered by Claude Code, Codex, or OpenCode. It helps developers run those agents across repository folders with persistent threads and configurable permissions.
Manta AI
Manta AI is an autonomous web app testing tool for teams that want to map application behavior, catch regressions, and generate tests without writing scripts or maintaining selectors. It works from a URL and supports plain-English test flows, run results with screenshots, and scheduled or deployment-triggered checks.
Ghost
Ghost est un assistant IA en terminal pour discuter, générer du code et lancer des tâches en ligne de commande. Modèles gratuits, Linux, macOS, Windows, open source.
Vi3ecode
Vi3ecode is a maintained development environment for working with AI coding agents. It keeps project context, terminal, Git, memory, flows, review, and communication connected around the agent you already use.
CreateOS Sandbox
CreateOS Sandbox is an isolated compute environment for running code and agent workloads inside Firecracker micro-VMs. It is designed for workflows that need machine-level isolation, private networking between sandboxes, and programmatic control through SDK, CLI, or MCP.