Team managers
Organize related conversations into named teams with a manager that monitors progress, coordinates members, and surfaces decisions requiring user input.
CodeAF
CodeAF coordinates AI coding agents, teams, and task workflows in one interface. Delegate development work, run checks, and monitor project progress.
AI coding agents organized as software teams
CodeAF is a coding-agent workspace for running multiple software-engineering agents from one window. It combines conversations, teams, task plans, sessions, checks, and spend tracking so users can delegate development work while retaining a view of what is running and what needs attention.
A request can be broken into dependent subtasks, assigned across a team, and checked as work lands. For larger or more specialized jobs, users can invoke a dedicated harness such as `senior-dev`; managers and specialists can continue work, report status, and ask the user only when a decision requires human input.
Features
Task planning and parallel execution
Turn a request into a plan with nested tasks and dependencies, then claim ready work and run multiple tasks concurrently when they are independent.
Specialists
Use complete, task-specific coding harnesses such as `senior-dev`. Specialists can run an engineering workflow from brief to checked result and continue independently for extended jobs.
Standing orders and watchers
Express recurring rules, scheduled reminders, and event-based watches in plain English, scoped to a chat, project, or broader workspace.
SSH-native remote access
Run the conversation on a development machine and attach from other devices over SSH; the documentation states that closing the laptop does not stop active work.
Model and spend visibility
Track spending and model allocation in the interface, with Pareto crewing selecting models for different task roles and the product describing cost-aware model assignment.
Use cases
Delegating feature work
Describe a feature or bug fix, let CodeAF turn it into subtasks such as implementation and tests, and monitor which items are running, complete, or waiting for a decision.
Coordinating an engineering project
Create a named team for a project such as storefront, billing, or a parser, then let a manager coordinate several focused conversations while keeping the project status in one view.
Handling focused engineering jobs
Invoke a specialist for work that benefits from a dedicated workflow, such as reviewing a pull request, migrating a package, or making a larger code change that needs independent checking.
Monitoring work away from the development machine
Attach to a running development session from another device over SSH when moving between a desk, laptop, or phone, without making the network connection part of the active coding loop.
Applying repeatable project rules
Define recurring instructions such as running tests before completion or notifying the team when an API changes, using plain-language standing orders rather than a separate configuration language.
Pros and Cons
Pros
- Provides a single control plane for multiple agent conversations and named teams.
- Supports task decomposition, dependencies, parallel execution, and progress reporting.
- Offers dedicated specialists with their own workflow, checks, and model access through CodeAF.
- Includes SSH-based access to work running on a development machine.
- Adds acceptance checks and a record of failed commands and fixes to support more controlled execution.
Cons
- The supplied evidence does not establish pricing, plan limits, or a complete integration list.
- The product is designed around agent orchestration and software projects, so its fit for non-development workflows is not established by the source material.
- Some capabilities are described at a high level; setup details for the full team, session, and handoff workflow are limited in the available documentation.
FAQ
How do I install CodeAF?
Install CodeAF with the one-line command `curl -fsSL https://agentfield.ai/get/codeaf | bash`, then run `codeaf` in a project. The documentation presents creating a first team as the next setup step.
Can CodeAF manage multiple agent teams?
Yes. CodeAF groups conversations into named teams, each with a manager and member conversations. Managers coordinate work and ask the user when they encounter a decision they cannot make.
How do specialists work in CodeAF?
Specialists are started in a conversation with a command such as `/senior-dev` followed by a brief. A specialist runs as its own task, with an independent workflow and checked result; CodeAF can also suggest handing work to a specialist when the task fits.
What does a CodeAF task produce?
The documented workflow includes planning a request into subtasks, running work, executing checks such as tests or build commands, and reporting the resulting status. The site also describes held-out acceptance criteria that are kept separate from the worker's task list.
Where can I find CodeAF pricing and integrations?
The available evidence does not document pricing, plan limits, or a current integration inventory. The pricing URL provided for the product is a not-found page, so those details should be confirmed with the vendor.
Quick Facts
- Category
- Developer tool / AI coding agent
- Primary users
- Software developers and engineering teams
- Workflow
- Teams, managers, conversations, tasks, specialists, and checks
- Installation
- One-line shell installer, then run in a project
- Remote access
- SSH-native access to work on a development machine
- Pricing
- Not documented in the supplied sources
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