AI Multi-Agent Programming: The Future of Development
When one AI agent is not enough, orchestrate multiple AI agents to tackle complex projects — from architecture design to implementation to testing, all in parallel, including code review and large refactoring. The official docs of Claude Code, Codex and OpenCode each show how to enable multi-agent work, configure it, and what it costs.
What is Multi-Agent Programming?
Multi-agent programming uses multiple specialized AI agents working together to solve complex development tasks. Instead of a single AI handling everything, each agent focuses on what it does best — architecture design, front-end and back-end work, unit tests and code review — each in its own context, while a lead agent or a script splits the work and combines the results. As of October 2026, Claude Code, Codex and OpenCode each document their own approach, in different forms.
Parallel Development
Multiple agents write code at the same time, so frontend and backend move forward in parallel without waiting on each other.
Specialized Roles
Each agent focuses on one area (architecture, implementation, testing, security) and plays to its strengths.
Higher Quality
Agents review each other's code and spot problems from multiple angles.
Multi-Agent Approaches in Claude Code, OpenCode and Codex
Claude Code Agent Teams
The multi-agent feature in Claude Code's docs: a lead plus teammates that share a task list and can message each other directly.
Architecture: lead -> teammates (separate instances) -> shared Task List
OpenCode Multi-Agent
Open-source multi-agent architecture with built-in Build and Plan agents and support for custom agents, combined to cover different development flows. OpenCode's official docs split agents into primary agents you talk to and subagents invoked by a primary agent or via an @ mention; both kinds can be customized. The oh-my-opencode plugin's repository is now oh-my-openagent, and QCode's docs no longer list its old built-in agent roles.
Architecture: primary agents + subagents; built-in Build/Plan and General/Explore/Scout, all customizable
Codex Subagents
OpenAI's Codex docs: current releases enable subagent workflows by default - Codex starts several agents on request and merges their results into one reply; custom agents are defined as TOML files.
Architecture: main session + parallel agent threads (view and switch with /subagents)
| Feature | Claude Code | OpenCode | Codex |
|---|---|---|---|
| Communication | Shared Task List + direct messaging | Invoked by the primary agent or via an @ mention | Independent execution |
| Number of Agents | Set by the task (docs: no hard limit) | 2 built-in primary and 3 subagents, plus custom ones | Spawned per task on request |
| Task Management | Shared Task List that teammates claim and complete | The primary agent dispatches specialists per task | Thread cap is set in config.toml |
| Cost (relative) | About 7x a normal session in plan mode (per docs) | Depends on the model each agent uses | Uses more tokens than single-agent runs (docs warn) |
Example scenarios
Parallel Feature Development
A frontend agent builds UI components, a backend agent writes the API, and a test agent writes test cases alongside them, moving forward in parallel.
Multi-Angle Code Review
A security agent checks for vulnerabilities, a performance agent analyzes bottlenecks, and a coverage agent assesses test completeness - problems surface from several angles.
Large-Scale Migration and Refactoring
Assign agents by directory or module, let each handle part of the migration, then verify everything together after merging - the refactor advances in parallel.
Multi-Agent with QCode.cc
One QCode.cc API key works across Claude Code, Codex, OpenCode and more; billing is per token and per-model prices are on /models.
One key across tools - Claude Code, OpenCode and Codex all use the same key
Cost control - the dashboard's usage stats show the model, token count and cost of each call
Flexible switching - pick the tool and model that fit each task
Hands-on, October 2026: setting up multi-agent work in Claude Code, Codex and OpenCode
Claude Code: five ways to run agents in parallel
As of 2026-10-20, the Claude Code docs list five ways to work on several tasks at once: subagents, agent view, agent teams, dynamic workflows and projects. They differ in who coordinates the work, whether the workers talk to each other, and whether they edit the same files.
- Subagents: workers inside one session that do a side task in their own context and return a summary. Define them as Markdown files in .claude/agents/ (project) or ~/.claude/agents/ (personal); only name and description are required, and model accepts an alias such as sonnet or opus or a full model ID.
- Agent teams: a lead plus teammates that share a task list and message each other directly. Experimental and disabled by default; set CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 to enable them. Teammates are only spawned in interactive sessions.
- Dynamic workflows: Claude writes a script that orchestrates many subagents, for jobs such as a codebase-wide audit or a 500-file migration; include ultracode in your prompt or ask for a workflow.
- Agent view: claude agents opens one screen to dispatch and monitor background sessions (research preview).
- Same files? Agent teams do not isolate teammates in worktrees, so partition the work by file; subagents can each get their own copy with isolation: worktree.
Codex: subagents and custom agents
OpenAI's Codex documentation says current Codex releases enable subagent workflows by default. Ask directly, for example spawn two agents or use one agent per point, and Codex starts agents in parallel and collects their results in one response; in the CLI, /subagents switches between agent threads. Codex ships with three built-in agents: default, worker and explorer.
Custom agents are TOML files in ~/.codex/agents/ (personal) or .codex/agents/ (project). Each must define name, description and developer_instructions, and can set model and model_reasoning_effort. Custom agents inherit the parent session's permissions, provider and MCP servers, so once your main session is configured, subagents use the same setup.
Global settings live under [agents] in config.toml, for example agents.max_concurrent_threads_per_session to cap concurrent threads and agents.default_subagent_model for the default subagent model. The docs note that subagent workflows consume more tokens than comparable single-agent runs, and suggest starting with read-heavy tasks such as exploration, tests, triage and summarization, being more careful with parallel write-heavy work.
OpenCode: primary agents and subagents
OpenCode's documentation describes two kinds of agents. Primary agents are the ones you talk to: the built-in Build and Plan, switched with the Tab key. Subagents are specialists a primary agent can invoke, or that you call manually with an @ mention such as @general; the built-in ones are General, Explore and Scout.
Define your own agents in the agent section of opencode.json, or as Markdown files in ~/.config/opencode/agents/ (global) or .opencode/agents/ (per project).
One QCode key for all three tools
As of 2026-10-20: for Claude Code, set ANTHROPIC_BASE_URL=https://api.qcode.cc/api and ANTHROPIC_AUTH_TOKEN to your QCode key (it starts with cr_). For Codex, add a custom provider in ~/.codex/config.toml with base_url = https://api.qcode.cc/openai and wire_api = responses (the provider name is up to you). For OpenCode, follow the OpenCode page in QCode's docs: using OpenCode requires the API direct access permission, which is off by default and is enabled for your key by online support on request.
A sample split: claude-opus-5-5 for the lead or orchestration, claude-sonnet-5-5 or claude-haiku-5-5 for workers; on the Codex side, gpt-6.1-sol, gpt-6-sol or gpt-5.6-terra. OpenAI's docs suggest gpt-6-luna for lighter subagents, but QCode does not offer gpt-6-luna for now, so use another GPT model. Billing is per token; per-model rates are listed on /models.
Cost check: Claude Code's docs say agent teams use approximately 7x more tokens than standard sessions when teammates run in plan mode. Pilot multi-agent runs on a small scope, then review usage per model in the QCode dashboard.
Multi-agent coding FAQ
What is multi-agent programming?
Several AI agents each work on part of a task in their own context, while a lead agent or a script splits the work and combines the results. Claude Code subagents, agent teams and dynamic workflows, Codex subagents and OpenCode subagents are all forms of it.
What is the difference between subagents and agent teams in Claude Code?
Per the Claude Code docs, subagents return results to the caller and cost fewer tokens because results are summarized back into the main context. Agent teams are fully independent sessions whose teammates message each other directly and share a task list; each teammate is a separate Claude instance, so the token cost is higher.
How do I run multiple agents in Codex?
Current Codex releases enable subagent workflows by default: ask Codex directly, for example spawn two agents or delegate this work in parallel, and use /subagents in the CLI to switch threads. For reusable roles, add TOML files to .codex/agents/ with name, description and developer_instructions.
How much more do multi-agent runs cost?
More, in proportion to how many agents run and for how long. Claude Code's docs put agent teams at approximately 7x the tokens of a standard session when teammates run in plan mode, and both the workflows and Codex docs warn that parallel agents use more tokens than a single run. Start small and give simple subtasks to lighter models. Personal Plans give a daily quota valid for 30 days, and if a day runs short you can buy a booster pack. With no personal plan and no wish for a monthly one, Pay-as-you-go Packs start at $4 for a one-time quota you use within 7 days.
Will parallel agents overwrite each other's code?
They can. Give each worker its own files or its own worktree: Claude Code subagents support isolation: worktree, while agent teams need the work partitioned by file. OpenAI's docs also advise caution with parallel write-heavy workflows in Codex.
How do I pay for QCode to power these tools?
With credit cards (Visa, Mastercard, AMEX), Apple Pay, Google Pay, Alipay, WeChat Pay or cryptocurrency across several coins and networks. One key calls Claude, GPT and leading Chinese models, so Claude Code, Codex and OpenCode can share it; setup is fully self-serve and takes a few minutes.
Unlock Multi-Agent Power
For always-on or parallel agents you can use QCode cloud servers: the server sits overseas, install Claude Code or Codex on it, and call models through QCode's endpoints with your QCode key. AI services and cloud servers share one balance; see the line comparison on qcode.cc/en/cloud.
Create a QCode account
One key across Claude, GPT and Chinese models, billed per token — live rates on /models.