Agent apps and code agents
Helix has two distinct types of agent. Understanding the difference prevents confusion about what each one does and when to use which.
Helix has two types of agent. They look similar on the surface — both use LLMs and have tools — but they serve different purposes and are configured differently.
Agent apps
Agent apps are conversational agents you build in the Helix UI. An agent app has a system prompt, an LLM, optional skills (web search, APIs, MCP servers), optional knowledge bases (RAG), and optional triggers (Slack, cron, webhook). You might build an agent app to:
- Answer customer questions grounded in your product documentation (RAG)
- Respond to support tickets via Slack or Teams
- Generate weekly reports on a schedule
- Call internal APIs based on user requests
- Handle live chat with a Crisp integration
Agent apps are created in Agents → New Agent and accessed via the Helix chat UI, an embedded widget, or the API. See Build an agent app for the full configuration walkthrough.
Code agents
Code agents run inside sandboxes and do software development. They read and write files, run tests, commit code, and open pull requests. They're what powers spec tasks.
Four code agent engines are available: Claude Code, Goose, Qwen Code, and Zed Agent. They all run in the same sandbox desktop; the difference is the harness, model access, and workflow features each brings.
Code agents are configured per project (as the agent: block in the project YAML) and are not interchangeable with agent apps.
Why two types?
The distinction reflects a difference in how the two agents are used and what they're optimised for:
| Agent apps | Code agents | |
|---|---|---|
| Where they run | In the Helix API process | Inside isolated sandbox containers |
| What they do | Converse, answer, call APIs | Read code, edit files, commit, test |
| Time horizon | One conversation turn | Hours of autonomous work |
| Approval model | None (conversational) | Plan approval before implementation |
| Output | Text, structured data | Git commits, pull requests |
An agent app that you ask "what does this function do?" is a different thing from a code agent that rewrites it.
The four code agent engines
These are not four different products — they're four pluggable engines for the same loop. Pick one per project:
- Claude Code — Anthropic's own CLI, best model quality for coding, uses your Anthropic key or subscription
- Goose — open-source, adds parameterised recipes for repeatable task types
- Qwen Code — open-source, works with any OpenAI-compatible provider including local models
- Zed Agent — Zed's built-in agent panel, no extra CLI, in-editor experience
See Choose and configure a code agent for when to pick which.
The agent loop
All code agents run through the same plan→implement→review loop. The engine choice doesn't change the structure of the loop; it changes the quality, cost, and workflow features within the implement step.
See How the agent loop works for the full picture.