Product
The operating system
for coding agents
Dispatch autonomous agents. Monitor progress. Review changes. Iterate with follow-up prompts. Design a prompt, get a feature out, iterate, publish.
Step 1
Dispatch autonomous agents
Write a prompt in the cloud dashboard and hit run. Trimo autonomously spins up a Docker container on your machine, clones your repo, and launches the agent in an isolated environment. Each pipeline gets its own branch. No babysitting required.
- ✓ Run multiple autonomous agents in parallel — each in its own container
- ✓ Automatic branch creation and git setup
- ✓ Framework-agnostic — currently supports Claude Code
trimo/jwt-auth
Writing auth middleware...
trimo/product-api
Running test suite — 23/24 passing
trimo/admin-layout
Completed — 4 files changed, 2 runs
trimo/login-validation
Test failure — needs review
Step 2
Monitor everything
Your autonomous agents work in the background while you focus on what matters. See all pipelines at a glance — which agents are working, which finished, which need attention. Real-time output streaming. No terminal switching.
- ✓ Web dashboard accessible from any device
- ✓ Real-time agent output and status updates
- ✓ Resource monitoring prevents OOM kills
Step 3
Review and iterate
Inspect diffs per run. Spot an issue? Write a follow-up prompt. The agent runs again with full context — same branch, same commits, building on everything before.
- ✓ Diff views per run — see exactly what changed
- ✓ Pipeline continuity across multiple runs
- ✓ Course-correct with follow-up prompts
Run 1 — Broad implementation
"Build the user auth flow with email/password and OAuth."
+342 lines across 8 files
Run 2 — Correction
"Use JWT with refresh rotation instead of sessions."
+89 -156 lines across 4 files
Run 3 — Polish
"Add rate limiting on login and fix email validation."
+67 lines across 3 files
Built-in
Git as infrastructure
Git isn't an afterthought — it's baked into the core. Every change is committed and pushed automatically. Destructive operations are blocked. Agent work is never lost, even if the container crashes. When the pipeline finishes, a pull request is ready for review.
Architecture
Docker isolation,
local execution
Every autonomous agent runs in its own Docker container with kernel-level isolation. Separate filesystem, network, and process space. Your code stays on your machine — the cloud dashboard only sees metadata.
- ✓ No cloud compute costs — runs on your hardware
- ✓ Source code never leaves your machine
- ✓ No token markup — use your own API keys
Cloud dashboard
UI, state, pipeline history, monitoring
Local daemon
Runs on your machine, manages Docker containers
Container 1
Agent A
Container 2
Agent B
Container 3
Agent C
Everything you need
Every feature included. Free, with no limits.
| Feature | Free |
|---|---|
| Execution | |
| Daemons (connected machines) Background processes on your machines that execute containers and stream status to the cloud dashboard. | Unlimited |
| Parallel pipelines (containers) Run multiple agent pipelines side by side, each in its own isolated Docker container. | Unlimited |
| Workspaces (repositories) Each workspace maps to a repository with its own configuration, pipelines, and run history. | Unlimited |
| Docker isolation per run Every agent run executes in a fresh container — your machine and other pipelines stay protected. | ✓ |
| Workflow | |
| Pipeline continuity Chain multiple runs into one pipeline. Prompt history, diffs, and branch context carry forward automatically. | ✓ |
| Git auto-commit and auto-push Agent work is committed and pushed automatically. No changes are ever lost. | ✓ |
| Agent safety rails Blocks destructive git and CLI commands and enforces branch policies so agents can't go rogue. | ✓ |
| Diff views per run Review exactly what each agent run changed before writing the next prompt or merging. | ✓ |
| Custom multi-step workflows Define DAGs of agent steps in a visual node editor and store them for reuse. Steps run automatically with parallel branching and joining. | ✓ |
| Intelligence | |
| Prompt history Every prompt, diff, and developer response is captured as a structured record for full traceability. | ✓ |
| Integrations | |
| GitHub Auto-push branches and open pull requests when pipelines complete. | ✓ |
| Platform | |
| Cloud dashboard Kanban board with real-time pipeline status, prompt editor, diff views, and run history — all in one place. | ✓ |
| CLI Manage daemons, trigger runs, and inspect pipeline status from your terminal. | ✓ |
Frequently asked questions
Common questions about using AI agents for software development.
How do I run AI coding agents without giving them access to my entire machine? +
Trimo runs every AI agent inside its own Docker container with kernel-level isolation. The agent gets a separate filesystem, network, and process space. Your source code stays on your machine, and the cloud dashboard only sees metadata. There's no shared access between containers.
Can I run multiple AI coding tasks at the same time? +
Yes. Trimo lets you dispatch multiple agents in parallel — each runs in its own Docker container on its own branch. You can work on a new feature, a bug fix, and a refactor simultaneously, then review each result independently. The only limit is your hardware.
How do I stop an AI agent from breaking my codebase with bad git commands? +
Trimo wraps git with safety rails that block destructive operations like force-push, branch deletion, and rebase on protected branches. Every change is automatically committed and pushed. If a container crashes, the work is already in git — nothing is lost.
Is there a way to use Claude Code autonomously without babysitting a terminal? +
That's exactly what Trimo does. Write a prompt in the web dashboard, hit run, and the agent works autonomously in a Docker container. You can monitor progress, review diffs, and send follow-up prompts — all from the dashboard. No terminal window required.
How do I manage the output when an AI agent changes dozens of files? +
Trimo shows you a diff view for every run, so you see exactly what changed. If something isn't right, write a follow-up prompt and the agent runs again on the same branch with full context. Each iteration builds on the previous one — like a conversation with code review built in.
Do I need to pay extra for AI tokens on top of the subscription? +
Trimo never charges for, marks up, or intermediates LLM tokens. You use your own Claude subscription or Anthropic API key directly. Trimo handles orchestration, isolation, git automation, and monitoring — the AI provider relationship is entirely yours.
Can I use AI coding agents on private repositories without sending code to the cloud? +
Yes. Trimo's architecture is cloud-control, local-execution. The cloud dashboard manages state and monitoring, but all code execution happens on your machine. Your source code never leaves your infrastructure. The agent runs locally in Docker — only metadata like status and run history reaches the cloud.