Herder vs Panda Code: Which Coding Agent Tool Should You Use?
Herder's terminal-based agent management vs Panda Code's desktop app approach, compared on machines, status, persistence, and updates.
What’s the difference between Herder and Panda Code?
Herder is a terminal multiplexer built specifically for coding agents. It wraps something like tmux but tracks whether each agent is working, blocked on a question, or done, and shows that in a sidebar. Panda Code is a desktop app that talks to agents you already have installed (Claude Code, Codex, Kimi Code, Open Code, GLM) and presents each one as a chat thread with diffs and approval buttons instead of a raw terminal screen. The short version: Herder gives you a terminal pane for every agent, including ones that don’t officially integrate with anything yet. Panda Code gives you a GUI built around the agents it explicitly supports.
TL;DR
- Herder now manages multiple machines in one window, combining your local box and any saved SSH targets into a single sidebar instead of one SSH session per window.
- A new dash-machine flag lets you run Herder commands against a saved machine without opening a window, which also means agents can script other agents remotely.
- Persistence got a real rework, with pre-shutdown saves, atomic writes, up to 48 layout snapshots, and staggered agent restarts instead of launching everything at once.
- Agents can now self-report their status and resume command, so Herder doesn’t need a built-in integration for every new CLI tool to track it.
- Updates no longer kill running sessions by default, with Herder asking before replacing a compatible server and Panda Code holding off updates until no agent is mid-task.
- Panda Code wins on review and orchestration features like per-turn diffs, a changes panel, agent teams, and Telegram/Slack bots, while Herder wins on raw terminal flexibility and multi-machine scripting.
- Both tools are still maturing: Herder is pre-1.0 with some open bugs, and Panda Code’s desktop app isn’t code-signed yet and depends on each agent’s own update cycle.
How does Herder handle multiple machines?
Before the recent updates, Herder’s remote mode was one client tied to one SSH host per session. The new version changes that: a single Herder window can manage your local machine and every saved SSH machine at once, all listed together in the sidebar. Running herder machine add with an SSH target adds it to that list, and if Herder finds sessions already running on that host, it offers to attach to one instead of starting a duplicate. Machines no longer need manual labels either, since Herder just uses the SSH hostname.
The agent list merges everything into one view. If an agent on a remote server gets blocked waiting for approval, it shows up next to agents running locally, with the same notification behavior. Each machine also reconnects independently, so a dropped server connection doesn’t affect agents running on your laptop. Keyboard navigation moves across machines in sidebar order, with a highlight before you confirm so you don’t send a command to the wrong box by accident.
On top of that, a dash-machine flag lets you run any Herder command against a saved machine without a window open at all, for example checking the agent list on a remote server directly from your local terminal. This matters beyond convenience: it means an agent running on your laptop can start another agent on a remote machine, send it a prompt, and read back the result, effectively letting agents orchestrate agents across machines. Both machines need to be running an updated version of Herder for this to work, and Herder will not silently fall back to running locally if a remote command fails.
Connection handling also improved. herder machine status checks all saved machines without prompting, herder machine reconnect lets you finish password or MFA logins in the terminal, and failed machines are rechecked automatically every 30 seconds. Windows SSH hosts are now supported, and the SSH connections themselves use compression plus smarter diffing, so typing, switching panes, and scrolling only send what changed rather than repainting the whole screen. That matters if you’re watching build logs stream over a slow connection.
How does Panda Code’s machine handling compare?
Panda Code takes an opt-in multi-machine approach rather than treating SSH as the default mode. Agents can launch threads on other computers you own and wait for the results, and you can run panda code serve on a spare machine or server so agents keep working while your laptop sleeps. For single long-running tasks, Panda Code also offers a cloud sandbox option through its run-on menu, with changes synced back to a local work tree when done.
Both tools can offload work to remote machines, but the philosophies differ. Herder assumes you’re comfortable managing SSH boxes and want direct terminal access to everything. Panda Code is built for people who’d rather not think about servers and want a GUI-managed version of the same idea.
How do they track agent status differently?
● Reading src/server.ts
● Editing 3 files
+ import { limit } from 'rate'
- app.use(cors())
✓ Tests passed · ready for PR
Herder either reads the terminal screen to infer what’s happening or, with the newest update, receives direct status reports from agents that support it. Agents can now tell Herder they’re working, blocked, or idle, and even hand over the exact command needed to resume their session. That self-reporting approach means Herder doesn’t need a dedicated integration for every agent anymore, which the creator calls the update that matters most long-term, since it turns Herder into more of a runtime than a tool chasing new agent releases.
Panda Code instead talks to each supported agent through its own interface. Approvals show up as a thin bar above the prompt with approve/deny buttons, and questions appear as small cards with selectable options. Functionally, both sidebars tell you what’s running, what’s blocked, and what’s finished. The practical difference is interaction: Herder has you jump into a terminal pane and type a response, Panda Code has you click a button.
Which tool handles persistence and reboots better?
Herder’s persistence rework is one of the more substantial updates. It now saves session state before the OS starts closing apps during shutdown, and writes those saves to disk atomically so a crash or power loss can’t corrupt the file. It keeps up to 48 layout snapshots in a session snapshots folder for manual recovery. On Mac and Linux, closing the shell that launched Herder no longer kills the server, and if the system runs out of processes or threads, the server survives rather than taking every pane down with it. When a session restarts, agents now launch one at a time with a small default delay between each (configurable via a startup-per-agent-delay setting), which matters a lot if you’re running a large number of agents at once and don’t want them all hammering the CPU simultaneously.
Panda Code’s persistence model is conversation-centric: every thread is saved in a local database so you can reopen and continue chatting later. It also has a resume-at-reset feature that automatically continues a task once a usage limit resets, which Herder doesn’t have an equivalent for. The practical split: Herder’s restore is more complete for raw terminal state, Panda Code’s is more about preserving the conversation and work itself.
How do the two tools handle updates without breaking sessions?
Both have moved toward not disrupting running agents during updates, which was a real pain point before. Herder updates can now leave a compatible running server and its agents untouched. If the server is missing a needed feature, only that specific action gets disabled rather than forcing a full restart. If a replacement is actually required, Herder asks first and defaults to no, then tells you exactly which servers are outdated and the command to restart each one.
Panda Code only applies its own updates when no agent is actively working, and it can update each supported coding agent with a single click, which is a convenience Herder doesn’t replicate since it treats agents as arbitrary terminal processes rather than managed tools.
Which one should you actually use?
Built like a system. Not vibe-coded.
Remy manages the project — every layer architected, not stitched together at the last second.
If you live in the terminal, SSH into multiple machines regularly, or use agents that don’t have mainstream GUI support yet, Herder is the stronger fit, especially after this round of updates aimed at multi-machine reliability and reboot survival. If you’d rather review diffs, run coordinated agent teams, and click through approvals instead of typing in a terminal, Panda Code fits better. Panda Code also brings things Herder doesn’t attempt: per-turn diffs, a changes panel for committing from work trees, two-click merges, a built-in browser for picking page elements to send to an agent, a taskboard, multi-model agent teams with an architect splitting work across workers, and bot integrations for Telegram and Slack.
Nothing stops you from using both. Running long unattended jobs on a server through Herder while doing day-to-day review and team coordination in Panda Code on a laptop is a workable split, since the two tools don’t compete for the same workflow.
Frequently Asked Questions
Is Herder free and open source?
Herder is an open-source project with its repository approaching 49,000 stars on GitHub at the time of this comparison. Specific licensing details should be checked on the project’s own repository.
Does Panda Code support every coding agent?
No. Panda Code only runs agents it explicitly supports, including Claude Code, Codex, Kimi Code, Open Code, and GLM. A brand-new CLI agent is likely to work in Herder’s terminal panes before Panda Code adds support for it.
Can Herder agents trigger other agents on different machines?
Yes. With the dash-machine flag, an agent running locally can start another agent on a remote saved machine, send it a prompt, wait for a response, and read the output back, which enables basic agent-to-agent orchestration across machines.
Is Herder stable enough for daily use?
It’s still pre-1.0 and has some open issues, including a terminal rendering bug with certain prompt customizations and a temporary regression in how it tracks Codex status after a recent change. The creator still recommends trying it if you regularly run several agents at once.
Does Panda Code work without installing agents separately?
No. Panda Code manages agents you’ve already installed rather than bundling them, so you still need Claude Code, Codex, or whichever supported tool installed on your system first.
