Maxxwell by Rindler
Writing

Agent Herd View: One Window for Agents

2026-10-25

An agent herd view is a single interface that shows all your AI coding agent sessions and their live states at once, so you can see what each agent is doing.

An agent herd view is a single interface that shows all your AI coding agent sessions and their live states at once, so you can see what each agent is doing, which ones need your input, and which ones are stalled or done without hopping across terminals or tabs.

How an Agent Herd View Works

In Maxxwell, the agent herd view is literally a window of lanes, each lane mapped to a real agent session you already run: Claude Code, Codex, Cursor-agent, or whatever else you use. Every lane is a live terminal-backed worker you can attach to, not a simulation or hidden sandbox.

Each lane carries a readable state label drawn from what the session is actually doing. The common states are:

Sitting above the herd is an orchestrator seat. This is itself a real coding-agent session, started from a written brief: “coordinate a multi-repo refactor for feature X”, “build and wire up three microservices”, etc. You talk to the orchestrator in language instead of juggling a dozen per-agent prompts. It responds with what it asked each worker to do, what landed, and which decisions it deferred to you.

The critical design detail: fleet controls draft, they do not act. If you ask the orchestrator to spin up three more lanes or retask a worker, Maxxwell writes a fully-formed, unsent sentence into the composer. Nothing hits the agents until you press Enter. You remain the one who actually changes the fleet.

The whole thing runs locally. Maxxwell surfaces the agents you already have installed, uses your existing Claude or ChatGPT/Codex access, and never ships your code or prompts to a Maxxwell server. Quitting the app detaches from the sessions; it doesn’t kill them, so long-running work keeps going in the background.

Why an Agent Herd View Matters for Developers

By 2026, AI coding agents are no longer novel. JetBrains reports 90% of professional developers use AI coding agents at work at least weekly and 68% daily, with Claude Code adoption jumping from 18% to 39% globally in under a year. The industry moved from "should I use an agent" to "how do I run several of them without becoming the bottleneck".

The bottleneck now is attention, not tokens. Past two or three sessions, you spend more time babysitting than building: answering minor questions, checking whether a lane is still alive, and noticing when one has confidently wandered off spec. Stack Overflow’s 2025 survey shows positive sentiment for AI tools sliding from the 70% range to 60%, even as adoption climbs, which matches the feeling of “this helps, but it’s noisy and easy to mis-aim.”

An agent herd view attacks that directly. Instead of eight terminals and four browser tabs, you get one window that tells you:

For Maxxwell’s audience - developers who already live in tmux and custom scripts - the key win is visibility without giving up control. You still own the workers: they’re your agents, your API keys, your repos. Maxxwell doesn’t auto-aim them, doesn’t silently restart or compact context; it gives you a herd view plus a conductor seat so you can decide what happens next.

How an Agent Herd View Differs from Kanban Boards and CI Dashboards

The term gets confused with a few adjacent ideas: kanban boards, multi-repo CI dashboards, and generic project management views. The differences are practical.

A kanban board (Jira, Linear, GitHub Projects) shows work items, not live processes. Cards move from “Backlog” to “In Progress” to “Done”. That’s useful for product and team planning, but none of it tells you whether your Claude Code session on branch feature/refactor-auth is currently blocked on a migration error or happily rewriting tests.

A CI dashboard (GitHub checks, Buildkite, CircleCI) shows pipeline runs and their statuses. You see “build #1423 - failed” or “test suite - green”. Again, critical, but not the same as watching a set of agents exploring designs, drafting code, and asking you questions before those branches even hit CI.

An agent herd view is about live agent sessions, not tickets or pipelines. Each lane is a process you can attach to and steer. States like working, waiting on you, and blocked are about conversational and coding progress, not something that already ran to completion.

Compared to other multi-agent orchestration tools - The Cog, Helmor, Alera, Acepe, Conductor - Maxxwell stays closer to the terminal. The herd view is a thin layer over your real sessions, not a replacement IDE. It doesn’t hide workers behind a proprietary workflow or cloud workspace. If you prefer, you can drop back into your tmux window and the same Claude Code process is still there.

In short: kanban and CI dashboards answer “what work exists and what passed?”, an agent herd view answers “what are my agents doing right now and where does my attention unblock them?”.

Example: Using an Agent Herd View for a Multi-Repo Refactor

Consider a multi-repo refactor: you’re migrating auth across three services (api-gateway, user-service, billing-service) plus a shared library. Without a herd view, the typical setup is four terminals, each with its own agent session, plus a notepad or issue tracker where you’re tracking decisions. Within an hour, you’ve forgotten which agent is waiting on a schema choice and which is silently rewriting code based on yesterday’s model of the library.

With Maxxwell’s agent herd view, you start by briefing the orchestrator seat:

"We’re migrating auth to JWT-based sessions across four repos. Spin up one worker per repo. For each: scan usage of the old token system, propose a migration plan, and implement it behind a feature flag. Stop and ask me before touching public APIs."

The orchestrator drafts the commands to start four worker lanes, each attached to your preferred tool in the corresponding repo; you press Enter to send them. You see them come up in the herd view as working while they scan and plan.

After a few minutes:

You don’t hunt for logs. You look at the herd view and decide:

  1. Attach to the billing-service lane, read the failure, and tell the agent to mock the dependency until CI catches up.
  2. Answer the api-gateway question in place and hit Enter so that lane resumes.
  3. Nudge the idle shared-lib lane by prompting: "You’ve scanned usage; now draft a concrete migration plan with stepwise patches."

At no point did Maxxwell silently restart work or auto-correct drift. It surfaced states and gave you one orchestrator seat to express decisions once, instead of repeating yourself into four terminals. When you close the app for lunch, the underlying Claude and Codex sessions keep running; when you reopen, the herd view reconnects and you see which lanes are done and ready for review.

On a team, this scales. Multiple developers can share the same herd view for a big refactor, each attaching to specific lanes while the orchestrator writes return reports that separate what actually landed (merged branches, passing test runs) from what is still waiting on a human. You move from “I have eight sessions open and I am the slowest part of this” to “I can see the herd, I choose where to intervene, and the rest keeps going.”