Agentastic, AgentsRoom, CodeAgentSwarm, Paseo: Different Orchestrators, One Shared Record

A new shape of tool has appeared in the last year, and it does not have a settled name yet. Agentastic, AgentsRoom, CodeAgentSwarm and Paseo are all, underneath their differences, the same idea: one environment that runs several coding-agent CLIs at once — Claude Code here, Codex there, a third agent in a third worktree — and lets a person supervise the fleet. Call them multi-agent orchestrators.

They are good at the problem they solve. What none of them is, is a record of the work. That gap is this article's subject — because the more parallel agents you run, the faster the gap finds you.

The four, briefly

The differences are real — native versus cross-platform, commercial versus open source, worktree-per-agent versus window-per-project. The similarity matters more: every one of them is an answer to who runs, where, and in parallel.

The blind spot they share

Run four agents in parallel and you get four streams of work — and four scrollbacks. The code is safe: worktrees isolate it, git records it. But the coordination facts around the code live nowhere durable:

• Which agent is doing what, and what "done" means for each task
• The decision made in agent B's session that changes what agent A should do
• The thing the human approved in a chat prompt at 9:03, and the three things still waiting for approval
• Why a task was abandoned, in words the next session can use

Orchestrators manage processes: start, stop, switch, supervise. They are not built to be the place where the work's facts accumulate, and their own sessions are as ephemeral as any agent's. When the day ends, the fleet's shared understanding ends with it — the same drawer problem as single agents, multiplied by parallelism.

What a shared record underneath gives you

The fix is not another orchestrator feature. It is a layer underneath all of them: one base that holds the tasks, the decisions and the state of the work as records, that every agent — whichever orchestrator launched it — reads before acting and writes to when done. Concretely:

• Task state survives the fleet. An agent in Agentastic and an agent in Paseo working the same project see the same task list, the same decisions, the same open questions. Switching orchestrators stops meaning starting over.
• Decisions become inputs. The call made in one session is a record the next session reads, not a paragraph buried in a transcript it cannot find.
• Approvals get a proper home. The consequential outputs — the migration, the customer-facing change — can wait as change requests with diffs, while routine updates land directly. Supervision stops being a scrollback you babysit.
• The CLIs become interchangeable parts. Note CodeAgentSwarm's list above: Antigravity CLI sits next to Claude Code and Codex as one more engine under the same roof. That is the direction of the whole category — the engines swap; the record is what must not.

Every tool in the table connects to Busabase that way — through the agent skill or MCP, with the change-request workflow included — which is the point: the base does not care which orchestrator is fashionable this quarter.

Handoffs: the moment the blind spot bites

Searches like "paseo handoff" are really asking what happens when work moves — from one agent to another, from desktop to mobile, from today's session to tomorrow's. A handoff carried by chat export carries the words but not the state. A handoff that works carries four things, as records:

1. Task state — what is done, what is in flight, what is blocked and on whom.
2. Decisions made — and the reasoning, in the form the receiver will actually read.
3. Open questions — the things explicitly not decided, so the receiver does not silently decide them by momentum.
4. Artifacts — the outputs themselves, linked to the task they belong to, not attached to a chat thread.

If those four live in a shared base, a handoff is just the next agent reading the base — the "handoff" stops being an event that can fail. If they live in the orchestrator's session, every handoff is a small migration, and small migrations are where context goes to die.

Adjacent shapes, same conclusion

Two more names from the same searches deserve a line, because they are not orchestrators but land on the same need. Grok Bot — xAI's always-on AI teammates, each with its own persistent cloud VM — raises the stakes in the opposite direction: an agent that never sleeps produces facts around the clock, and "who reviewed this?" stops being rhetorical. Hermes Agent, Nous Research's autonomous terminal agent, ships with its own persistent memory and skills — which answers the question for one agent, and re-opens it the day a second tool needs what Hermes knows. In both cases the searches ("grok bot mcp", "hermes agent mcp") end in the same place: connect the agent to the shared record, so what it knows and does is not trapped in its own runtime.

Orchestrators will keep multiplying — that is a healthy category doing its job. Pick whichever runs your fleet best. Just do not ask it to also be the memory of the work. That is a different layer, it belongs to you, and it should be the one thing that does not change when everything above it does.

FAQ

Should I pick my orchestrator based on whether it has a built-in shared memory? Built-in memory inside one orchestrator helps until work crosses tools — a second orchestrator, an always-on bot, a teammate's different setup. Judge an orchestrator on running agents well; judge the record layer separately, and prefer one every tool can reach.

My agents all run inside one tool today. Do I still need this? You need it the day the second agent starts writing things the first one depends on — which, inside a multi-agent IDE, is usually day one. The parallel worktree is exactly the setup where a decision in one session silently invalidates another, unless both read the same record.