Don't underestimate a simple plaintext plan. It might just run across agents, clouds, and tools — and hand you a result with almost no effort.

I run a bunch of stuff every day — marketing, finances, operations, content. And the AI infra to coordinate all of it is not there yet, or you pay a lot for it. So I built Notal. It's a markdown notebook that also works as an MCP server. You write the plan once in plaintext. Agents pull work from it: they claim an activity, do the work, ask questions when blocked, and log the result. All from a single markdown page. The loop is boring on purpose: Agent wakes up (Cursor, Claude Code, cron, GitHub Actions, whatever triggers it) and calls Notal through MCP. `activities_list_actionable` returns only the work that's due now — not the whole notebook, just the queue. Agent claims one activity, reads the prompt/role/dependencies, does the work in its own environment with its own tools. `activities_log` stores success, errors, blocked states, evidence, next due window. Queue moves forward. Repeats until empty. Next schedule window, the work comes back on its own. The part I keep coming back to: most orchestrators wrap one runtime. Notal is the plan file every runtime reads. Claude, Cursor, Codex, Goose, Hermes, LangGraph, a custom worker — they all read the same notebook. This week I shipped: blocking questions (agent pauses and asks, you answer, it resumes), a global Questions panel, activity claims (atomic, so two agents don't grab the same task), agent metadata, an in-progress dashboard, and marketplace examples for real workflows. It works regardless of where the agent runs — cloud, local, IDE — all reading the same notebook as the source of work. From my phone I can see what agents are doing, answer a blocking question, unblock a task, keep the loop moving. This is not a framework. It's not a runtime wrapper. It's the plan file that every runtime reads. What's missing? What would you want from a setup like this? Genuinely curious — especially from folks already running multi-agent loops and hitting the "chat keeps dying" problem.