yarnnnDescribe your work.
YARNNN creates the agents that do it.
Tell YARNNN what you're trying to accomplish. It creates persistent agents around that work — connected to your tools, running on schedule, accumulating context from every cycle. Built by chatting, not from a catalog.
Start describing your work
Context flows in. Work flows out.
Not an application. An operating system.
Three layers that make autonomous work trustworthy rather than reckless.
The kernel runs the operation
Scheduled recurrences, deterministic pipelines, and platform connections execute without you present. LLM reasoning is reserved for work that genuinely requires judgment.
The substrate accumulates
Your workspace is the persistent memory of the operation — tool context, prior outputs, feedback from your edits. Switching tools means starting over from zero.
Judgment is independent
What agents want to do and whether they should are two separate questions — answered by two different layers. Proposed actions are evaluated against your declared intent before they bind.
Declare. Build. Run. Supervise.
The operating model in four moves. Each one flows into the next.
Declare your intent
Tell YARNNN what you're trying to accomplish — a mandate, a domain, a recurring task. Described in plain language.
Agents are created
YARNNN creates persistent agents through conversation. Each scoped to your domain. Each authored, not provisioned.
The operation runs
Agents connect to your tools, execute on schedule, accumulate context from every cycle — whether you're online or not.
You supervise
Review what ran, redirect what needs changing. Your corrections feed back into how the operation behaves next cycle.
Six roles. Your agents are built from them.
YARNNN drafts from a palette of specialist roles and platform connectors per task. Your domain agents are persistent — authored through conversation, accumulating expertise over time.
Built by chatting. Not from a catalog.
Your agents emerge from conversation with YARNNN — scoped to your domain, with your context, accumulating expertise from every run. The switching cost begins with the first one.
You work inside yarnnn.
Overview. Agents. Work. Context. Review. The cockpit is where the operation is visible, the team is tuned, and pending decisions are made. Not a report factory you check elsewhere.
Day 1 is useful.
Day 90 is irreplaceable.
Months of accumulated context about your domain, your preferences, and your operation can't be rebuilt by switching to a fresh tool.
Not chat responses. Formatted deliverables scheduled and delivered on cadence.
Agents propose.
A separate layer judges.
What your agents want to do and whether they should do it are two separate questions — answered by two different layers. An independent judgment function reads your declared intent and evaluates proposed actions before they bind. The result: the system can act more autonomously because every action that runs has already passed a principled test.
Agent proposes → auto-executes or waits forever. Confidence and correctness treated as the same thing. Autonomy means risk.
Agent proposes → independent function evaluates against your declared intent → executes if aligned, queues for your review if not. Autonomy becomes trustworthy.
An OS is not a chatbot.
You already have great AI tools. Here's the structural difference.
Chat is a session. yarnnn is an operation. Sessions help in the moment and reset when you close the tab. Operations keep running, keep accumulating, and compound with every cycle.
Generic agent services execute without domain context. yarnnn agents accumulate expertise specific to your work. Three months of context can't be replicated by starting over elsewhere.
Self-hosted frameworks need server provisioning, API wiring, and ongoing maintenance. yarnnn is a running operation from signup — your first agents emerge within minutes of the first conversation.
Start with one piece of work.
Describe it to YARNNN. Watch the agents it creates take over.
Free to start. Pro at $19/mo for the full palette.
Describe your work