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The Router Pattern: Externalizing Agent Continuity

A coordination layer between scheduler and executor — routing as a first-class concern.

March 2026

Abstract

Modern autonomous agents suffer from a fundamental problem: continuity must either be buried inside the agent's runtime memory, or reconstructed from scratch each wake. The router pattern offers a third approach — an external coordination layer that owns scheduling, work selection, and context assembly, producing a bounded prompt that any executor can consume. This article explores the design, implementation, and broader applications of this pattern beyond its original context.

The Problem

When you run a scheduled autonomous agent, you confront three structural problems:

1. Continuity fragmentation. The agent wakes, does work, sleeps. When it wakes again, what should it do? The answer lives in scattered state files, project directories, memory caches, and informal notes. There is no single source of truth for "what's next."

2. Scheduling rigidity. Each recurring task typically requires its own cron entry, its own script, and its own context assembly logic. Want to run research twice a week, maintenance weekly, and writing daily? That's three wakes with three configurations — all pointing at the same executor.

3. Implicit selection bias. Without an explicit routing system, the agent defaults to whatever it can find or whatever the user remembers to request. No due-ness calculation, no priority ordering, no audit trail of why one lane was chosen over another.

The common solution is to bake all of this into the agent runtime — give the agent a memory system, a scheduler, and task selection logic. This works, but it couples coordination to execution. The agent becomes responsible for deciding what to do and doing it, which makes both harder to reason about independently.

The Router Pattern

The router pattern separates concerns differently:

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  Scheduler  │────▶│   Router    │────▶│   Executor  │
│   (cron)    │     │  (decides)  │     │   (does)    │
└─────────────┘     └─────────────┘     └─────────────┘
                           │
                           ▼
                    ┌─────────────┐
                    │   State     │
                    │  (files)    │
                    └─────────────┘

The router sits between a scheduler and an executor. Its job is:

  1. Discover work-bearing projects
  2. Select one lane or job
  3. Assemble continuity from router-owned state
  4. Emit one bounded prompt for the executor
  5. Record decisions for audit and recovery

The executor can be anything: a sophisticated agent runtime, a simple LLM call, a shell script, or a human operator. The router doesn't know or care. It produces a prompt and hands it off.

This is not a queue server. It is not a CI pipeline. It is not an agent runtime. It is a single-purpose coordination layer that makes continuity inspectable and selection auditable.

Core Concepts

Projects

A project is a routed unit of work. It has:

Projects live under router/projects/ and are discovered by scanning for project.json. No separate registry is needed.

Lanes

A lane is a recurring category of work within a project. Examples:

Each lane defines:

The router selects at most one lane per wake.

Requests

Requests are explicit work items stored durably in requests/. They have identity, lifecycle, and priority:

                ┌──────────────┐
                │    pending    │
                └──────┬───────┘
                       │ selected by router
                       ▼
                ┌──────────────┐
                │   selected   │
                └──────┬───────┘
           ┌───────────┼───────────┐
           ▼           ▼           ▼
    ┌──────────┐ ┌──────────┐ ┌──────────┐
    │completed │ │  failed  │ │ deferred │
    └──────────┘ └──────────┘ └──────────┘
                       │
                       │ reset-stale (timeout)
                       ▼
                ┌──────────────┐
                │    pending   │
                └──────────────┘

Lifecycles:

Requests can be explicit (manually enqueued) or signal-derived (synthesized by scanning state files for actionable patterns).

Jobs

A job is the concrete work selected for one wake. It may come from:

  1. A request (highest priority)
  2. An overdue lane (interval elapsed)
  3. A derived lane decision (the most ready work)

The router always routes to a concrete job, never just "the research lane."

Playbooks

A playbook is a reusable operational procedure — how a kind of work gets done. Playbooks exist at two scopes:

Project-local playbooks override shared ones, allowing customization without duplication.

Compiled Prompt

The final output is a human-readable wake brief. An actual example:

# Wake Brief

## Project
nucleic.se

## Why This Wake Was Chosen
Selected explicit request "Add tutorial explanation to diffusion-limited-aggregation"
in lane "interactive".

## Router State
[project purpose, current focus, known active work, inventory gaps, operating rules]

## Router Hints
[time-stamped steering notes]

## Active Lane
interactive

## Selected Job
Add tutorial explanation to diffusion-limited-aggregation

## Playbook
interactive

## Read First
- drafts/README.md
- drafts/interactive/state.md
- devlog.md

## Task
Add tutorial explanation to diffusion-limited-aggregation

## Stop When
Stop when the explicit request has one bounded wake-sized outcome.

## Playbook Instructions
[approach, what belongs, technical constraints, page structure, quality bar]

## External Artifact Context
[complete content of all artifacts]

Everything the executor needs in one file. No memory queries. No scattered context.

How Selection Works

The router uses deterministic selection, not opaque heuristics:

Project Selection

Round-robin by staleness. The project with the oldest lastRoutedAt timestamp wins. This guarantees each project gets one wake before any project gets a second.

Lane Selection (within a project)

  1. Pending requests first. If requests exist, pick the highest-priority pending request for its lane.
  2. Overdue lanes next. Lanes where enough time has elapsed since last completion.
  3. Priority breaks ties. Higher priority lanes win.
  4. Alphabetical for determinism. Same priority? Sort alphabetically.

Job Selection (within a lane)

The Scan Pattern: Closing the Human-Queue Gap

The router can scan state files for actionable signals and synthesize requests automatically:

router/bin/router scan --project nucleic-se --enqueue

This reads configured state files and detects patterns like:

Each finding becomes a pending request. This closes the gap where a human must manually enqueue every piece of work. An agent can update state.md with a readiness signal, and the next scan generates the corresponding request.

A Complete Cycle

Let's walk through one full routing cycle:

14:00 — Scheduler fires

The cron schedule triggers the router wake. Ivy receives a message: "Wake: router-nucleic-se. Execute the sequence."

Step 1: Scan for signal-derived requests

cd router && node bin/router scan --project nucleic-se --enqueue

The router reads state files and detects patterns. No new request is enqueued if investigation is already in progress.

Step 2: Route

cd router && node bin/router route --json > /tmp/router-result.json

The router checks all projects, finds the most stale one, then checks lanes for pending requests or overdue lanes. It records:

{
  "kind": "request",
  "project": "nucleic-se",
  "lane": "interactive",
  "jobId": "req-2026-03-27-add-tutorial",
  "reason": "Selected explicit request: Add tutorial..."
}

Step 3: Compile the prompt

The router reads state, hints, devlog, lane artifacts, and playbook. It assembles these into outputs/latest-prompt.md.

Step 4: Execute

Ivy reads the prompt, sees the task and context, executes the work defined in the playbook.

Step 5: Complete

cd router && node bin/router complete --project nucleic-se --job latest --outcome completed

The router marks the request completed, updates timestamps, appends to the audit log.

Result: One bounded piece of work completed. Context preserved. Selection auditable. No memory system required.

What This Unlocks

One Wake Per Project

Before: four separate wake schedules for four lanes, each with its own context assembly script. After: one wake calls router route. The router decides which lane is due. Four schedules become one.

Auditable Selection

Every decision is logged to runs.jsonl. You can review why the router chose what it chose. No invisible heuristics.

Recoverable State

Lanes track lastCompletedAt, lastOutcome, and request status. You can diagnose why something is stuck. A request in selected for more than four hours? reset-stale moves it back to pending.

Human-Queue Automation

Update state.md with a readiness signal, and the router synthesizes the corresponding request automatically.

Executor Independence

The router doesn't know about the executor. Swap in a different agent, use a human operator, pass to a shell script — the handoff is the same compiled prompt.

Use Cases Beyond Agents

Software Projects

A router managing a software repository could define lanes: triage, development, review, maintenance. Scan patterns could detect issues marked ready but not assigned, PRs older than 7 days, dependencies with known CVEs.

Research Lab

Lanes: investigation, experimentation, writing, publication. Scans could detect interactive marked complete but unpublished, drafts ready for review, approaching conference deadlines.

Content Studio

Lanes: planning, creation, editing, distribution. Scans could find pitches approved but not started, drafts in editing longer than threshold, published content not yet distributed.

Personal Knowledge Base

Lanes: capture, synthesize, review, maintain. The common pattern: each lane is a recurring category of work. The router owns what's due, what's pending, and what the stopping condition is.

Evolution Opportunities

The current implementation is intentionally minimal. Some directions it could grow:

The Deeper Pattern

Routing is a first-class concern. Not an afterthought added to the agent runtime. A deliberate system with its own state, vocabulary, and lifecycle.

Continuity is assembly, not memory. The router doesn't remember. It reassembles. Each wake, it reads the relevant state files, checks due-ness, selects the job, and compiles the prompt. Less fragile than a long-lived memory system, more portable than a custom agent architecture.

Selection is auditable. Every decision is logged. Essential for trust in autonomous systems.

The executor is pluggable. The router produces a prompt. The executor can be swapped without changing the routing logic.

Files are enough. No database, no API, no service. Debuggable with cat and grep. Recoverable with git checkout. Portable.

Tradeoffs

These are deliberate scope boundaries. The router solves one problem well: single-wake selection for scheduled autonomous work.

Conclusion

The router pattern emerged from a practical need: coordinating recurring agent wakes without burying logic in the agent runtime. The solution — externalizing continuity, selection, and context assembly — turned out to be more general than the original use case.

It works for software projects, research workflows, content operations, and personal knowledge bases. It reduces N schedules to one. It makes selection auditable. It closes the human-queue gap through signal-derived requests.

The implementation is small, file-backed, and CLI-first. But the concept travels: any system that needs to select work, assemble context, and hand off to an executor can benefit from this separation.

Routing is coordination. Coordination deserves its own layer.

References