Your agent needs a task queue — here's how to build one that won't break

Your agent is getting overwhelmed. You ask it to write code, then interrupt with a Slack message, then pile on three more tasks while it's mid-function. It starts dropping context, mixing up requirements, and eventually just... stops working coherently.

The problem isn't your agent's intelligence. It's that you're treating it like a human who can juggle multiple threads when it's actually a single-threaded process that needs clear task boundaries.

Here's the pattern that fixes this: give your agent an explicit task queue.

The simplest version looks like this:

## Current Task Queue

### ACTIVE
- [ ] Refactor user authentication module
  - Context: /src/auth/
  - Requirements: Add 2FA support
  - Started: 2024-01-15 14:30

### QUEUED
1. [ ] Review PR #247 (slack message from Sarah)
2. [ ] Update API documentation for v2.1
3. [ ] Debug production login issue (P1)

### COMPLETED TODAY
- [x] Fixed database connection pooling
- [x] Deployed hotfix for payment processing

Your agent maintains this in a dedicated file — task_queue.md or in its memory system. When you interrupt with a new request, it doesn't context-switch immediately. Instead:

• Captures the new task: "Adding 'Debug production login issue' to queue as P1"
• Assesses priority: "This is urgent — should I finish the current auth work or switch now?"
• Makes an explicit transition: "Pausing auth refactor at line 47, switching to P1 issue"

The key insight: your agent needs to acknowledge the interruption without immediately acting on it. This prevents the context-bleeding that kills productivity.

For coding agents, add these queue states:

### BLOCKED
- [ ] Database migration script
  - Waiting for: DevOps team to provision staging DB
  - Context saved: /docs/migration_plan.md

### REVIEW
- [ ] Payment integration refactor
  - Status: Code complete, needs human review
  - PR: #251

This prevents your agent from spinning on blocked tasks or forgetting about work that's waiting for human input.

The queue discipline that actually works:

• One active task maximum — everything else goes in QUEUED
• Context checkpoints — before switching tasks, save exactly where you left off
• Priority interrupts allowed — but they require explicit transition
• End-of-day cleanup — review queue, update priorities, archive completed work

I've been running this pattern for six months across three different coding agents. The difference is dramatic — instead of half-finished work scattered across 12 files, I get clean task completion and proper handoffs.

The queue becomes your agent's external brain for work management. It can pause mid-function, handle your urgent Slack request, then resume exactly where it left off without losing context or mixing up requirements.

Your agent isn't just a better programmer with a task queue — it becomes a better worker. And that's the difference between a useful tool and something that actually runs parts of your business.