How to Run an AI Agent 24/7 (Without Burning Money)

The dream: an AI agent that works while you sleep. Monitors things. Creates content. Handles routine tasks. Always on.

The reality most people hit: a $500/month API bill and an agent that hallucinates itself into a loop at 3am.

Here's how to do it properly.

The Core Pattern: Cron-Based Autonomy

The biggest misconception about 24/7 agents is that they need to be "always running." They don't. They need to be always available — there's a difference.

Instead of a long-running process burning tokens by thinking about nothing, use a cron-based pattern:

# Every hour, wake the agent with a task prompt
Schedule: 0 * * * *
Payload: "Pick your highest priority task and execute it.
          Report what you did when done."

The agent wakes up, reads its context (memory files, task list, status), picks work, does it, reports, and goes back to sleep. Cost per wake cycle: ~$0.10-0.50 depending on complexity.

The Autonomy Loop

Here's the exact pattern we use for our agents:

STEP 1: READ CONTEXT
- Today's memory file (what happened so far)
- Task list (prioritized work items)
- Status file (what did I do last hour?)

STEP 2: PICK TASK (by priority)
1. Urgent fixes / bugs
2. Revenue-generating work
3. Content creation
4. Infrastructure improvements
5. Nice-to-haves

STEP 3: EXECUTE (minimum 20 min productive work)
- Build, fix, deploy, or create something concrete
- Commit changes to git

STEP 4: REPORT
- Send brief status to team channel
- Update status file for next cycle

This gives you a self-directing agent that genuinely produces work every hour. Not just chat — actual deliverables.

Cost Control: The Math

Let's be honest about costs. Here's what 24/7 operation actually looks like:

Pattern	Cycles/Day	Cost/Cycle	Monthly
Hourly autonomy loop	24	$0.30	~$220
Every-2-hour loop	12	$0.30	~$110
Business hours only (8h)	8	$0.30	~$75
Monitoring (lightweight)	24	$0.02	~$18

The key insight: not every cycle needs to be expensive. Monitoring and health checks can use a cheaper/faster model. Save the heavy model for actual creative work.

Cost Optimization Tricks

1. Model routing: Use Sonnet for daily tasks, Opus only for complex reasoning
2. Heartbeat checks: Lightweight pings that skip work if nothing needs attention (costs ~$0.01)
3. Smart scheduling: More frequent during business hours, less at night
4. Context pruning: Don't load your entire history every cycle — just today + relevant files
5. Early exit: If the agent determines there's nothing to do, it should say so immediately

Monitoring: Know When Things Break

A 24/7 agent without monitoring is a liability. Here's what to track:

• Status reports: Each cycle should produce a brief report sent to your chat
• Error counts: Track failures per hour. Three+ in a row = alert
• Token usage: Set daily budget caps. Agent should know its spending
• Task completion rate: Is it actually finishing things or spinning?
• Git commits: Concrete proof of work. No commits = no work

The State File Pattern

Every agent should maintain a simple JSON status file:

{
  "agent": "bolt",
  "timestamp": "2025-02-14T20:00:00+01:00",
  "status": "active",
  "current_task": "Writing blog content",
  "last_hour": {
    "tasks_completed": 2,
    "summary": "Built 3 blog posts, deployed to Vercel"
  },
  "next_hour": {
    "planned": ["SEO optimization", "Newsletter draft"],
    "blockers": ["Twitter API rate limited"]
  },
  "health": {
    "loop_count": 24,
    "errors_last_hour": 0,
    "uptime_hours": 24
  }
}

This gives you instant visibility into what each agent is doing, and the agent itself uses it to maintain continuity across cycles.

Common Pitfalls

1. The Infinite Loop

Agent gets stuck retrying something that will never work. Fix: set a max retry count and move on after 5 attempts.

2. The Token Burner

Agent loads massive context every cycle "just in case." Fix: lazy loading — read summaries first, detail only when needed.

3. The Busywork Trap

Agent refactors its own config files 47 times because it ran out of real tasks. Fix: explicit priority lists. When the list is empty, the agent should report "nothing to do" and stop.

4. The Silent Failure

Agent encounters an error but doesn't tell anyone. Fix: every cycle MUST produce a report. No report = something is wrong.

A good 24/7 agent is like a good employee: it does its work, keeps you informed, and asks for help when it's genuinely stuck. It doesn't need hand-holding, but it also doesn't go rogue.

Getting Started: Weekend Project

1. Friday evening: Set up the runtime (OpenClaw, or your preferred platform). Create SOUL.md, AGENTS.md, USER.md.
2. Saturday morning: Define 10 tasks your agent should handle. Create a task list file. Set up the first cron job (every 2 hours).
3. Saturday afternoon: Monitor the first few cycles. Tweak the autonomy prompt. Fix obvious issues.
4. Sunday: Add monitoring. Set up the war room channel. Let it run overnight.
5. Monday: Check the war room. Your agent worked all weekend. You didn't.