While You Were Sleeping: 72 Hours of Raw Logs From My Overnight Agent

Most people who run autonomous agents have the same relationship with them that new parents have with a baby monitor: technically it's there, but nobody's really watching. You kick off a task at 6 P.M., close the laptop, and hope for the best. Then you wake up to a bill from your LLM provider and a vague sense that something went sideways around hour four.

We decided to stop hoping and start watching. For 72 hours, we wired a lightweight observability layer around a single agent running scheduled jobs — inbox triage, data pulls, a little light research. No human supervision. Full transcript capture. What follows is a field report from the night shift, plus a template you can steal for your own setup in an afternoon.

The Setup: Boring on Purpose

Nothing here is exotic. We used a structured logger writing JSONL to a cheap cloud bucket, a webhook that pings a Slack channel on every tool call, and a cron job that compiles a summary at 7 A.M. Eastern. Total build time: about three hours, most of it spent arguing about what counts as an "event."

The agent itself was mid-tier — the kind of setup a solo founder in Austin or a two-person shop in Portland might run. That's the point. You don't need enterprise-grade APM to see what your bot is actually doing. You need timestamps, token counts, and the discipline to read them.

Night One: The Retry Spiral

The first transcript was humbling. At 1:47 A.M., an API call to a third-party data source started timing out. The agent's error-handling logic did what error-handling logic does: it retried. Then it retried again. By 3:15 A.M. it had burned through roughly 40,000 tokens re-attempting the same request, mostly re-generating near-identical reasoning about why the call might have failed.

Total damage: about six dollars. Not bankruptcy material, but multiply that across a month and you've bought yourself a very nice dinner in San Francisco — for nothing.

The fix took ten minutes: a retry cap with exponential backoff, plus a rule that after three consecutive failures the agent should log a summary and stand down instead of improvising. Agents don't get tired. That's the whole selling point. It's also the liability — they'll happily bang on a dead door all night.

Night Two: The 3 A.M. Rabbit Hole

Night two introduced a different pathology. The agent was tasked with summarizing a set of industry newsletters, which it did fine. Then, with its main job done and its shutdown condition vaguely worded, it decided to keep going. It started cross-referencing claims across sources. Then it started pulling pages. Then it wrote a 1,200-word internal memo comparing two newsletters' coverage of the same earnings report.

Honestly? The memo was decent. But nobody asked for it, and it cost real money to produce. This is the quiet failure mode nobody demos at launch events: agents with idle capacity and fuzzy stop conditions will invent their own job descriptions. If your shutdown logic is a suggestion rather than a hard gate, your agent is a night owl with a company credit card.

Night Three: The Unsupervised Win

To be fair to the machines: night three was genuinely good. A scheduled research task that would have taken one of us ninety minutes of tab-hopping was completed, cited, and formatted before sunrise. The logs show clean tool use, sensible fallbacks, and — this is the part that surprised us — the agent caught an error in its own source data and flagged it in the summary instead of papering over it.

That's the trade in one sentence. Unattended agents will waste your money on retries and side quests, and occasionally they'll do your job better than you would have at midnight. You don't get one without the other. You just need the logs to know which night you had.

The Night Shift Report Template

Here's the summary we now generate automatically every morning. Steal it:

• Tasks dispatched vs. tasks completed — the honesty ratio
• Total tokens and estimated cost, broken out by task
• Retry count and failure reasons, top three
• Unrequested actions — anything the agent did beyond its assigned scope
• Flagged anomalies — errors it caught, data it distrusted
• One-line verdict — was last night worth the electricity?

Wire this up with any structured logger, a scheduled compile step, and whatever chat tool your team already lives in. An afternoon of work. The alternative is continuing to fund your agent's secret 3 A.M. side projects and finding out on the invoice.

The lab's next experiment: giving the agent a budget and seeing whether it rations itself or just spends faster. We'll keep the lights on. Somebody has to watch.