Ad budgets rarely blow up. They leak. By day three of the month one campaign is already spending faster than its plan allows. Cost per acquisition edges up a little each day for a week, and the trend only shows when somebody finally pulls the chart. An old keyword that stopped converting keeps eating money that could go to the ones still pulling their weight. There's no single alarm here, just a slow drip spread over two ad platforms, and nobody has the hours to read every line of both each morning.

So we gave the job to an agent on Machine. Each day it pulls spend and results from Google Ads and Meta Ads and posts a ranked list of findings, with suggested fixes, to Slack. It doesn't change a single budget, campaign or ad. Suggesting is all it does.

The problem

Any one of these issues is simple to spot when you're actually looking: a campaign off its budget pace, CPA or ROAS sliding, an ad or keyword that's lost its touch. The catch is that they're scattered across two platforms with two different dashboards, and reviewing every live campaign in both, every single day, falls apart the moment real work shows up. When the weekly review finally notices a campaign that has burned through its whole month's budget by day ten, or a keyword now costing twice as much per conversion, that money is gone.

The standard remedies fall short. Each platform's own alerts use their own thresholds and can only see their own account. A spreadsheet review once a week is careful, but seven days gives a pacing slip or a CPA jump plenty of room to grow. And bidding or budget tools that make changes by themselves take away the very thing a marketing team wants to hold on to: the call.

What we built

Each day a scheduled trigger on Machine starts a fresh session: a new cloud computer (a sandbox) used only for that run. The agent pulls spend and results from Google Ads and Meta Ads. It compares each campaign's pace with its monthly target, measures how far CPA and ROAS have moved from recent performance, and picks out weak ads and keywords plus any odd jumps in spend or click-through. Then it writes up suggestions in priority order, such as pausing a particular ad, moving budget to something that's working, or adding a negative keyword, and posts that ranked list to Slack. Neither ad platform gets a single write.

How it works

The pattern

A daily cron opens a fresh session with read-only connectors into Google Ads and Meta Ads, and the optimization rules sit in a skill. The agent studies spend and results on both platforms and its only output is the Slack post. Pauses, budget moves and keyword changes are always suggestions, never actions.

Guardrails

Because the agent sees live spend on two ad platforms, its access is narrow and flows one way:

• Isolation. Each run gets its own sandbox. The session can reach only Google Ads and Meta Ads, and the Slack post is the one thing that leaves it.
• Scoped secrets. The Google Ads and Meta Ads credentials are stored encrypted in the Secrets Manager, delivered into the sandbox when the run starts, and only handed to the agents you grant them to.
• Recommend-only. No write access exists on either ad platform. The agent can't touch a budget, pause a campaign or edit an ad. Reporting and suggesting are its whole job.
• Everything is code. The optimization rules, the thresholds and the permissions for each platform are files in your repo. They're versioned, and you change them through a reviewed change request, not a dashboard toggle.

The outcome

Pacing, the CPA and ROAS trend and the hunt for weak performers used to mean opening two dashboards. Now they show up as one ranked Slack message each morning, and every finding brings its figures and a clear suggestion. The agent reads and advises. Your marketing team still decides what gets paused, moved or excluded.