A case study from my own account. Under an hour, no console, every deletion checked before it happened. This page shows exactly what the sweep found, and the one call that mattered more than the cleanup.
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This is the AWS account behind my own projects and teaching work. In raw dollars it is a small bill, and I am saying that up front. What makes it worth a case study is the percentage and the pattern. The same categories of waste sit on bills a thousand times this size, and the method scales with the bill.
This was also not a first pass. A few months earlier I did a full cleanup that removed a real chunk of spend. The 22% documented here is what an agent found after that: waste that crept back in, plus older waste the earlier pass never caught. Some of it dated back to 2019.
The sweep itself was one conversation with Claude Code. I never opened the AWS console.
Cloud waste almost never shows up as one obvious number. It shows up as resources nobody remembers creating, each billing a little every month. Here is what was sitting on mine:
Half of it was hiding in linked child accounts I almost never log into. The agent swept every account in a single pass, which is exactly where a manual audit gets tired and stops.
Nothing was deleted blindly. Before recommending any delete, Claude checked what each resource was wired to.
One S3 bucket looked like an old dump I could safely empty. It turned out to be the live destination for my CloudTrail logs, the record of everything that happens in the account. It stayed.
That is the real lesson of this case study. Running the commands is cheap now. Knowing what is production, and what quietly breaks if it disappears, is the job. An agent can do the sweep. Someone still has to own the call.
Every resource was checked before it was removed, and one live dependency was caught and kept. The other lesson is about time: this account had already been cleaned once, and the waste grew back within months. Cloud waste is not a mess you fix once. It regenerates, so the sweep has to repeat.
If a small, recently cleaned account was still carrying 22% waste, consider an estate with multiple teams, multiple accounts, and years of shipped and abandoned projects. The categories are the same: dead resources, forgotten artifacts, orphaned snapshots, stale logs, and child accounts nobody watches. The bill is just bigger.
For companies I run this as part of a scoped audit: the same sweep across cloud and AI spend, plus the judgment layer, with every finding priced in dollars. How it works is on the audit page.
One caveat, stated plainly: this case study is my own account, and the raw dollars are small. Client case studies with confirmed figures will be added here as audits complete and clients approve publishing.
15 minutes to see if this fits. No pitch if it doesn't.