A Developer's $2,500 Opus Token Burn on OpenClaw: Real-World Workflows vs. Tooling

A software shop owner on r/openclaw shared their experience of spending $2,500 in Opus tokens using OpenClaw, and it's a candid look at how experienced developers lean on the tool for ad-hoc automation rather than predefined workflows.

What They Actually Did

• Upgraded and bug-fixed their own programs – the core use case.
• Taught OpenClaw vision to click buttons and check screen output for correctness.
• Managed a server running multiple customer full-stack apps.
• Used it as an assistant to fill out website forms.

What “Workflow” Means to Them

The author admits they don't really think in terms of workflows. When they have a process, they just tell OpenClaw to build software for it. Their closest example of a workflow is paying contractor invoices — a manual, non-programmatic sequence saved in a separate memory file:

1. Open the invoice tracking file
2. Go to this week's pay period
3. Line up who submitted an invoice with name
4. Open each person's invoice file
5. Go to this week's spreadsheet in each invoice file

They note that none of this is programmatic, asking the community: “Is that a workflow?”

The Big Picture

This post highlights a common divide in developer usage of AI coding agents: some users build intricate multi-step automations (workflows), while others rely on ad-hoc, conversational interactions even for repetitive tasks. The $2,500 Opus spend suggests heavy usage, but without formal workflow structures — reinforcing that raw token consumption doesn't always correlate with systematic automation.