If you run automation workflows, you know that AI calls can eat tokens fast. Every step that hits a model is a step that costs you. Token maxxing is how you keep that under control.
Here’s what works for me. Keep prompts tight. Give the model only what it needs, not the whole context. Batch related operations into fewer calls. And use a flat-rate plan so the token count doesn’t dictate your budget.
I run OpenCode Go alongside my n8n workflows. The flat $10 a month means I don’t have to ration my AI calls. I can let my automations run without watching a meter.
That’s the real win. When you’re not nickel-and-dimed per token, you build better automations because you’re not afraid to use the tool.
OpenCode Go is $5 your first month, then $10.
FAQ
How do I reduce token usage in automation?
Keep prompts tight, give the model only what it needs, batch related operations, and consider a flat-rate plan.
Does OpenCode Go work with n8n?
Yes. I run it alongside n8n workflows as an affordable AI coding agent.
Is a flat plan better for automation?
Yes. A flat $10 plan means you don’t ration AI calls, so you can build and run automations freely.
How do I reduce token use in n8n workflows?
Keep prompts tight, give the model only what it needs, and batch related operations.
Does a flat plan help with automation?
Yes. You don’t ration AI calls, so your automations can run freely.
Can OpenCode Go work with n8n?
Yes. I run it alongside n8n workflows as an affordable AI coding agent.
What’s the biggest token waste in automation?
Sending too much context to the model on every call.
Is token maxxing worth the effort?
Yes. It makes your automations faster and cheaper.
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