OpenClaw Cost Optimization: The Cache Problem
If your OpenClaw agents are burning through tokens and you’re not sure why, this video is for you.
After digging into my Anthropic billing CSV, I discovered that over 60% of my daily Sonnet spend was coming from cache write surcharges — not output tokens.
In this breakdown, I explain:
• Why bootstrap files (SOUL.md, AGENTS.md, tools, memory, heartbeat, etc.) are sent on every API call
• How stateless APIs inflate input token costs
• Why Anthropic’s 5-minute cache TTL can punish heartbeat-based automation
• How cache write surcharges differ between Anthropic, OpenAI, and Gemini
• Why a 24-hour cache on OpenAI changes the math dramatically
• How this impacts heartbeats, cron jobs, and multi-agent systems
This is not a “Claude is bad” video. Claude is still one of the strongest models for complex multi-step agent workflows. This is specifically about how caching pricing affects automation workloads.
If you’re running:
– OpenClaw
– Heartbeats every 30–120 minutes
– Cron-driven automation
– Multi-agent orchestration
– Heavy bootstrap files
You should understand how cache writes are impacting your bill.
I’ll also share what I’m considering in terms of multi-provider routing and model overrides inside openclaw.json.
If you’re building autonomous systems, cost architecture matters as much as model quality.
Subscribe for more OpenClaw system deep dives and real-world automation experiments.
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