3 weeks of OpenClaw: token costs, loops, and compaction — lessons from the trenches

A developer on r/openclaw shared hard-won lessons after three weeks with OpenClaw. The post covers five major pain points and their fixes — practical advice for anyone stuck in the agent-configuration grind.

Don't use Opus for everything

The biggest money waste: running Opus on trivial tasks like heartbeat checks and cron pings. The user switched to glm-5.1 for routine work and only uses sonnet 4.6 for tasks that require reasoning. This cut token costs by roughly two-thirds.

Agents loop and forget by default

Out-of-the-box agents loop, forget decisions, and ask bizarre questions. The fix: write custom rules including anti-loop instructions, context summaries, and verification steps that make the agent confirm its actions before asking for more input. The user emphasizes this is tedious but essential — it's what separates a working agent from a broken one.

Start small, add features one at a time

Trying to wire up email, WhatsApp, web scraping, and cron simultaneously broke everything. The user backed up, started with email summaries only, got that solid, then added each feature incrementally. Obvious advice, but easy to ignore when excited.

Compaction destroys long-term context

OpenClaw's context compaction gradually erases decisions made days ago. Workaround: dump important info into workspace docs, maintain decision logs, and feed the agent reference material before each session. It's annoying but makes a night-and-day difference in agent memory.

Consider Autoclaw for setup if not technical

For users overwhelmed by initial configuration, Autoclaw offers a one-click installer with preloaded skills. The user found it helpful to avoid fighting with installation issues.

The user's final warning: those “my agent built a full app overnight” posts come from people who spent weeks tuning their config first. Don't compare your day three to their month three.