OpenClaw users seek smaller contexts

Bigger hardware helps, but the real fix is usually architectural: an agent should stop dragging every log, note, and intermediate thought into the next call. Keep durable state out of the live prompt by summarizing prior steps and storing long-term memory separately. Strip tool output aggressively so each turn only reloads the few files, snippets, or commands that matter right now. Break work into narrower phases or sub-agents so the model sees smaller objectives instead of one giant catch-all context. Local agent stacks tend to bloat fastest when session history, codebase scans, and action logs are all treated as equally important.