I think openclaw is OVERHYPED. Just use skills

A detailed user critique of the AI agent platform OpenClaw is gaining traction, challenging its core value proposition. The author, after a week of testing, argues that while features like automated memory, cron jobs, and integrations are technically present, they often introduce more problems than they solve. Specifically, the automated memory is criticized for polluting context with irrelevant information, leading the user to prefer a 'manual memory' approach where they explicitly prompt the system to recall learnings from specific skills like 'superreporttrending-skill'.

The review posits that the true intelligence and utility reside not in OpenClaw's 'runner' or automation engine, but in the individual skills—whether developed in-house or integrated from third parties. The user contrasts OpenClaw with OpenCode Web, which they find superior, suggesting a preference for a more flexible, skill-centric environment where tools are recalled on-demand with up-to-date data rather than running on rigid, automated schedules. This reflects a significant split in AI agent philosophy: one favoring full automation and another advocating for powerful, user-controlled tools.

This critique matters because it taps into a central tension for professionals implementing AI agents. For complex, evolving tasks, overly aggressive automation can reduce control and context relevance. The argument elevates the importance of skill libraries and interoperability over monolithic platform features, suggesting the market may reward modular, composable AI toolkits that empower users to build their own workflows rather than locking them into pre-defined automation loops.