As the head of engineering for blitz.gg, dyno.gg, and probot.io I do one thing well: I automate my job, all day, everyday and without OpenClaw.
The fact is, I’ve been automating things since before “agentic” was a buzzword. That is because when I started my career in the release engineering team at Oracle, it was “automate or die” at every turn. When your pipeline involves 647 manual steps and need to run thousands of tests every night, you don’t philosophize about automation. You just do it.
So when the hype machine started screaming about AI agents taking over the world, I had mixed feelings. Not skepticism about AI itself , I think LLMs are genuinely useful. But the framing bothered me.
The idea that you should hand the wheel to a model and let it drive. That’s not automation. That’s delegation to something you can’t fully control, observe, or reproduce.
The Problem
Yes, LLMs can reason about things. They can summarize, classify, and synthesize in ways that would have required entire teams a decade ago. But they’re also non-deterministic, occasionally sycophantic, and depending on which provider you’re using, one deprecation away from your entire workflow collapsing.
Honestly the OpenClaw style of “just give the agent access to everything” approach has a few problems:
- Trust. If an LLM is making decisions autonomously, how do you know it’s making the right ones? You often don’t, until it’s…