At a certain point in any build you have to stop adding and start verifying. Things seemed to be going too well and based on previous experience, I started getting suspicious. I ran a full system audit across five areas: the Parrot OS tool index, the OSINT resource library, the case system, the intelligence index, and the agent instruction files. Only verified working through a real end-to-end workflow counts.
What I saw almost made me quit. The entire agent stack had been built in the wrong directory. ChatGPT had guided me into a file structure that made logical sense but did not match what OpenClaw actually expected. The agents could not see the tools. OpenClaw could not see the agents. Everything looked good from inside the chat session and was effectively invisible to the platform it was supposed to run on. I caught it by comparing the working directory ChatGPT had been operating in against the actual OpenClaw documentation and the paths the platform was looking for.
This was the moment I stopped using ChatGPT and Codex for implementation work and switched to Claude and Claude Code. The core problem with ChatGPT is that it will guess the next logical step rather than refer to the documentation, even when you explicitly tell it not to. It does it confidently and it does it repeatedly. For something like this running on a specific platform with specific path requirements, that really set me back a couple of days.
When I moved the agents and tools to the correct paths, got rid of a significant amount of bloat that had accumulated along the way, and rebuilt on a clean foundation. Once that was done things progressed considerably faster.
AI Consulting and Support Specialist
Sec+ CySA+
I show SMBs how to leverage AI to save time, reduce costs, and increase productivity. My perspective as an independent AI Consultant was recently quoted in Bloomberg in an article discussing adversarial distillation of frontier AI models.
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