[stego-tech]

Amazing article that puts my outsider observations into technically-digestible details. Tangentially, their repeated observations to providers hiding or obfuscating important systems or processes are highly relevant to my own developing case studies for my CurrentCo.

The problem with building automations atop these systems isn’t entirely their probabilistic nature (though that is the lion’s share, at least for me personally), but also the inability to effectively troubleshoot the processes themselves due to key components being obfuscated from view. How can we effectively troubleshoot what went wrong in an agentic loop when we cannot see the reasoning tokens generated from our inputs? How can we triage a broken process when token logs aren’t ours to view? How does one create determinism from increasingly obfuscated probability engines?

All of that is why I spend the bulk of my time testing local models and harnesses for work, rather than leaning on Gemini or Claude. It’s not that I doubt their capabilities, rather that I need to be able to show potential customers where the agent or model made a mistake that caused harm - which is something I can presently only do with local models. That’s why (I suspect) the compliance narrative from the foundational labs has been more along the lines of “humans vetting what AI does” instead of being able to prevent AI from making errors through iterative improvements on a process.