Interesting analysis, but it still assumes that improving AI systems is primarily an engineering problem.
Whether improvement happens in model weights, harnesses, context layers, memory stores, or evaluation loops misses the more fundamental question:
"Who holds decision authority?"
A system can have perfect traces, benchmarks, evaluations, memory, and self-improvement mechanisms, yet remain ungovernable if intelligence is allowed to authorize actions.
From an IFA perspective, the real architecture is not:
Interesting analysis, but it still assumes that improving AI systems is primarily an engineering problem.
Whether improvement happens in model weights, harnesses, context layers, memory stores, or evaluation loops misses the more fundamental question:
"Who holds decision authority?"
A system can have perfect traces, benchmarks, evaluations, memory, and self-improvement mechanisms, yet remain ungovernable if intelligence is allowed to authorize actions.
From an IFA perspective, the real architecture is not:
Model → Harness → Context
https://tauguard.xyz/
Yes, this is an engineering take