Explore evidence-led notes on where AI should run, what agents need after the demonstration, and how technical mechanisms change workflow economics. Claims are bounded to their workload and evidence.
Match an observed AI failure to the least irreversible intervention that can resolve it. This decision ladder separates prompting, retrieval, fine-tuning, distillation, and routing by mechanism, new operating burden, evaluation need, countercondition, and rollback instead of treating them as a technology maturity sequence.
Treat parameter count, dense or mixture-of-experts architecture, and quantization as configuration fields rather than value scores. This guide shows CTOs what each number can describe, what it cannot prove, and how to compare exact artifacts on matched workloads, hardware, service, and recovery conditions.
