Demos are not evidence
A smooth demo can hide setup work, human correction, narrow task design, and fragile reliability.
SLDI Research audits whether AI-agent systems actually reduce delay, cost, supervision, risk, and decision failure — or merely produce faster output with hidden work behind it.
Agentic products are being sold through impressive demos, automation language, and productivity promises. SLDI asks the harder business question: what actually improved?
A smooth demo can hide setup work, human correction, narrow task design, and fragile reliability.
Fast output is useful only when it reduces total delay, error, review time, and decision friction.
Some systems shift the burden from execution to monitoring, correction, prompt management, and cleanup.
“A system is intelligent only to the extent that it reduces the cost of arriving at a better decision.”
SLDI — Law of Delayed Intelligence
We evaluate AI agents, workflows, and automation products through practical outcome measures that matter to businesses and buyers.
Turn product claims into credible proof, identify failure zones, and sharpen market positioning.
Understand whether an agent will save money and time after training, monitoring, and correction are counted.
Compare AI-agent systems through delay, reliability, cost, and operational burden instead of hype alone.
SLDI Research is preparing first-stage audit notes on AI-agent products and workflows. We are open to serious submissions, collaborations, and early audit requests.