Insights · 4 essays · 1 guide
Monitoring the AI flow itself: performance, cost and whether the outcome was achieved.
Guide · AFPM
AI Flow & Performance Monitoring: reconstructing every AI execution as a traceable flow — across agents, models, policies, tools and infrastructure — so it can be observed, explained and controlled.
AFPM
A system can look perfectly healthy while the work it does is slow, wasteful or wrong, so AI has to be judged by the whole process, not just by whether the machine is running.
AFPM
Counting how much computing AI uses is not enough; the number that matters is how much it cost to get the right result.
AFPM
When AI work goes wrong, every system involved may say it did its job, so finding the cause means seeing the whole story on one timeline.
AFPM
AI systems change every week, so keeping them efficient has to be a routine rather than a review every few months.
Thirteen essays and a guide on AI operations, governance, performance and the agent workforce. Follow via RSS
