Your AI workflows are probably failing because they have no memory
We accidentally discovered most “AI automation” failures are actually memory failures 😭
Everyone obsesses over prompts/models/agents.
Meanwhile the real operational bottleneck is:
the AI forgets everything every run.
Brand rules.
Approvals.
Customer context.
Formatting logic.
What already failed last week.
What humans corrected yesterday.
So companies end up rebuilding context manually forever while pretending the workflow is automated.
The teams getting insane leverage right now are basically building persistent operational memory layers around their workflows.
That’s the difference between:
“cool demo”
and
“system compounds for 6 months without collapsing”
Been experimenting with this in Runable lately and honestly the memory/orchestration layer feels more important than the model itself now.