Most organizations scale output faster than they improve scalable decision quality.
That gap is where things start to break.
I’ve seen this play out across every stage, from early teams to systems at Amazon and Meta. Execution keeps getting faster, but the way decisions get made doesn’t adapt at the same pace.
That’s where misalignment, rework, and drift start to compound.
This is where I explore that in public.
If this feels familiar
Decisions that should be obvious keep coming back to you. Different teams are solving the same problem in different ways. AI increased output. But alignment got worse.
Nothing looks obviously broken. But things don't add up. This is not an execution problem.
It's a decision system that was never designed for this level of speed.