Most apps decay into noise as they scale. This one gets more honest.
MIST learns on three loops at once. Here's how a single experiment ends up making the whole system smarter — and why a loud, wrong result can't hijack it.
Three loops. Two gates. Evidence flows in freely — and gets canonized slowly.
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MIST gets better for YOU.
Through repeated self-experiments it builds a profile unique to you and converges on the least-invasive strategy that actually works for your body — not generic advice.
Your data makes everyone's MIST smarter.
Thousands of honest n=1 results, pooled, reveal patterns no single person could see. Convergence across people is what turns scattered self-experiments into real, weighted evidence.
The strongest proof becomes knowledge the system can stand behind.
When evidence converges and replicates, it graduates into a validated framework that grounds the public Kai product — and resets the baseline every future user starts from.
We ingest freely. We canonize conservatively.
Anyone's experiment can enter — but only as evidence tagged with how strong it actually is. Nothing enters as "truth."
Only evidence that converges across many people AND replicates can graduate into a framework.
The promotion gate is where this lives or dies.
Set that bar too low and you've built a confident misinformation engine with extra steps. Set it well and it's a moat nobody can copy. We treat the gate as a hard research problem, not a slogan — because honest uncertainty is the product.
"We win by showing the work, not by sounding certain."The through-line of the whole series — from the weights-vs-context architecture, to one honest day, to the system that compounds it.