Learning
Turn scattered effort into a curve that bends upward. Fewer detours, faster feedback, deeper understanding.
What should I learn next?
Three landscapes
Where the randomness is — and where the leverage is.
We start with three domains where small, well-chosen steps compound into very different outcomes.
Careers
Treat a career as a search problem: sample options cheaply, keep what gives signal, and commit when it counts.
Which path fits me best?
AI leverage
Put AI to work as a multiplier — for thinking, building, and deciding — so each step you take goes further.
How do I 10× my own work?
The method
Explore, read the signal, converge.
Borrowed from stochastic optimization, applied to people. Noise isn't the enemy — it's how you escape a local minimum.
01
Explore
Try many things, cheaply. High temperature, wide steps, no regrets.
02
Read the signal
Measure what moved. Separate the gradient from the noise.
03
Converge
Lower the temperature. Commit to the direction that keeps paying off.
Status
This is a blueprint, not a finished map.
Synchastic is taking shape. Programs, writing, and tools are on the way.
Currently exploring — check back soon