129 mentions · 16 chunks · 14 episodes
The gradient of adoption for a consumer is: is their expected value of the product greater than the expected cost? If so, there's a gradient of adoption. "Expecte...
... that true information lives at the edge. All markets happen on the margin, the gradient of surprise. If you aren't at the edge. then you don't have real information.
Inductively achievable goals are the gradient of improvement. They have a series of salami slices of actions that are viable. The actions are easy to accomplish (that is, within your adjacent pos...
... improving AI agents. Another example of noisy-but-biased signal still giving a gradient if you have enough of it.
...s an abstract benefit, and has no concrete downside for users. That created the gradient where it could grow without bound. All it needed was the right seed crystal to kick it off. If it had concrete downside, then that would have dominat...
...e, it is effectively closed. It must be possible to adopt a new system across a gradient.
The gradient of competition can only give users what they want, not what they want to want. Users get to decide what to purchase. They'll decide to use the one th...
If you follow the gradients of optimization you get what people "want" not what they "want to want." Don't drive something that matters off a cliff, or let them drive themselve...
...llective. Those are what will be taken, according to Goodhart's Law. That's the gradient that the swarm will follow. An individual who doesn't care about the collective (or feels that it doesn't make sense for them to do an action that's ...
...tification is inevitable for successful products. Over time they roll down that gradient. It's a one-way process, a ratchet. The only question is how quickly it rolls down.
It's not that Goodhart's Law just so happens to find shortcuts. It's that the gradient the swarm descends fundamentally are shortcuts. The ideal vector is what all of the members of the collective, if they didn't know which member of th...
Data can only tell you the gradient, not where to go. If you just follow the gradient, then you'll random walk through the problem domain. If it's short-term data, (e.g. UXR for accepta...
Surprise is the gradient of improvement. Surprise requires a mental model to be surprised in the first place. If you are incurious about the world around you you can't be sur...
Competition is the gradient of improvement. Once no one else can plausibly compete the drive for improvement is gone.[ahp][ahq][ahr] That's how you get stagnation.
...lly like existing alternatives, it's hard to get going. There isn't enough of a gradient to differentiate yourself. But if your thing has an internal network effect that the other things lack, then over time that network effect will get s...
Surprisal gives us a gradient we can choose to follow.