Many projects have attempted a new, decentralized model of applications.

But none of them have had a significant, wide-scale impact.

After looking through many, there are a number of recurring patterns I see:

1) No security model

For composing untrusted components, they'll "figure it out later".

But this is the core dynamic that has to be figured out, you can't retcon it onto a system after the fact.

If you don't have a composition model, you end up with a high friction system with a very small set of composed components.

For example, lots of permission prompts with impossible-to-answer-in-the-moment questions.

And a small number of components that have earned enough brand reputation for people to be willing to take a leap of faith to use them: a heavily centralizing force.

2) No ecosystem dynamic

These might have an infrastructure dynamic

That is, the provider builds a given integration at fixed cost, they can re-sell it to many users with low marginal cost.

But an ecosystem dynamic makes the product more valuable at a compounding rate with the size of activity in the system.

An ecosystem dynamic requires things created in the ecosystem to be able to be used by others without the provider doing any work at all.

Can good ideas from your most motivated users bubble up and help the less motivated users without your involvement?

If not, then you don't have an ecosystem dynamic.

3) B2B

In some ways, B2B is easier, because you can go after a specific business problem and immediately get revenue in the door.

But businesses are also typically only willing to pay for things that solve a direct problem for them.

A lot of these new paradigms have an ecosystem effect, where they get radically more useful overall the more engaged users there are.

You can draft off hyper-motivated individuals who are tinkering and experimenting, and use their improvements to improve the thing for other users, too.

But if they have to be high-intent, paying B2B customers, that is much harder to activate, much slower.

A low-friction model that allows tinkerers to create value might get to a large enough value proposition for businesses to want to use it later.

4) Non-turing-complete

There are a lot of cool alternate-physics protocols and ecosystems in for example the social networking space.

These are interesting and have potential, but they're fundamentally about messaging, not creating.

There's limited space for turing-complete tinkering that could buoy the whole ecosystem.

5) Requires a command line

There are lots of ecosystems that grow a highly engaged developer community with tons of momentum.

But they assume that users will use a command line, if only for a few actions.

But this sets a very low ceiling on the size of the plausible user population, and can be hard to break out of.

6) Only as good as the AI.

A lot of systems rely on the single core model having high enough quality.

But if it's not, the product fails at that use case

The AI's quality sets the ceiling, instead of the floor.