Jobs that will exist by 2030: Postmortem personality custodian
When someone dies, their AI twin doesn’t disappear. It will still recognize their voice, memories, habits, opinions, and decades of conversations.
The custodian’s job is to decide what happens next.
Should the AI continue to talk to family or be shut down forever? Should it be allowed to learn from private memories and messages, or should it keep them sealed forever? If the person was a scientist, artist, or world leader, should a sanitized version of their agent, stripped of intimate memories, be preserved for research and education?
And what if those historical AI agents become so valuable that museums, universities, or private collectors want to buy them? Who has the right to sell a digital personality? The family? The government? No one?
By 2030, inheritance won’t just be about money or property. This will be about deciding who gets the mind after a person dies.
@RallyOnChain
Building infrastructure is hard. Building it from scratch is even harder every time.
That’s why ideas like nested chains and progressive governance are so prominent. Let builders focus on building great apps while also achieving independence over time.
I’m excited to see more people sharing the Canopy story 🌿
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Help tell Canopy's story - and get rewarded for it 🌿
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If this is your first time opening @sleepagotchi, don’t rush into collecting points ⛔
Take five minutes to set everything up properly.
Connect your health data.
Set your sleep window.
Link the accounts you actually use.
Make sure your Hub profile matches.
The app is much more useful when it has the right context, and you’ll avoid having to fix incompatible accounts later.
Small tweaks, smoother journey 💜
Many people ask what makes @TheARCTERMINAL different, so here’s the simplest way I can explain it.
Most AI tools work like this:
1. You open the app
2. You type in a request
3. The AI responds
4. You repeat the process tomorrow
ARC has a much bigger goal.
Instead of treating AI as a chatbot, it treats it like an operating system where context, memory, and persistent execution all work together.
That means the goal isn’t just “better answers.”
It helps agents remember what’s important, keep track of what’s in progress, and ultimately complete tasks based on your goal, instead of waiting for endless requests.
You spend less time repeating yourself and more time building.
This is the part I think a lot of people overlook.