I travelled 4,435 miles to attend the @RealVision#CryptoGathering in Miami. Here are my top 3 takeaways, plus a couple of free bonus resources you must check out.
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@lennysan@bot Giving ppl $200 credits is a great way to properly play with @bot and understand its true capabilities.
I think @bot can do so much, but having looked into the feedback on X, people are frustrated with hitting weekly usage limits within days.
It’s a “hot start problem” though
I’m using it to build a personal knowledge base. I have a “Summariser” that captures not only the latest trend in tech and markets, but it also analyses the podcasts that I come across and want to listen to, but short of time on.
I then have a “Tester” which tests me on those knowledge!
@nikhilx22 E.g. I've been procrastinating setting Hermes up on vps. I can do it, but it's a hassle. Whereas Grok Bot, I feel myself wanting to use it right away. That's the power of UI.
Having said that, I do think one needs to be mindful of platform and context centralisation.
@nikhilx22 I think Hermes's full customisability cuts both ways in this instance. It introduces flexibility and control, but at the expense of UI imo
Grok Bot removes the friction for everyday ppl who doesn't want to fuss with vps blah blah. They just need agents that get things done.
@RaoulGMI@bot Yeap I’m very close to going all in on using Grok Bot!
How do you see this working with Claude, Raoul, knowing that you’re a heavy user too? Do you see yourself using one or the other, or they somehow complement each other and have different use case? Thx!
The U.S. Treasury just doubled the maximum size of certain long-term bond buybacks from $2 billion to at least $4 billion per operation.
Long-term yields immediately fell.
But 99% of investors don't udnerstand what this ACTUALLY means-
Here’s what is actually happening: 🧵
The U.S. Treasury just doubled the maximum size of certain long-term bond buybacks from $2 billion to at least $4 billion per operation.
Long-term yields immediately fell.
But 99% of investors don't udnerstand what this ACTUALLY means-
Here’s what is actually happening: 🧵
@ranli_thinker This looks stunning and actually makes reading long-form article a much more enjoyable experience.
Everyone learns differently through different modals. This is great for visual learners who still want to go deep on ideas.
Thanks for creating and sharing this!
Most AI content is backwards. And it's making people feel more left behind.
Here's what ten years at Toyota taught me about fixing it:
Open X right now. Endless demos of what AI can do.
Build this agent. Automate that workflow.
All about the doing.
But showing someone what a tool can do is useless if they don't know what problem they're trying to solve.
It's like handing someone a drill and demonstrating 47 ways to use it without asking what they're actually trying to build. The drill doesn't matter if you don't know whether you need a shelf or a deck.
People collect AI tools like trading cards. They watch the tutorials. They recreate the demos. Then they sit there wondering why none of it feels useful.
That's because they skipped the first step.
At Toyota, we use PDCA: Plan. Do. Check. Act.
Most teams wanted to jump straight to the "Do." They'd see a new tool and start implementing. No diagnosis. No clarity on what good looks like.
We had to pull them back.
"Planning" meant three things:
- where you are now
- where you want to be
- what's in the way
Not bureaucratic. Just the difference between motion and progress.
The same thing is happening with AI right now.
Everyone is skipping to the capabilities without defining the problem. People watch demos to learn what AI can do.
They still don't know what they need it to do.
AI capabilities are abundant. Clarity is rare.
The demos are infinite. Your attention is not.
Capabilities are everywhere. The scarce thing is knowing what you actually need solved.
Before you watch another AI demo, ask yourself:
- What am I hoping to get out of it?
- What problem needs solving?
- What does good look like?
- What's in the way?
The tool comes second. The problem comes first.
The demos are designed to grab attention. They pull you in before you know why you're watching.
Knowing what AI can do is table stakes. The real edge is structured thinking that pinpoints what you actually need solved.
What's one problem you wish AI could solve?
Write it down before you look for the tool.
You might not need a new demo.
You just need five minutes of thinking.
The old 60/40 worked because the environment allowed it to.
That environment changed. The correlation broke.
The new diversification line is AI versus non-AI.
If you're still thinking in stocks versus bonds, you're optimising for a regime that no longer exists.