idk man, but trading probably isn't the way you're going to make it. Build something. Believe in something. Compound value over months and years. 1min chart < 10yr

New economies unlocked by tokens and infrastructure. We sat down with @GEODNET founder @mikeahorton last November. He laid out the vision, and remarkable progress solana:7JA5eZdCzztSfQbJvS8aVVxMFfd81Rs9VvwnocV1mKHu had made to date. Awesome to see their continued success.

What you can market is a more reliable signal to follow than what you can make.

My guess: token subsidies persist much longer than most expect. The incentive to own the app layer is massive. Billions upon billions will be spent on trying to win it. Anthropic / OpenAi going public will accelerate/extend this.

love this. Alongside building Micro, Brett has been deconstructing successful launch videos for the past few months. (check his feed). Clearly he's put all that insight into this vid. Product seems to be built on the thesis that the harness is valuable, memory makes agents valuable and integrations make it accessible to anyone.

The amount of talent in Canada is surreal

Solid crew.

Basic math.

Six ideas worth stealing from "What AI does to Engineering" w/ @naval, @rauchg, @bscholl & @maxhodak_ - Your job isn't writing code anymore. It's building the factory that writes the code. - AI doesn't flatten talent. It widens the gap. Leverage compounds judgment. - Tokens are the new lines of code. Waste tokens, save time. - Models went from junior executors to principal-level sparring partners. - Taste moved up the stack. Picking the right system beats writing the syntax. -Pure software gets less defensible. The moat moves to the infrastructure agents call. Lots more in there too. Worth a listen.

Had this thought tonight, something workable here, maybe a little far out, but I think that we’re moving into a world where the composition of every startup, or organizational system, will start human and then end AI. Like the desired end state of any organizational system will always be something that becomes entirely autonomous. And the ideal number of humans in an organizational system will be 0. You’ll say I worked on that from 2027- 2029 and now it’s autonomous, and I’m working on this new project now, pre-autonomous.

The greatest gift to startups is when companies like OpenAI, Claude, Google etc. do everything. Just like AI has context windows, humans do too… and humans will allow a product to do 1-2, maybe 3 jobs for them… max. The more the large co’s do, the less likely they are to get people to use them for that particular thing. Humans naturally want products to fit a mental model and a product doing too many things makes it harder for humans to recognize what to use it for, when to use it, and why it’s uniquely valuable. Clay Christensen’s “jobs to be done” is a good model for this… people don’t adopt products because they’re comprehensive, they hire a product to do a specific job. A tool that’s too generalist weakens the clarity of “the job.” That opens the window for startups to enter and tell the user to use their product for XYZ painful thing. It focuses product design, marketing, and resources. When investors ask me “what if Google does this?” My favorite response is… “they’re a public company, you can buy their stock. Why are you talking to me?” Google and every major lab can do anything… literally. And I hope they do because it’s a losing playbook.

Love this, but is Slack the right platform to use? Or do I just need to get over my dislike of slack ..?

More people want to invest than trade. But structurally, it’s much easier to trade than invest. That feels like a valuable misalignment to solve.

Ai is race to the top (vs race to the bottom) technology. It will support both, but uniquely unlocks doing more, better.