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Everyone talks about AI trading. Very few talk about AI that actually explains its decisions. That's what stood out to me about Engine. Instead of blindly following signals, you can see the reasoning behind every trade, while staying in control of your funds. Definitely an interesting approach to agentic... show more

0xBasit🧑‍💻🐶

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13,755 views • 2 months ago •via X (Twitter)

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Abhi

12,179 views • 3 months ago

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53,758 views • 1 month ago

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 views • 10 months ago

LinkedIn just started hiding AI-written posts. And their system catches them 94 percent of the time. But the answer is NOT to stop using AI. They announced this in May. If your post sounds like everyone else's, it doesn't get deleted. It just stops spreading. Your followers see it. Nobody new ever does. They're even flagging the way AI writes. Sentences like "it's not this, it's that"? Flagged. But most people missed one line in that announcement: using AI to HELP you write is totally fine. You just have to make it sound like you. Here are 2 things you can do: One, give your AI your own stuff. Upload your old posts, your client results, your stories, your data, your transcripts. Now instead of pulling generic advice off the internet, it's writing from YOUR experience. In your voice. Two, write about what people care about RIGHT NOW. I check AnswerThePublic to see the exact questions my audience is typing in this week then I write about those. The more you sound like yourself and talk about real problems people face, the more people will want to hear what you have to say.

LinkedIn just started hiding AI-written posts. And their system catches them 94 percent of the time. But the answer is NOT to stop using AI. They announced this in May. If your post sounds like everyone else's, it doesn't get deleted. It just stops spreading. Your followers see it. Nobody new ever does. They're even flagging the way AI writes. Sentences like "it's not this, it's that"? Flagged. But most people missed one line in that announcement: using AI to HELP you write is totally fine. You just have to make it sound like you. Here are 2 things you can do: One, give your AI your own stuff. Upload your old posts, your client results, your stories, your data, your transcripts. Now instead of pulling generic advice off the internet, it's writing from YOUR experience. In your voice. Two, write about what people care about RIGHT NOW. I check AnswerThePublic to see the exact questions my audience is typing in this week then I write about those. The more you sound like yourself and talk about real problems people face, the more people will want to hear what you have to say.

Neil Patel

12,378 views • 1 month ago

Mobile put a bank in your pocket. AI is going to put a banker in your pocket. Micky 🐸 says AI agents will start making investment decisions on your behalf very soon. “What I expect to see very soon is an AI agent that can do all kinds of investment decisions and recommendations. The agent will do all kinds of commerce decisions and recommendations. It can do any kind of payment decisions on your behalf. The agent is going to free up time for you and give you ideas that you didn’t have. We're just starting. What we expect is that we're going to see a bunch of new companies and incumbents that are going to be shipping these features in ways that we have not experienced before.”

Mobile put a bank in your pocket. AI is going to put a banker in your pocket. Micky 🐸 says AI agents will start making investment decisions on your behalf very soon. “What I expect to see very soon is an AI agent that can do all kinds of investment decisions and recommendations. The agent will do all kinds of commerce decisions and recommendations. It can do any kind of payment decisions on your behalf. The agent is going to free up time for you and give you ideas that you didn’t have. We're just starting. What we expect is that we're going to see a bunch of new companies and incumbents that are going to be shipping these features in ways that we have not experienced before.”

David Senra

43,676 views • 1 month ago

Everyone talks about finding the next trading opportunity. But one thing deserves more attention: the cost of accessing it. → MEXC 0 Fee direction stood out to me because it reflects a long-term User First approach. → With 08/08 getting closer, I’m curious to see what comes next. I shared my thoughts in the video below. Let me know what you think. 👇

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ʜᴀʙɪʙ ʜᴋ

18,187 views • 2 months ago

FundedNext just launched something I think you’ll find interesting. With FundedNext MCP, you can connect your FundedNext account to your preferred AI assistant and instantly ask questions about your account, challenge progress, drawdown, payout eligibility, trading performance, risk patterns, and much more. Instead of digging through your dashboard, just ask. It’s also read-only, so your account stays secure. This is one of those tools that can genuinely help you become more aware of your own trading. Try it here:

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Techriz💯📈

38,829 views • 2 months ago

🔥 Todd Blanche just CALLED OUT Democrats for their conveniently timed AI outrage "This AI issue suddenly came up TWO MONTHS before an election..." "Every Democrat senator suddenly RACES to a microphone to talk about AI after being eerily silent for months and months and months." "So to talk about the timing of this as being nothing but an effort to to influence the midterms.. I shouldn't have to say that out loud. Of COURSE that's what it is." "And that shouldn't be what drives the decisions that we're making around AI. We can't lose the AI race to China."

🔥 Todd Blanche just CALLED OUT Democrats for their conveniently timed AI outrage "This AI issue suddenly came up TWO MONTHS before an election..." "Every Democrat senator suddenly RACES to a microphone to talk about AI after being eerily silent for months and months and months." "So to talk about the timing of this as being nothing but an effort to to influence the midterms.. I shouldn't have to say that out loud. Of COURSE that's what it is." "And that shouldn't be what drives the decisions that we're making around AI. We can't lose the AI race to China."

Nick Sortor

73,767 views • 22 days ago

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XM_COM

13,239 views • 1 year ago

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12,944 views • 6 months ago