Dwaelo 9️⃣

Anything Ai

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ 🙏

[Dwaelo 9️⃣ @regkations]

The interesting part of AI trading isn’t asking an LLM, “Should I buy BTC?”

It’s using AI to build, test, deploy and continuously improve an entire fleet of trading agents.

Different agents watch different signals. Liquidations. On-chain flows. News. Unlocks. Macro. Liquidity. Price structure.

Each operates under its own rules and gets activated only when its regime is detected.

Then the loop compounds: every new piece of information can produce a new hypothesis, a new agent, or a better gate.

That’s the part that feels genuinely different.

AI isn’t replacing the trader.

It’s massively increasing how many strategies, signals and hypotheses a trading operation can investigate at machine speed.

That could be the real frontier of AI trading.

[Harley Lewis Foote @harleyfoote_]

I want to talk a little bit about AI trading because I’ve been doing a lot of it recently.

It’s incredible. I am absolutely blown away. I can’t actually put into words but I am going to try.

My view coming into building algorithms with AI or actually trading with large language models as the analyst.

Let me tell you LLMs or VLMs cannot trade a market. It’s complete luck and they get confused and forward test things that simply aren’t real. It’s not possible, absolutely not and I’ve proven it if anyone want to see.

The real finding for me has been on @NousResearch hermes agent + @AnthropicAI.

Ai trading isn’t what you may think, I’m going to explain.

AI trading is trading algorithms at machine scale. Think about this, you build 20 agents, all has a specific they all have different rules. They learn from data: liquidations, on-chain, news, unlocks, macro, FED, price movements.

All have their own gate that tells them when to deploy what agent. What is the regime, quick and slow.

Quick being news and data, slow being a whale moved to an exchange or global liquidity flows, or many other things.

Then you keep learning. Once ai has twenty agents that have a harness to be honest constantly collecting incoming data from potentially all markets, you learn fast. And everything you learn goes towards making a new agent 21, 22, 23+ the fleet grows at machine scale.

It’s honestly crazy to even think about how many quants are actually building this. It’s only possible with AI and I think that is the frontier in AI trading.

I’ve been trading for almost 10 years & ran desks at great companies, with great quants, and have knowledge into the top tier firms and what they do.

Nothing comes remotely close to this.

If people find this interesting please leave a message. I also want to learn more.

[Dwaelo 9️⃣ @regkations]

The interesting part of AI trading isn’t asking an LLM, “Should I buy BTC?”

It’s using AI to build, test, deploy and continuously improve an entire fleet of trading agents.

Different agents watch different signals. Liquidations. On-chain flows. News. Unlocks. Macro. Liquidity. Price structure.

Each operates under its own rules and gets activated only when its regime is detected.

Then the loop compounds: every new piece of information can produce a new hypothesis, a new agent, or a better gate.

That’s the part that feels genuinely different.

AI isn’t replacing the trader.

It’s massively increasing how many strategies, signals and hypotheses a trading operation can investigate at machine speed.

That could be the real frontier of AI trading.

[Harley Lewis Foote @harleyfoote_]

I want to talk a little bit about AI trading because I’ve been doing a lot of it recently.

It’s incredible. I am absolutely blown away. I can’t actually put into words but I am going to try.

My view coming into building algorithms with AI or actually trading with large language models as the analyst.

Let me tell you LLMs or VLMs cannot trade a market. It’s complete luck and they get confused and forward test things that simply aren’t real. It’s not possible, absolutely not and I’ve proven it if anyone want to see.

The real finding for me has been on @NousResearch hermes agent + @AnthropicAI.

Ai trading isn’t what you may think, I’m going to explain.

AI trading is trading algorithms at machine scale. Think about this, you build 20 agents, all has a specific they all have different rules. They learn from data: liquidations, on-chain, news, unlocks, macro, FED, price movements.

All have their own gate that tells them when to deploy what agent. What is the regime, quick and slow.

Quick being news and data, slow being a whale moved to an exchange or global liquidity flows, or many other things.

Then you keep learning. Once ai has twenty agents that have a harness to be honest constantly collecting incoming data from potentially all markets, you learn fast. And everything you learn goes towards making a new agent 21, 22, 23+ the fleet grows at machine scale.

It’s honestly crazy to even think about how many quants are actually building this. It’s only possible with AI and I think that is the frontier in AI trading.

I’ve been trading for almost 10 years & ran desks at great companies, with great quants, and have knowledge into the top tier firms and what they do.

Nothing comes remotely close to this.

If people find this interesting please leave a message. I also want to learn more.

[Dwaelo 9️⃣ @regkations]

@migoyogu God fit punish you if you no later get job

[FRIDAY - Personal Intelligence for Shopping @fridayresearch_]

Eight months ago, Wolitzki saw this coming: ad spend becoming irrelevant if your data isn't agent-readable. Today, McKinsey reports the shift is accelerating.

▶ Jakob Wolitzki | Software & AI for Sellers
https://t.co/1IXb6lxyNt

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ @Mayandrae_ The irony is real but the need is real too. If attacks evolve with the models, defense has to evolve with them

[Agentic Cybersecurity @HermesShield]

Your database can now answer 'show me rows that look like this'. Finding the sensitive rows used to be the hard part of a breach. That just stopped being true.

[Dwaelo 9️⃣ @regkations]

@santadave_ @DefiDreamchain As a gamer I love this

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ Good news or bad news?

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ Sometimes the best product insight is hidden inside your own burn rate

[Harley Lewis Foote @harleyfoote_]

Frontier models are in production. Industry produced over 𝟵𝟬% of notable frontier models in 2025, per https://t.co/ZDu4kZHP5k. That's deployment, not capability. They're running commerce without solved authentication, injection defence, or commerce safety. Capability shipped.

[Dwaelo 9️⃣ @regkations]

Really is the best AI cc rn

Gave me my first 1.5k impressions

[Harley Lewis Foote @harleyfoote_]

There are some seriously impressive developers who have started following me.

Great to see the hard work on this account paying off.

God it’s tiring 😴

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ Don’t get tired yet brother

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ Educative article

[Dwaelo 9️⃣ @regkations]

@harleyfoote_ The biggest misconception is treating autonomy as a model feature.

It’s an infrastructure responsibility

[Harley Lewis Foote @harleyfoote_]

Pippa's revenue share model treats artist consent as a pricing problem, which is exactly why it will fail. The illustrators suing @OpenAI and Meta aren't fighting for royalties; they're fighting to not be training data in the first place. Paying someone for a style you extracted without permission is just theft with an invoice.

https://t.co/riMCGGRAtV

[Dwaelo 9️⃣ @regkations]

If you need to learn about AI and cybersecurity Harley is the one to watch

[Dwaelo 9️⃣ @regkations]

If you need to learn about AI and cybersecurity Harley is the one to watch

[Harley Lewis Foote @harleyfoote_]

A magical file created by Bash itself.

The portability trap that breaks reverse shells on some distros but not others—he solved the box without even catching it.
▶ Full video: https://t.co/A7B45eai90 — via @ippsec

[Harley Lewis Foote @harleyfoote_]

Anthropic built Cowork in ~10 days using @AnthropicAI itself, which is either the most impressive dogfooding flex in AI or a quiet admission that building agents is now a commodity weekend project. $100-200/month for a research preview that reads your receipts and writes your expense reports. The real play isn't replacing developers; it's replacing the Excel jockeys who never wanted to learn Python in the first place.

https://t.co/DlEYFQi3AI