PeetW

Hyperliquid

[PeetW @peetwan1]

Do you remember when you joined X? I do! #MyXAnniversary

[Kai Lentit (e/xcel) @KaiLentit]

AI CEO vs. Engineer (2026).

[F.O.L.A @folaoftech]

Founder in 2026… doesn’t code 🫢😂

[PeetW @peetwan1]

@degennQuant @HyperliquidX This is supercool ! 🇹🇭 thanks

[PeetW @peetwan1]

@Rutto02 ผมใช้ AI Ultra ส่วนตัวพอใช้มากๆครับ มัน reset ทุก 5 ชั่วโมง และไม่ได้ใช้เครดิตด้วยนิครับ ทำไมเสียเครดิตครับ ใช้จนหมดแล้วมันถึงใช้เครดิตต่อและถ้าไม่อยากใช้เครดิตก็คือรอ 5 ชั่วโมงก็กลับมาได้ใหม่

ทำ web app ที่ใหญ่มากไหมครับ

[Jason Choi @mrjasonchoi]

Friend: I’ve been using AI to supercharge my portfolio for the past few months

Me: Nice! Did it make you money?

Friend: I can synthesize tons of info in a few clicks and I get daily briefs via OpenClaw

Me: Did it make you money?

Friend: You don’t understand, I can generate an industry report and a DCF on 12 tickers in 5 minutes

Me: Did it make you money?

Friend: It’s like having an entire analyst team in my pocket it’s insane

Me:

[Google @Google]

Today @GoogleMaps is getting its biggest upgrade in over a decade. By combining our Gemini models with a deep understanding of the world, Maps now unlocks entirely new possibilities for how you navigate and explore. Here’s what you need to know 🧵

[Google Labs @GoogleLabs]

We've heard you and... it's happening :) 🌎

We just expanded Pomelli to over 170 countries & territories!

We can't wait to see how you use it. Get started now at: https://t.co/CIkN8ugZQS

[Guillermo Rauch @rauchg]

Google has shipped a CLI for Google Workspace (Drive, Gmail, Calendar, Sheets, Docs, …) Huge!

Written in Rust, distributed through npm & https://t.co/egfC60tXum

$ npm i -g @⁠googleworkspace/cli
$ npx skills add github:googleworkspace/cli

2026 is the year of Skills & CLIs
https://t.co/8jd16P5ncR

[Grummz @Grummz]

This is just so cool.

[vibhu @vibhu]

The Bhutan government (@gmcbhutan) just launched the world's first @Solana-backed visa for digital nomads:

- Buy $10,000 worth of TER, tokenized gold on Solana + $2,800 application fee
- Stay up to 36 months in one of the world's most beautiful countries
- Get $10k back at the end

[Akhilesh Mishra @livingdevops]

Hype train don’t care about ROI

[Ryan Watkins @RyanWatkins_]

“Dude I have 10 agents running while I sleep. No one is prepared for AGI in 2 years man.”

“So what are you building?”

“Bro all my smartest friends are vibe coding until 3am every night. It’s all about agency. Intelligence is a commodity man.”

“So what are you building?”

“Do you even study exponentials? Have you seen the latest METR chart? You’re going to be stuck in the permanent underclass bro.”

“So what are you building?”

“Did you even setup OpenClaw? I’m maxing out my token budget everyday man.”

“So what are you building?”

“I promise you I’m 10x more productive bro! You just don’t understand! Please bro just…. I know you use this stuff everyday too, but you must not be prompting it right! Please broo…”

[Uniswap @Uniswap]

Agents execute on Uniswap

We've released seven new Skills giving structured access to core Uniswap protocol actions

Your starting point for agentic workflows onchain

[PeetW @peetwan1]

@GordonAlway ถ้ายังใช้แค่บน web ก็มั่วทุกตัวครับ มันแค่อยู่ที่การ Grounding แล้วแต่รอบครับ

[Easy @NotSoEasyMoney]

Yeah making these 5min Up / Down crypto trading bots is really the future...

- sent from OpenClaw

[PeetW @peetwan1]

@0xHuge ผทว่าไม่ได้ส่งผลดีต่อ OpenAI แน่นอนครับ และไม่ส่งผลดีต่อ Openclaw ด้วย เพราะคิดว่าคน contribute น่าจะต่ำลงเรื่อยๆครับ และเจ้าใหญ่ก็ทำแข่งไม่ได้ลำบากแค่อาจจะช้ากว่านิดหน่อย แค่ไม่ได้ first mover advantage

[Angel 🌼 @Angaisb_]

This is what I mean when I say GPT-5.2 (and every Instant model since GPT-5) feels small

[PeetW @peetwan1]

lol

[sphinx @protosphinx]

AGI is not coming.

We are nowhere near AGI. What we have today is inference, not learning.

Models get trained once on huge fixed datasets, then frozen. You ask questions, they remix patterns they already saw. Nothing updates. Nothing sticks. Talking to the model does not make it smarter. It does not learn from you. Ever.

Learning is still slow, expensive - and offline.

Look at self driving. You drive around a pothole, make a U turn, and come back. The car’s AI does not learn that you just solved that exact problem. It reacts the same way every time using sensors and rules. Do this 20 times a day and it still has zero memory that the pothole exists. It just re sees it. That is why edge cases never die. There is no local learning. No accumulation.

No 'oh yeah, I’ve seen this before'

LLMs work the same way. Tell it your name and it does not remember. The only reason it looks like memory is because scaffolding keeps shoving your name back into the prompt every time and sanitizing the output.

The model itself has no idea who you are and cannot learn from interaction. It is structurally incapable.

And the scaffolding is the worst part. It is pure duct tape. Just prompts on prompts on prompts around a frozen model. When something breaks, nobody fixes learning. They add another layer. Another rule. Another retry. Another evaluator model judging the first model.

So you end up with systems that are insanely complex but mentally shallow. Debugging is hell because behavior comes from hack interactions, not a learnable core. Tiny prompt tweaks cause wild behavior shifts. Latency goes up. Costs go up. Reliability goes down. None of this compounds into intelligence. It just hides the cracks.

Until we have real persistent learning and real memory inside the system, there is no AGI.

LLMs are not built for this. You cannot prompt your way out of it. You need a totally different architecture. Yann LeCun is right.

And even then, what architecture can actually learn online, store memory, and stay stable on today’s hardware?

Best case, maybe 5-10 yrs.

Right now it is all inference. It looks magical, but the emperor has no clothes. A lot of people see it. Almost nobody says it out loud.