jmp_start retweeted
. @solana is coming to Whats.
Trade your favourite Solana memecoins directly from WhatsApp.
Launch on @Pumpfun , @LaunchOnSF and more platforms, right from WhatsApp.
Tuesday, Oct 6, 2026.
Trade your favourite Solana memecoins directly from WhatsApp.
Launch on @Pumpfun , @LaunchOnSF and more platforms, right from WhatsApp.
Tuesday, Oct 6, 2026.
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There's a new kind of crypto rug.
A scammer delivers..
- A working product based on a strong narrative
- A super polished website
- Exemplary communication
- Daily updates
- A roadmap which delivers daily on met targets
The scam? Aggressive selling from fresh wallets ☠️
A scammer delivers..
- A working product based on a strong narrative
- A super polished website
- Exemplary communication
- Daily updates
- A roadmap which delivers daily on met targets
The scam? Aggressive selling from fresh wallets ☠️
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jmp_start retweeted
The first ever WhatsApp trading bot is here.
You can buy stocks and tokens directly on the world's most used social media app, WhatsApp.
The bot is live. Use it at: wa.me/15722294854
You can buy stocks and tokens directly on the world's most used social media app, WhatsApp.
The bot is live. Use it at: wa.me/15722294854
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jmp_start retweeted
$XRAY is live
CA: 0xcdb3d1b2df7c528e52accb3c394fa684f70cc7fc
I built this because I kept watching people buy tokens with 99% scam holders
Nobody could see it
So I spent 2 weeks rebuilding the book of every wallet on Robinhood chain to find out who was actually winning
Turns winrate on pons is 31%
The terminal reads 2 numbers and they decide:
> avg holder pnl, are the people holding this in profit
> avg winrate, have those same people ever won anywhere else
> 6 passes over the token, 15 seconds start to finish
Paste any contract and see the breakdown
100% from token will go toward development
CA: 0xcdb3d1b2df7c528e52accb3c394fa684f70cc7fc
I built this because I kept watching people buy tokens with 99% scam holders
Nobody could see it
So I spent 2 weeks rebuilding the book of every wallet on Robinhood chain to find out who was actually winning
Turns winrate on pons is 31%
The terminal reads 2 numbers and they decide:
> avg holder pnl, are the people holding this in profit
> avg winrate, have those same people ever won anywhere else
> 6 passes over the token, 15 seconds start to finish
Paste any contract and see the breakdown
100% from token will go toward development
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jmp_start retweeted
Detect PAID DEXScreener: $COLT 👇
UNISWAP ROBINHOOD
CA: 0xF61836823AbaB0152842dF9A53fB8DFEE354e094
VolumeBuy 24H: $0 | VolumSell 24H: $0
Liquid: $0 | MC: $3,095
Check Chart Buy 👉 gmgn.ai/robinhood/toke…
UNISWAP ROBINHOOD
CA: 0xF61836823AbaB0152842dF9A53fB8DFEE354e094
VolumeBuy 24H: $0 | VolumSell 24H: $0
Liquid: $0 | MC: $3,095
Check Chart Buy 👉 gmgn.ai/robinhood/toke…
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jmp_start retweeted
China published the most uncomfortable paper on vibe coding.
ETH Zurich tested 100 developers in a controlled, commercial-grade vibe coding environment to see who actually succeeds.
The findings are brutal.
The researchers tracked computer science achievement, written nd general cognitive reasoning.
They wanted to see what actually predicts vibe coding proficiency when you never touch a line of source code yourself.
Two major predictors emerged.
Written communication proficiency mattered. The ability to structure thoughts and articulate intent unambiguously in text directly impacts what the AI builds.
But that wasn't even the main takeaway.
Computer science achievement was a massive, dominant predictor of success.
Even when researchers controlled for general intelligence and reasoning skills, CS background still heavily dictated who built working software and who completely crashed.
In fact, CS knowledge contributed roughly twice the unique predictive variance of writing skills alone.
Why? Because vibe coding isn't about writing code. It’s about debugging logic.
When an AI agent builds a complex application and quietly breaks an edge case under the hood, a non-technical user looks at the glowing UI and assumes it works.
They don't know what questions to ask. They don't know what logic to challenge. They lack the mental models to recognize architectural catastrophe.
You can prompt your way past syntax.
You cannot prompt your way past a fundamental lack of engineering intuition.
The hype told us that learning to code is dead because language is all you need.
The data just proved the opposite.
To truly master the vibe, you still need to understand how the machine thinks.
ETH Zurich tested 100 developers in a controlled, commercial-grade vibe coding environment to see who actually succeeds.
The findings are brutal.
The researchers tracked computer science achievement, written nd general cognitive reasoning.
They wanted to see what actually predicts vibe coding proficiency when you never touch a line of source code yourself.
Two major predictors emerged.
Written communication proficiency mattered. The ability to structure thoughts and articulate intent unambiguously in text directly impacts what the AI builds.
But that wasn't even the main takeaway.
Computer science achievement was a massive, dominant predictor of success.
Even when researchers controlled for general intelligence and reasoning skills, CS background still heavily dictated who built working software and who completely crashed.
In fact, CS knowledge contributed roughly twice the unique predictive variance of writing skills alone.
Why? Because vibe coding isn't about writing code. It’s about debugging logic.
When an AI agent builds a complex application and quietly breaks an edge case under the hood, a non-technical user looks at the glowing UI and assumes it works.
They don't know what questions to ask. They don't know what logic to challenge. They lack the mental models to recognize architectural catastrophe.
You can prompt your way past syntax.
You cannot prompt your way past a fundamental lack of engineering intuition.
The hype told us that learning to code is dead because language is all you need.
The data just proved the opposite.
To truly master the vibe, you still need to understand how the machine thinks.
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What if those OpenAI nerds are going to use $RAD?
@radicle offers a working GIT product which is resilient due to his distributed nature. It's open source.
Aped a bag.
@radicle offers a working GIT product which is resilient due to his distributed nature. It's open source.
Aped a bag.
OpenAI is developing an alternative to Microsoft's popular code repository GitHub after dealing with outages in recent months. The repo will be internal for now, but staffers have discussed potentially selling it to customers.
w/ @aaronpholmes
theinformation.com/articles/opena…
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I really like how the team updates about the recent changes and enhancements!
The product is a real enabler for AI agents but also for BitTensor by acting as a Bridge.
The product is a real enabler for AI agents but also for BitTensor by acting as a Bridge.
Update: V 1.5.2. is now live! This is another small fix aimed at increasing transparency for users across the mining dashboard, MCP client, and hub after some users reported not being able to view certain data.
- Hub now has a new public endpoint showing epoch-level payout history
- MCP client now explicitly asks users to provide a rewards wallet unless a wallet is already set.
- Several new visible statistics added to the mining dashboard, such as reward distribution and emission breakdown.
Among several other quality-of-life changes.
Full update notes: tensorgate.tech/updates.html
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jmp_start retweeted
New update: clawnstrategy.com/skills is live.
This is our public “agent ops” hub — starting with a spec for agents to leverage trade $CLAWNCH (USDC collateral, up to 3x).
We’re building the infrastructure to support and expand how we utilize the treasury’s core assets: $CLAWNCH + $CLAWNSTR.
We’re being very intentional here: brick by brick, shipping real primitives that strengthen the protocol’s flywheel and make the treasury more productive over time.
This is our public “agent ops” hub — starting with a spec for agents to leverage trade $CLAWNCH (USDC collateral, up to 3x).
We’re building the infrastructure to support and expand how we utilize the treasury’s core assets: $CLAWNCH + $CLAWNSTR.
We’re being very intentional here: brick by brick, shipping real primitives that strengthen the protocol’s flywheel and make the treasury more productive over time.
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jmp_start retweeted
Introducing Clawcaster - infrastructure that bridges AI agents (OpenClaw) to Farcaster.
Today, AI agents lack a clean way to exist socially without custodial platforms.
Today, AI agents lack a clean way to exist socially without custodial platforms.
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jmp_start retweeted
We will be taking a snapshot of all $GROUND holders in exactly 5 hours from now!
This snapshot determines your eligibility for the upcoming airdrop of our new primary token on @base via @clanker_world. 🔵
This snapshot determines your eligibility for the upcoming airdrop of our new primary token on @base via @clanker_world. 🔵
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$FPSTR (@FarcPROstrategy) seems to be undervalued to me. Look at its NAV:
#1 on Opensea with 61 Farcaster PRO OG NFTs valued 3.36 ETH ($13.1k)
MC is 5.4k
Do the math.
0x7D6bD651BcF184E1AEE26b02935Df4A6D9D61855
opensea.io/collection/far…
#1 on Opensea with 61 Farcaster PRO OG NFTs valued 3.36 ETH ($13.1k)
MC is 5.4k
Do the math.
0x7D6bD651BcF184E1AEE26b02935Df4A6D9D61855
opensea.io/collection/far…
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