LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted
Four myths about staking $LINK.
Anyone can deposit to get staked, no reSDL needed. Rewards grow your staked $LINK balance automatically with no further action to take.
stake.link stakes in @chainlink's own staking pools.
Staked $SDL earns a share of protocol fees in staked LINK - $stLINK.
LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted
$KTA Early days, but maybe keep an eye on Keeta forming a double bottom, if it plays out and we break above the blue line you may not get sub $0.10 ever again.
As always just saying.
LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted

Watcher.Guru@WatcherGuru3h
United States
United StatesConnected via WebAccount-level information, not a live location or per-post device.
JUST IN: 🇺🇸 JPMorgan CEO Jamie Dimon says the US economy is "booming."
I wonder when Mimir prediction market will open base:0xc0634090f2fe6c6d75e61be2b949464abb498973
mimir.market/leaderboard
LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted
Watching this 1960s dating show has completely fried my brain, what an era..😍😍
Replying to @retardsgonnawin @MasihEther
GM GM
LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted
Security. Reliability. Institutional-grade compliance.
These are the non-negotiable requirements for moving trillions in tokenized assets across blockchains.
@SergeyNazarov explains why CCIP 2.0 became the interoperability standard for global finance.
Replying to @pharos_network @Anvitamate
Pharos ? oh yeah that network I wasted heaps of time testing and got nothing I remember now
Replying to @Kore_Miner @KeetaNetwork
I'm at the bottom of the shaft
Getting the shaft here boss. If I add more $KTA will that help ?
LinkTOAD goldnutter 𓆏⬡⬢🌊 𓀡 logic/acc truth/acc retweeted
How much better can an agent get without retraining the model? Google Research open-sourced Harness², a framework that keeps model weights fixed and improves everything around them: prompts, guardrails, memory, tool guidance, subagents, skills, scripts and plugins.
For each task it proposes edits, probes them on that same task, and composes a refined harness from how the runs differed, then carries the lessons forward to future tasks. The authors report gains of up to 11.5 points on WorkBuddy-Bench and 4.5 points on JobBench for GLM-5 and Gemini 3.5 Flash. It's Apache 2.0 research code, and there's a local demo that needs no model credentials.
If you build agents, run that demo first, then read the lessons it saves and ask whether you'd have made the same edits by hand. 🔧
#AIagents
Link in Comments
Replying to @TheLinkPanda @vajolleratzii
Hopefully things get better soon fren !





















