Goodwaitik ./

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Goodwaitik ./

Goodwaitik ./

@goodwaitik

artist / builder / moderator

Katılım Eylül 2024
1.6K Takip Edilen1.3K Takipçiler
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
still not in @liquidtrading discord? you're making a mistake it's not just a chat, it's a place where traders actually share how they trade and why they make certain decisions here's what you can find there: ⤷ strategy channel with full position breakdowns and entry logic ⤷ active chat to discuss markets, strategies and ideas anytime ⤷ content channel where the community supports quality posts and the team rewards active contributors with roles if you're using Liquid and still not in the discord - you're missing a lot join in: discord.gg/vGcCjQEghE
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
everyone in AI right now wants larger context windows • more tokens • more memory • more compute but almost nobody talks about how difficult context scaling becomes in practice this graph is actually pretty interesting because it shows how even top models start losing consistency as input/context size grows and the important part here is that this isn't only a model intelligence problem anymore once AI systems become large and distributed enough, execution quality starts depending on: • routing • inference load • execution environments • node coordination which means scaling compute alone no longer guarantees stable output quality at some point distributed AI systems stop being just a compute problem and become an orchestration problem and this is exactly @Gradient_HQ is trying to solve through execution-aware orchestration across the network
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
@Nekt_0 i've used MetaMask and Avichi before, but compared to KAST (which im using now) they're noticeably worse
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
decided to compare some of the most talked about crypto cards rn used metrics like: • availability • cashback • crypto-native UX • payment experience • ecosystem/community • card design • self-custody integration tbh the results turned out pretty interesting each card has its own strong side: @MetaMask - strongest wallet ecosystem @gnosis_ - very strong self-custody and infrastructure approach @AviciMoney - premium crypto-native vibe @ready_co - polished fintech UX but @KASTxyz currently feels like one of the most balanced options overall btw this isn't just a conclusion based on the table - me and my friends have actually used every card here so the difference in UX and overall payment experience becomes pretty noticeable in real usage
Goodwaitik ./ tweet media
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꧁꧂Anomalia ꧁꧂
꧁꧂Anomalia ꧁꧂@Anomaliiq·
Pyth adding cocoa, coffee, sugar, and live cattle feels oddly timely. Not because “commodities are next,” but because everyone is suddenly watching the boring stuff again. Food prices Tariffs Weather Supply chains Cattle Energy Metals All the things that actually move the real world. And now more of that pricing is becoming usable onchain. BTC to beef cattle sounds like a meme, but it’s also probably where markets are going. @PythNetwork
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Borsch
Borsch@borsch737·
⚽️Arsenal vs Crystal Palace could end up being one of the more entertaining EPL matches this week. Palace at home usually creates problems even for stronger teams, but Arsenal’s attacking form has looked way too solid lately. I’m expecting Arsenal to control most of the game, but I still think Palace finds a goal. That’s why I ended up taking a 2-1 Arsenal prediction here. Been testing the new Football Market on @42space and I genuinely like how much deeper it feels compared to basic prediction markets. The exact score system and match scenario trading make the whole experience way more interactive than simply picking win or lose. 👉If you want to check this match market yourself: 42.space/share/17793622…
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Kuznets
Kuznets@kuznetsjeka·
the paradigm change of ai agents in automated finance automated agents are changing the financial world on-chain but face one major obstacle: legacy market data. fragmented data sources, inconsistent formatting and high latency have left the automated agent community with an inadequate amount of reliable market data to make good and timely decisions, or to successfully execute trades. in short, the data structures of legacy market data were not designed to support machines. @PythNetwork is addressing this challenge. pyth pro: the data engine for automated financial execution pyth pro's data engine enables algorithmic trading and next-generation ai trading through the provision of a single api. the key characteristics of pyth pro will provide the following benefits to the automated agent community: • instantaneous, high-fidelity (truly real-time) and low latency (sub-second) between taking market data and using it for automated decision-making. • cross-asset (crypto, fx, equities & commodities) access to market data and unified standardization across data sources. • last, institutional-grade infrastructure to support multi-assets on-chain decentralized finance products and prediction markets at scale. pyth pro's impact on the downstream market is significant: reliable market data smart analysis + automated execution = better decisions and optimised outcomes. if ai agents represent the future of automated execution, then pyth pro represents the data platform that drives accuracy for them. the age of automated finances on chain at scale is now a reality!
Kuznets tweet media
Kuznets@kuznetsjeka

cutting out the middlemen: why first-party data is the only way forward for defi the integrity of a protocol is only as strong as the data powering it. most oracles rely on "reporter networks"-a complex chain of middlemen, aggregators, and third-party apis that introduce latency and points of failure. @pythnetwork changes the game by moving to a publisher network model. why first-party data matters: • direct sources: data comes straight from the world’s biggest exchanges and market makers (like jane street and cboe). • signed at the source: information is cryptographically signed by the owners themselves, ensuring it hasn't been tampered with. • no middlemen: by removing the "aggregator layer" used by legacy oracles like chainlink, pyth eliminates unnecessary delays and potential manipulation. • maximum precision: sub-second updates directly on-chain mean your dapps react to market moves as they happen, not seconds later. the comparison is clear: legacy networks use third-party apis and independent node operators (middlemen), creating a "diluted" price feed. pyth connects the source directly to the smart contract. in the world of high-stakes defi, accuracy isn't just a feature-it's a requirement for survival.

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Nomber.inj 🥷
Nomber.inj 🥷@NomberFax·
Music IP is finally moving onchain! @Injective and Musicow are bringing fractional music ownership into crypto, turning songs and royalties into programmable financial assets. In this video, I break down why this partnership matters. 🎵👇
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
@1Asgore1 да чота умное захотелось сделать, решил карты сравнить хайповые
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Goodwaitik ./
Goodwaitik ./@goodwaitik·
@anstapnever idk, based on the official information about this investment round, they didnt participate in it... but maybe you're right
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anstap
anstap@anstapnever·
@goodwaitik "with continued support from Paradigm" doesn't that mean they also threw in their share? you think it just means they're continuing to support their first investment round?
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Waka
Waka@Waka_qq·
Bridge Kit on @arc is integrated with @pharos_network Developers building on Pharos can now integrate cross-chain USDC transfers with CCTP in under 10 lines of code. This gives Arc builders a much faster and simpler path to cross-chain USDC liquidity for RWAs, DeFi, payments, and more. Start building on Arc today📍 docs.arc.io/app-kit/bridge
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Keith (❖,❖)
Keith (❖,❖)@ferdo717·
Ritual feels like one of the clearest examples of AI x blockchain moving from theory into actual infrastructure. Ritual is building a system where agents can already operate with real autonomy.💥 What stands out most: Ritual treats core agent capabilities like model calls, scheduling, keys, attestation, and execution guarantees as native infrastructure. That matters because real autonomous agents need more than intelligence. They need: • Persistent execution • Secure identity and key management • Reliable scheduling • Verifiable actions • Access to onchain and offchain tools What’s especially interesting is the developer experience: Install the skill system, give your AI agent instructions, and it can start building dApps by selecting the right precompiles, contracts, and workflows step by step. In simple terms: You describe the outcome. The agent handles much of the technical process. That lowers the barrier significantly for builders and makes Ritual feel less like a blockchain and more like an operating environment for autonomous software. Link in comments. Gritual fam💚 @ritualfnd @ritualnet
Keith (❖,❖)@ferdo717

Another amazing dApp from the Ritual community: Ritual Paws by _neitenoz26, and the creativity is really impressive.💥 You get your own virtual pet and take care of it by feeding it, playing with it, bathing it, and putting it to sleep so it’s powered up for the next day. You can also: • Check your pet’s status • Choose different pet designs from inventory • Create your own Ritual Paws card Fun, creative, and definitely worth exploring. I’m sharing my video experience exploring Ritual Paws + my own Ritual Paws card. Link in comments.😻 @ritualfnd @ritualnet

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Miracles
Miracles@og_miracles·
3 free GitHub repos every Polymarket trader should know most people still trade the headline but the better edge usually comes from infrastructure: > orderbooks > liquidity > wallet flows > market risk > automation > signal filtering here are 3 repos worth studying: 1. Polymarket/agents an official Polymarket framework for building AI agents it includes: > Polymarket API integration > agent utilities > RAG support > news and web search data sources GitHub: github.com/Polymarket/age… 2. NYTEMODEONLY/polyterm Polymarket inside your terminal the repo includes tools for: > orderbook analysis > whale tracking > arbitrage scanning > market risk grading > signal-based predictions this is the kind of tool that makes Polymarket feel less like a website and more like a research terminal GitHub: github.com/NYTEMODEONLY/p… 3. ent0n29/polybot an open-source Polymarket trading infrastructure toolkit built around: > paper and live execution > strategy runtime > ClickHouse analytics > market and user trade ingestion > Grafana and Prometheus monitoring not something to blindly run with real money but if you want to understand how Polymarket infrastructure can be built, this repo is worth reading GitHub: github.com/ent0n29/polybot most traders are trying to predict the outcome the smarter game is building systems that tell you which markets are even worth touching
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Ridark@ridark_eth

x.com/i/article/2055…

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Nekt0
Nekt0@Nekt_0·
A 19-year-old in Prague just bought his parents an apartment Cash They thought he was studying computer science He was Just not the curriculum they expected Here's his exact bot: t.me/poly_parlay_bo… He built it during his first semester using university computing resources His edge: Polish and Eastern European political news - Local elections - Coalition negotiations - Regional diplomatic developments The crowd on Polymarket is overwhelmingly English-speaking They don't read news They don't follow politics They don't track local government shifts that affect EU markets He does His claude bot monitors every major Polish, Czech and Hungarian news outlet simultaneously Finds Polymarket political markets that haven't priced regional developments yet When a cluster appears he opens this: [ссылка] Instead of entering each mispriced market separately One parlay where each correct call multiplies the payout of every other leg January: +$1,400 April: +$8,200 Last month: +$22,000 His parents thought he was at the library He was Just not studying what they thought The apartment closed last tuesday
Fokki@0x_fokki

x.com/i/article/2056…

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Insomnia
Insomnia@insomnia_vip·
This is currently the largest DeFi protocol in existence The total TVL of @aave already exceeds $14.6B But the real value is hidden in the smart contract architecture Core Modules manage token interest rates Flash Loan features provide instant arbitrage liquidity Data & Storage separates pool configuration storage Configuration is managed directly through the DAO And this is only the surface of how deep and interesting the system actually is If you want to truly understand how it works you need @CyfrinUpdraft The course covers all the core fundamentals and helps you understand the deeper mechanics
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Insomnia@insomnia_vip

You are either the 100k winner or the dupe submitter on @CodeHawks

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Ji1n
Ji1n@Ji1n11·
Gm fam Here’s what I’ve got planned for today: - Visit the barber - Read something new about copywriting - Post something if I can - Finish a few tasks irl - Get ready for the gym tomorrow How’s your day going?
GIF
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Vova Sadkov
Vova Sadkov@vsadkovv·
tokenized stocks are now live on LAB a few thoughts after spending the last few months on this: > the brokerage stack is one of the most overbuilt parts of finance. four or five companies sit between you and the trade, each taking a cut, each adding a delay. when you collapse it, you realize how much of "investing" is just middleware tax > retail traders have been getting the worst deal in finance for 30 years. fx fees, custodial fees, withdrawal fees, settlement delays, limited access to specific tickers. tokenized equities fix this almost by accident > the people most excited about this aren't crypto natives. they're people who've been locked out of capital markets their whole lives. that's the actual customer settlement was always the moat. t+2 is now t+0. once people experience that, they don't go back
LAB@LABtrade_

Tokenized stocks are available for trading on the LAB app Clean execution, no unnecessary steps, just you and the market Once you trade like this, there’s no going back

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bolivian@_bolivian

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