Quazia

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Quazia

Quazia

@LollLunn

token jockey @clanker_world wallet plumber @farcaster always growing

Katılım Eylül 2008
568 Takip Edilen271 Takipçiler
Quazia retweetledi
morganlefay.eth 夢 💹🧲
Just quoted @ripsapp burning another 10B $RIPS (40B total from treasury). This isn’t just another burn. It’s the team removing the biggest source of overhang so $RIPS can actually capture value as the game scales. Game utility loop (why it can stick): Rips is a gamified onchain discovery engine. Users open digital packs in the mini-app (Farcaster + Base App) and pull real ERC-20 tokens from verified projects. It turns the exhausting task of finding quality coins into something fun and transparent — each card is backed by actual tokens. Current loop: > Open packs → discover new ecosystems/tokens > Engage with those projects > Stake $RIPS → get Rips Points multipliers > Climb leaderboard → earn airdrop allocations across seasons This creates real usage + stickiness. It’s not just “play to earn” — it’s play to discover + farm exposure. Sponsored packs (Bankr, AI agents, Charms, etc.) already show projects are willing to pay for distribution through the app. Revenue potential: Primary revenue comes from pack sales (users pay to open packs). Secondary layer is sponsored packs — projects pay to feature their tokens and get direct distribution to active onchain users. As volume of packs opened grows, two things happen: > More revenue flows into the ecosystem. > More tokens get pulled and distributed onchain → increases overall activity on Base. The burns are important here. By reducing supply (100B max → ~70B total now) and committing to burn more on vesting unlocks, the team is making $RIPS scarcer as real usage and revenue potentially increase. Staking for points also locks up supply during farming periods. Current setup: > Very low MCAP with relative volume that punches above its weight > Live product with actual gameplay and sponsored packs running > Team that listens (burned treasury after feedback) and has public vesting wallets > Additional angle: RIPS holders get allocation in the upcoming Plinks token This is still early and high risk — vesting unlocks and execution risk remain. But the combination of fun discovery game + paid distribution channel + improving tokenomics is one of the more coherent low cap setups on Base right now. Not financial advice. Just tracking whether usage turns into sustainable revenue. @nazimahmed @jessepollak @clanker_world
Rips@ripsapp

We just burned an additional 10,000,000,000 $RIPS. Book value: roughly $16K. That’s another 10% of total supply permanently removed. Tx link in comments. This follows our previous 30B $RIPS burn, bringing total burned treasury supply to 40B $RIPS. Why? Because treasury overhang creates uncertainty. And we want $RIPS aligned with the people actually holding it, trading it, and using @ripsapp. No selling. No dumping. No overhang. Straight to the burn address. We’re still early, still building, and still listening. As more tokens unlock through vesting, we’ll continue taking action to improve the long-term health of $RIPS. Naz, @pagameba and the @CoinHeroFun team makers of @ripsapp & @Plinks_App

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Quazia
Quazia@LollLunn·
@pillheadddd Token having utility =/= community stops complaining
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/Pillhead(yes)
/Pillhead(yes)@pillheadddd·
@LollLunn 🫡 re 4 the idea is that baseline tokens get utility out of the box in the form of native staking, lending and leverage which all drive positive price action
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Quazia
Quazia@LollLunn·
@z0r0zzz Isn't clear ice sort of this? Lack of air means slower melt time and harder texture just like the opposite is true of sonic style "good ice"
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ross.wei
ross.wei@z0r0zzz·
they should make a kind of hard ice that melts more slowly
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smol life 🐬
smol life 🐬@life_smol·
@LollLunn @alpeh_v the productivity gains in such cases is more modest. And often a result of even more grinding by the team to meet the expectation of improved productivity
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ʕ •ᴥ•ʔ@alpeh_v·
auditing ai generated code has made me much less bullish ai and I think the bill is going to come due for any company that leans into it too hard
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Quazia
Quazia@LollLunn·
@AzFlin Depending on the tasks too I'm not sure using GitHub for an execution plane is the most secure solution. Maybe good for monitoring or something idk
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Quazia retweetledi
AzFlin 🌎
AzFlin 🌎@AzFlin·
what actually is aeon? i know you guys do not read or investigate, so i decided to myself 😁 TLDR it's a scheduled task runner built on top of GitHub actions You fork their repo, add your Anthropic API key, edit a config file with a schedule of skills (that they wrote), and then Aeon will run this everyday for you on Github Actions. GitHub Actions is a clever serverless way to run code as it's free (for public repos) I could see someone get value in this if the skills are good and you want to fire some out-of-the-box task that you don't want to customize yourself I personally wouldn't use this - the Anthropic API is very expensive, and I can trivially write my own task scheduler / skills myself Aeon is not a coding agent nor an agentic harness. What I really dislike about CT marketing is often things are over-marketed. Something is labelled as XYZ incorrectly but no one bothers to look into what the product actually does. I often cannot understand what a product actually does until I do a deep investigation myself.
AzFlin 🌎 tweet media
aeon@aeonframework

aeon is the most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever ⭐ A growing number of agentic projects are building on top of aeon, let's take an overview of them 👇 > github.com/aaronjmars/aeon

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Quazia@LollLunn·
@alpeh_v Is this universally the case or do you see teams that have tight control and review cycles such that the output of code is actually good?
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ʕ •ᴥ•ʔ@alpeh_v·
not even from a security perspective, but from a code quality perspective. I think with people not looking closely at the outputs the AI gets away with shit you would have fired a junior engineer for
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Yash Khivasara
Yash Khivasara@k2_yash·
@AzFlin the one place step 1 breaks for me is when the model needs data it was never trained on. that's the only reason i reach for retrieval. everything past that is usually solving boredom, not problems.
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AzFlin 🌎
AzFlin 🌎@AzFlin·
Same thing applies in AI > use this LLM > wait it’s outdated, use this new one > now you need long term memory setup ofc, your AI needs to remember things > ok now you need this agentic harness, it’ll supercharge your LLM’s capabilities > but you’re using too many tokens now, try this token reduction skill > you’re only running one agent? What a scrub, you need to parallelize. Use this multi agent orchestration tool. And on and on and on. To infinity. And guess what .. for most people, the most effective path would have been to stop at step 1 Just use this LLM.
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Aakash Gupta@aakashgupta

Every certified personal trainer alive would look at this program and call it garbage. No progressive overload, no rest days, no pulling movements, no periodization, no protein timing. Three exercises and running. That's it. For 1,095 straight days. Tasuke got more shredded than 95% of people paying $200/month for optimized coaching. Run the bull case for modern programming. Periodized splits with progressive overload produce faster hypertrophy in controlled studies. Undulating rep schemes prevent plateaus. Pull/push balance prevents injury. Rest days allow supercompensation. The science is real and the results are measurable. A good coach will get you further in 12 weeks than Saitama's routine will in 12 weeks. No question. Sounds like a win for complexity until you realize what Tasuke actually traded it for. He traded optimization for the one variable that beats all of them: a program so simple he never had to think about whether to do it. 100 push-ups. 100 sit-ups. 100 squats. 10km. Go. The $30 billion fitness industry sells periodization, app subscriptions, macro calculators, and recovery protocols because those are renewable revenue. Adherence to three exercises for 1,095 days generates zero recurring fees. You can't monetize "just keep showing up." 328,800 total reps. 10,000 miles. Built on a routine a fictional bald superhero made up as a joke. The program was never optimal. The program was never supposed to be optimal. The program was supposed to be impossible to talk yourself out of on a Tuesday morning. And that turns out to be the only fitness variable that compounds.

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Quazia retweetledi
banteg
banteg@banteg·
pretty amazing exploit investigation harness based on takopi made by @wavey0x you just send a tx hash and it gets back to you in 15-30 mins with a full report and a root cause.
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AzFlin 🌎
AzFlin 🌎@AzFlin·
man how many of these y'all used i've only used 1 (claude code) kind of embarassing cause i dont know what else is out there; what i'm missing out on but i'm already productive with CC and i don't really have any complaints on it
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Quazia@LollLunn·
@pillheadddd @AzFlin I mean IMO if you're only using one model in your harness you're doing it wrong and I would never use a harness that straps me to a single providers models but 5.5 is deffo stronk af - implementation tho tbh I think 5.3 is still a little better and lately I've been using comp 2.5
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/Pillhead(yes)
/Pillhead(yes)@pillheadddd·
@AzFlin nerd consensus is that you should be using 5.5 these days. i mix it up btwn codex cli and constructor.
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Georgios Konstantopoulos
Open Sourcing Centaur: Multiplayer, self-hosted, secure agents for Slack. Centaur has been transforming how @paradigm and @tempo invest, build and research. Now you can run it yourself on infrastructure you control. Instructions below.
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Quazia retweetledi
banteg
banteg@banteg·
someone complained that last ethereum foundation transparency report was in 2024. tasked codex with making a new one. couple of hours later i had an updated report with all the recent developments.
banteg tweet media
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