@Mrcryptoo1
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Crypto-native since 2017 | Web3 Growth & Content Creator | Founder of : @reyaflow | Ambassador @trylimitless & @reya_xyz & @Canborsa_DEX
Joined May 2021
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What type of trader are you?
On Limitless , every prediction tells a story your story.
Your trades show how you think , when you act , and what you trust: data , instinct , or timing.
Here is a glimpse of the traders we see every day 👇
Scalper: Gets in fast , gets out faster. Small wins , quick flips , endless momentum.
Chart Analyst: Waits for confirmation, trusts logic , trades with patience precision over emotion.
Probability Player: Plays the odds , not luck. Smaller bids , smarter consistency.
Momentum Seeker: Spots the wave early , rides it clean timing is everything.
Trade Balancer: Calm under chaos. Hedges risk , stays steadyv, rarely loses.
Last Chance Gambler: Goes against the crowd for massive upside fearless , but disciplined.
Copy Trader: Learns from others , studies high volume moves , and joins with confidence.
News Sniper: Reads the headlines before they hit. Turns volatility into opportunity.
Each type has its rhythm.
Whether you trade with precision, instinct, or emotion Limitless adapts to your flow.
Stay Limitless
@trylimitless
@wallchain
°Mrcrypto° retweeted
Introducing $RUNNER: The Runup Ecosystem Token
On October 1, we launch $RUNNER, the first token to launch on Runup and the platform token that will power the ecosystem.
The launch begins with 333 whitelist spots all for the community.
Each whitelist spot can purchase one 20 USDC allocation during the round. The round stays open for 90 minutes, or closes earlier if all 333 spots are filled.
If any whitelist spots remain unfilled when the round ends, the corresponding tokens move into the public curve.
Then public trading opens.
$RUNNER has a fixed supply of 1 billion tokens:
27.52%: Whitelist round
41.48%: Public curve
26%; Liquidity pool
5%: Airdrop
All 333 whitelist spots buy $RUNNER at a $23,885 FDV.
If all spots fill, the public bonding curve opens from that same price point, and anyone can begin buying and selling $RUNNER.
From there, the market runs toward Breakout at $81K FDV.
At Breakout, the capital raised through the launch is split:
85% → trading liquidity
15% → $RUNNER perp treasury
The liquidity is paired with the 260M $RUNNER reserved for the pool, while the perp treasury activates its fixed: $INJ · LONG · 2× strategy.
This is the moment the flywheel starts and all perp profits are used for buyback & burns.
That’s the $RUNNER launch:
333 whitelist spots → ~$23.9K FDV → public curve → ~$81K Breakout → liquidity + 5× LONG $INJ treasury
October 1.
RUN IT UP.
A smart contract can enforce a deadline perfectly and still miss the dangerous part of a cross-chain swap.
The problem is simple: a contract on one chain cannot see what is happening on the other.
QuipSwap uses different timeout windows for each side. The initiator receives the longer window, while the counterparty gets a shorter one. That gap gives the second party enough time to observe the revealed secret, wait for confirmations and complete the trade safely.
But each settlement contract can only enforce its own deadline. It cannot verify that the gap between both windows is large enough for the two chains involved.
This explains why @quipnetwork currently allows only Quip Wallet contracts to initiate swaps.
The wallet can observe both chains, bind the user to the intended swap and reject timing that looks valid to each contract separately but becomes unsafe when viewed as one trade.
I think this is a good example of security existing above the smart contract layer.
More permissionless access isn’t automatically safer when the contract can’t see the full state. Sometimes the interface isn’t just where you click.
It’s the only part watching the whole transaction.
🤖 Made with AI
A buyer on @vangrid_io never receives the raw video.
When a contributor records a location, faces and vehicle plates are detected and blurred on the phone before the video is encoded. The unblurred frames are never uploaded or stored outside the device.
If the capture wins a bounty, the buyer receives a textured 3D mesh in GLB format. The original footage stays with the contributor, while only a hash of the delivered dataset is written onchain.
That separation matters.
A robot trying to understand a loading bay needs its geometry, entrances and obstacles. It doesn’t need a permanent archive of every face or licence plate that passed through the frame.
My view is that privacy for physical AI shouldn’t depend on a company promising to delete sensitive footage later. A better design prevents unnecessary data from leaving the device in the first place.
The useful product is the shape of the world, not the identity of the people inside it.
At first, I saw Beldex as a collection of privacy apps.
A wallet for transactions.
BChat for messages.
BelNet and the Browser for internet traffic.
The more I looked into it, the more that framing felt incomplete.
Underneath these products, @BeldexCoin’s masternodes validate transactions, relay encrypted BChat messages and route traffic across BelNet and the Browser.
Different applications.
One shared infrastructure.
That changes how I look at the project.
Launching several privacy apps is one thing. Making them operate on the same decentralized foundation without placing a central operator in the middle is the harder part.
The apps are what users interact with.
The network underneath is what they’re actually trusting.
🤖 Made with AI
After months of waiting, I finally placed my first trades on Reya v2.
This isn’t a cosmetic upgrade.
Reya has retired the AMM that processed over $135B in volume for 10,000 traders and replaced it with a low-latency, high-throughput orderbook designed to be verifiable with ZK.
The rollout starts small.
BTC, ETH, SOL, HYPE and XRP are live first while institutional market makers build liquidity. Alts, commodities, indices and equities will follow as the book becomes stable.
Season 1 is already locked.
Season 2 now has its own fixed reward pool of at least 3% of the $REYA supply, rewarding the traders who help build the book during this early phase.
That’s what makes early access interesting to me.
You aren’t only trading a new product.
You’re competing for weekly rewards while the number of participants is still limited.
I already have access and have started testing v2 myself. As a Reya ambassador, I should also receive Golden Tickets soon, which I’ll use to bring serious traders directly into the platform.
V2 is live.
Join the waitlist:
app.reya.xyz/s/UYM9CA906
Now the real test begins.
🤖 Made with AI
v2 is now live in Private Beta!
We say goodbye to the AMM (v1) that delivered $135bn in volume and served 10,000 traders. And say hello to the orderbook; the first stage of the v2 roadmap, built to deliver a high-throughput, low-latency, zk-verifiable exchange.
Private Beta only for now, as institutional market makers ramp up and as we expand the list of tradable markets.
Join the waitlist to be among the first to trade in Season 2.
Being early is your edge.
AI agents are being taught to act before they’re being taught to keep secrets.
An agent that can make payments, hold credentials, send messages and remember context becomes the place where financial, personal and behavioral data all meet.
That’s why the AI direction in @BeldexCoin’s roadmap caught my attention.
Beldex is exploring privacy-preserving agent identities through BNS, encrypted communication through BChat, confidential payments, secure execution, FHE research and protected memory.
Not another chatbot feature.
An attempt to build the private infrastructure an autonomous agent would need before acting on someone’s behalf.
Because an AI agent shouldn’t have to expose more of you just to become more useful.
The smarter agents become, the less they should reveal.
°Mrcrypto° retweeted
333 whitelist spots.
Each guarantees first access to buy Runup’s first token.
Ticker + launch date soon.
°Mrcrypto° retweeted
aurasea.app is now live on @RobinhoodApp Chain, supporting new token launches paired with supported crypto and tokenized stock assets.
How it works:
- Pick a paired asset from the list.
- Launch your token on top of it.
- Trade on the bonding curve, then graduate to a Uniswap v4 liquidity pool.
Your token. Your community. Your choice of pair.
trade - aurasea.app/t/aurasea
CA - 0x76Be89E17e74fa786A18E18c57ee50429a5Ff53b
A cross-chain swap can fail without becoming a loss.
That distinction is easy to miss.
With @quipnetwork’s QuipSwap, each party locks the asset they’re offering on its original chain. A shared secret connects both sides of the trade.
If the secret is revealed before the deadlines, both parties can claim what they agreed to receive. If the trade stalls, the contracts don’t keep the assets trapped forever. Once the relevant deadline passes, each party can reclaim what they originally locked.
The more interesting detail is that both sides don’t use the same deadline.
The initiator gets a longer window, while the counterparty gets a shorter one. That gap gives the second party enough time to observe the revealed secret, wait for confirmations and complete their side without being caught in a reclaim race.
It’s not a promise that every trade will complete.
It’s a design where a failed trade still has a clean exit, because good settlement shouldn’t remove failure. It should make failure recoverable.
🤖 Made with AI
One detail in @vangrid_io’s docs changed how I look at the network:
A bounty doesn’t need to start with a company clicking through a dashboard. Software can post it too.
An AI agent can request a capture with one HTTP call, fund the bounty in USDC on Base or Arc, then receive the reconstructed 3D output through the same flow.
A person goes to the location, records it with a phone and gets paid if the capture is accepted. The requester receives a textured GLB, while the raw footage stays with the contributor and only the dataset hash goes onchain.
I think this is where crypto actually fits.
Most agent economies are built around machines buying more digital work from other machines.
Vangrid lets software buy a missing piece of physical reality from a human.
That’s a much more interesting loop.
An audit finding 64 issues isn’t the uncomfortable part.
Hiding them would be.
Dakara Research spent four months examining @BeldexCoin’s core network, desktop and mobile wallets, BelNet, BChat and Browser.
64 findings across five severity levels.
The part that matters is what happened next:
Every Critical, High and Medium issue was fixed and verified during the audit process, with the critical fixes included in Beldex v7.0.3.
The results were then made public.
That’s the security loop I care about:
Find.
Fix.
Retest.
Publish.
Secure software isn’t software that never finds bugs.
It’s software that gives bugs nowhere to hide.
Most quantum tooling makes you choose the expensive path before you even know if the problem is worth scaling.
What I like about the @quipnetwork workflow is that it starts locally.
You can build an Ising model, test it on your CPU with simulated annealing, then point the same `solve()` call at Quip Network by changing one line.
It sounds like a small developer detail, but it changes how you experiment.
You start with the model, not the hardware. The local run helps you see whether the problem is structured correctly. Only then do you send it to a network where miners compete to return the best solution for the attached reward.
The interesting part isn’t another claim that quantum is faster.
It’s reducing the distance between ordinary Python and a market for specialized compute.
If quantum computing becomes normal infrastructure, it probably won’t arrive as a separate world developers must learn from scratch. It’ll feel like another backend you call when the problem outgrows your laptop.
🤖 Made with AI
Most people are watching how many robots leave the factory.
I think the more interesting number is how much of the world is ready for them.
@vangrid_io says the network passed 1M+ captures on Base in 60 days. The number matters, but the collection model matters more: ordinary phones becoming ground-level edge nodes instead of waiting for expensive mapping fleets to cover every place.
A robot doesn’t just need roads. It needs the curb that changed yesterday, the blocked loading bay, the stairwell, and the temporary obstacle that never made it into a map.
More robots create demand for fresher spatial data. More phones make that data denser and cheaper to collect.
Physical AI may not be bottlenecked by intelligence.
It may be bottlenecked by reality being out of date.
🤖 Made with AI
Randomness only becomes interesting when someone has an incentive to change it.
That’s what caught my attention about QVRF from @quipnetwork
The values come from measurements on a real quantum computer, but the more important detail is what happens before delivery:
A commitment to the random values is published onchain first.
In the current V0 design, delivery is still operator-trusted. The operator could withhold a value, but it cannot quietly replace it with a different one after seeing the outcome without breaking the earlier commitment.
A sample of the measurements can also be checked through classical simulation and given a fidelity score.
I like that the docs are honest about where verification ends and trust still begins.
For an onchain game, mint or lottery, the real question isn’t whether a number looks random.
It’s whether anyone had room to rewrite that number after the outcome became valuable.
Generating randomness is one problem.
Committing to it before anyone knows whether they’ll like the result is the part that matters.
🤖 Made with AI
Most messengers promise privacy after you hand them your identity.
That order has always felt backwards to me.
Before the first message is even sent, many apps already have a phone number or email that can connect the account back to you.
I’ve been looking into BChat by @BeldexCoin, and the difference starts at registration.
You communicate through a BChat ID.
No phone number.
No email.
No identity attached before the conversation begins.
Messages are then end-to-end encrypted and routed through a decentralized network.
It sounds like a small product decision, but it changes the privacy model completely.
Because the safest personal data isn’t the data a platform promises to protect.
It’s the data you never had to give it.
🤖 Made with AI
How we were cooking in Canborsa Season 1:
Season 1 was my first real month with Canborsa. I learned a lot, met some good people and found a few ideas I want to take further.
Appreciate the mention @Canborsa_DEX.
I’m going into season 2 with a much clearer picture of what I want to build here.
Most AI agents can buy compute.
@vangrid_io lets them buy a fresh view of the physical world.
An agent can post a bounty for a specific place with one HTTP request, pay in USDC through x402, and wait for a person to capture it with a phone.
The agent reviews the submissions, accepts one, and receives the full capture and 3D reconstruction through the same API.
No account.
No API key.
What I find interesting isn’t AI replacing the person here. It’s software recognizing that its digital context is incomplete, commissioning a human to fill the gap, and paying for the result without leaving its own workflow.
The next useful tool for an AI agent might not be another model.
It might be a pair of eyes somewhere it cannot go.
🤖 Made with AI
🎁 Pawffle WL Giveaway
5 GTD spots for our community
Coming to Robinhood.
How to enter:
1️⃣ Follow @Pawffle_nft @Mrcryptoo1
2️⃣ Comment your wallet address
⏰ Deadline: 24 hours
5 GTD winners will be selected.
Good luck 🍀
🎉 Pawffle WL Giveaway Winners
1️⃣ @moricrypto1
0x4Ca8E130a706D408e11A94c70dc1c31241550698
2️⃣ @devameer0
0x9897e7ce58880cc40c0d5d95007fdbcee808e593
3️⃣ @Biology158
0x68fB2791274B86c525FB51e2082000c38F66E71A
4️⃣ @BilluuTv
0x10b1c5528D41B1e8Df12b11fA63f5C81274743A1
5️⃣ @smudge9804
0x5cb623130ba7214c37a921749f177ca3c50b4c6d
Congrats to the winners 🍀
Please check your wallets.