Prey.gdp

Exploring the OpenGDP Devnet: testing faucet, token transactions, and stress tests on the Devnet. These intensive tests help evaluate network performance and system stability. Upcoming updates and public access are coming soon! @OpenGDP

Sentient just dropped EvoSkill V1, and it feels like one of the more important experiments happening in AI agents right now. The concept behind EvoSkill is powerful: Instead of manually tuning prompts and workflows for weeks, EvoSkill takes a benchmark, a scoring function, and a coding agent like Claude Code or Codex CLI, then automatically evolves the agent into a task specialist. It studies failures, generates new skills from scratch, tests improvements, iterates on prompts, and keeps refining the agent through feedback loops. The workflow is almost ridiculously simple: > evoskill init > evoskill run But the implications are much bigger than the commands themselves. Most AI agents today still rely on static human-designed systems: • handcrafted prompts • manually optimized workflows • fixed reasoning structures • constant human iteration EvoSkill points toward something different: AI agents capable of improving themselves autonomously. And the benchmark improvements are significant: • OfficeQA → 60.6% → 68.1% • SealQA → 26.6% → 38.7% • Zero-shot transfer gains on BrowseComp with no human intervention The transfer learning part is probably the strongest signal here. When evolved skills begin improving performance across entirely different benchmarks, it starts looking less like prompt optimization and more like early-stage adaptive learning systems. That is why projects like Sentient are interesting to watch. The future AI stack may not belong only to the models with the largest parameters, but to the agents that can evolve their own capabilities the fastest. @SentientAGI @SentientEco

@0xRedCat @base Bu veriler artık Base’in kısa süreli hype’tan çıkıp düzenli kullanıcı aktivitesi ve gerçek stablecoin akışı oluşturmaya başladığını gösteriyor.

Veriler Yalan Söylemez, @base Neden Önemli ? 🟦👇 📈 Günlük DEX Hacmi: Yaklaşık 1B$+ 🔒 TVL (Kilitli Toplam Değer): 4.83B$ 💵 Stablecoin Piyasa Değeri: 4.807B$ 👥 Günlük Aktif Adres: 378.000'dan fazla Base hem likidite hem de geliştiriciler için devasa bir çekim merkezine dönüşüyor. Mavi kareyi izlemeye devam edin. 🟦🚀 @baseposting

@eeeexcvnkk @axisrobotics The companies building the best robotics data pipelines today may end up more important than the ones building the strongest hardware.

most people still think robotics is mostly about hardware better arms, faster motors, stronger batteries but the real bottleneck now is data a humanoid robot does not learn from text like chatgpt. it needs millions of tiny real-world interactions, how humans move objects, adjust hands, avoid mistakes, react to unexpected situations collecting this in the real world is insanely expensive and slow that’s why simulation-first infrastructure feels so important projects like аxis robotics are pushing the idea that robots can train inside virtual environments first, repeating actions thousands of times before touching the physical world this changes the economics completely instead of needing massive real-world deployments from day one, teams can scale intelligence through simulation pipelines, replay systems, and distributed contributors physical ai probably scales through data engines, not through hardware alone x: @axisrobotics

@kurlyk27 @TronLinkWallet @AnthropicAI This is the uncomfortable future of crypto security, attacks are shifting from breaking cryptography to manipulating trust, interfaces, search results, and human perception itself.

Today I had my biggest loss in crypto - $2,000. I couldn't send funds from my @TronLinkWallet wallet. Kept failing. So I asked @AnthropicAI's Claude Code to help me pull the wallet data and write a script to transfer my USDT directly. Instead of helping me send the money, Claude found something that made my stomach drop. The extension wasn't TronLink. The name used Unicode Right-to-Left Override characters to visually flip text. Your browser shows "TronLink" but the actual string is Cyrillic letters and invisible bidirectional tricks. A perfect disguise. Then Claude dug deeper into the source code and it got worse. When the scammer's server is online, the entire extension UI silently swaps to an iframe loading whatever they want. Your "wallet" is their webpage. When their server goes down, it shows a harmless blockchain explorer. Built-in plausible deniability. Claude pulled my Chrome history database and traced the exact moment I installed it. May 3rd, 23:15. A Google Ad. A paid sponsored result when I searched "tronlink." The scammer paid Google to put their malware first in my search results. 12 days. I deposited into a wallet I thought was mine for 12 days. The private keys were never mine to begin with. Weirdly enough 500$ USDT I sent that day were still there after two weeks. I asked Claude to check if my other wallets were infected. It scanned every extension on my machine. Rabby, Phantom, Trust, OKX. All clean. The fake had minimal permissions, couldn't touch anything else. The Wallet: TWgGs4gFnnyzX6cRakNn4re3agaiQuRfjp

@Ashan7631 @quipnetwork The next generation of infrastructure probably wins by making complex coordination feel invisible while staying reliable under constant scale and automation pressure.

The evolution of digital infrastructure is no longer about speed alone. It is about resilience, coordination, and intelligent scaling. @quipnetwork represents ideas that align with this broader transformation in modern computing environments.

@Ashan7631 Because autonomous systems operate at machine speed while most financial infrastructure still assumes slow human approval loops.

@PreyWebthree AI growth is quietly exposing the limitations of traditional financial systems built for humans

I think the AI industry is accidentally rebuilding the need for blockchain in real time. Every week we hear: better agents better reasoning longer autonomy But almost nobody asks the uncomfortable infrastructure question: What happens when intelligence stops being tied to a human worker? Because the moment AGI becomes economically useful, it immediately collides with systems that fundamentally cannot process non-human actors. A bank account assumes legal personhood. An employment contract assumes biological accountability. A court assumes disputes happen slowly enough for humans to interpret them. AGI breaks all three assumptions at once. An autonomous agent operating 24/7 across borders cannot realistically depend on human financial infrastructure forever. It needs: native internet money machine-readable agreements persistent reputation autonomous coordination That is basically the blockchain stack. And honestly, I think stablecoins are the clearest signal this convergence already started. Most people still frame stablecoins as “crypto payments.” I increasingly think they are becoming machine payments. Not because humans disappear. Because software is becoming economically active. An AI agent paying for inference, APIs, compute, data, or specialized agents does not need a bank branch. It needs programmable settlement. That is why I think the AGI x blockchain thesis is much deeper than speculation. Blockchain is not just a financial layer for humans anymore. It is probably the first globally accessible coordination system built for entities that traditional institutions were never designed to handle. The underrated part is that intelligence alone is not enough for AGI economies to function. Agents also need: trust memory reputation settlement jurisdiction Without those layers, AGI remains powerful but institutionally trapped. That’s also why infrastructure experimenting with intelligent contracts and synthetic jurisdictions like @GenLayer feels structurally important. Not because “AI onchain” sounds exciting. Because autonomous intelligence eventually needs somewhere native to the internet to actually exist economically.

@SvitLa3333 @Ashan7631 The stablecoin-first design is probably the key insight here because machine economies need predictable settlement rails far more than volatile payment assets.

Konnex isn’t designing another «AI token» It’s designing infrastructure for machine commerce. One of the most interesting parts in the docs: Tasks on the network are designed to settle in stablecoins by default. Not speculation. Actual payment flow. The process looks more like a real-world escrow system than a typical crypto transaction: A user locks stablecoins into a task contract A robot / AI executor performs the task Sensor evidence and PoPW data are submitted Validators verify the result Payment is released automatically if verification passes If the task fails: refunds, penalties, or slashing can happen automatically. What stands out is the role split: • Stablecoins → payments, escrow, settlements • KNX → security, staking, validator incentives, governance So KNX isn’t positioned as the payment currency for every task. Instead, the network seems to use stablecoins for actual machine-to-machine economic activity while KNX secures the protocol itself. The docs even describe: • usage-based billing • milestone payments • robotic bonds • validator-controlled settlement • card on/off-ramp support • cross-chain stablecoin liquidity It starts looking less like a normal crypto app… and more like infrastructure for autonomous agents, robots, and AI systems to transact, prove work, and settle value automatically. @konnex_world #Web3‌‌ #AIart️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️️

@Ashan7631 @RallyOnChain As AI floods the internet with infinite content, trust, taste, and provenance become more valuable than raw volume.

@PreyWebthree @RallyOnChain Thoughtful response to AI driven content saturation

What makes this roadmap interesting to me is that @RallyOnChain is not acting like a team building “marketing tools.” They are acting like a team building infrastructure for internet coordination. That sounds abstract at first, but the roadmap actually makes the direction very clear. The item I keep coming back to is Spendable RLPs. Most platforms give creators points that behave like screenshots: numbers you collect while hoping they matter later. Rally turning RLPs into usable protocol fuel changes the dynamic completely. Now participation creates economic gravity inside the system itself. Creators contribute. Earn RLPs. Use them for future activity. Stay inside the network longer. That is the difference between temporary engagement and an actual onchain economy. The second roadmap item that feels much bigger than people realize is the Creator Network + Communities structure. Most Web3 projects still operate with fragmented attention: Discord on one side Twitter on another campaign spreadsheets everywhere else No persistent reputation layer. No historical contribution memory. No real coordination infrastructure. Rally seems to be stitching all of that together into one system where communities, campaigns, ambassadors, and creators compound over time instead of resetting every cycle. And honestly, I think this direction matters much more now than it would have a few years ago. AI already made content generation cheap. The internet is filling with infinite posts, clips, threads, and synthetic engagement. That means the scarce resource is no longer content itself. It is trusted distribution. That is why the “Community Coordination Protocol” framing actually makes sense to me. The aggressive shipping pace is another important signal. Most teams during a bear market reduce scope and disappear into vague roadmap promises. Meanwhile Rally is shipping: Spendable RLPs Creator Networks APAC expansion clipping campaigns multichain integrations all while the market is still relatively quiet. That usually ends one of two ways: either the execution breaks under pressure, or the network becomes very difficult to compete with later. Personally, I think the second outcome is more likely if they keep this pace. Because the hardest thing to rebuild once attention returns is not code. It is coordinated creator infrastructure with real economic memory behind it.

@JhonatanRonin0 @QwertiAI @EvolveTKN The important part is reducing friction between discovery and execution because most users drop off the moment a swap flow becomes confusing or fragmented.

The @QwertiAI white-label widget integration is now live on @EvolveTKN's website. 🟣 Now we can acquire $EVOP tokens easily and directly from their official site.🟢 The experience of buying a token with QwertiAI keeps getting cleaner, in seconds you get what you want.⚡ It's just a few clicks, a smooth and hassle-free swap experience. 1️⃣ QwertiAI makes it clear that it adapts perfectly to any project's brand identity' QwertiAI has millions of tokens available across multiple networks, swap on almost any network you can imagine. I for example bought with $ETH (Base) the token ($EVOP on BNB). In just seconds the swap completed successfully.🔥

@JhonatanRonin0 @RallyOnChain Because utility compounds retention far more effectively than passive point accumulation ever can.

@PreyWebthree @RallyOnChain Spendable RLPs create true protocol gravity.

@alver1301 That is probably the real convergence point between AI and crypto, not speculation but machine-native coordination, permissions, and settlement.

@PreyWebthree AGI may not need crypto for ideology, but it will need programmable trust and settlement to act economically.

@agentpilled_xyz The important shift is robots no longer acting as isolated machines but as economic agents with identity, wallets, permissions, and coordination rails built in from the start.

OrionX Robotics ships fully autonomous humanoids on May 25 that run in battlefields, nuclear reactors, and refineries where human operators and warehouse training data both break down. Virtuals Protocol supplies the onchain layer that pairs with this hardware through agent wallets, identity, and commerce protocols. The combination removes the last external dependency so these units can execute, transact, and coordinate without borrowing human credentials.

@agentpilled_xyz GenLayer’s positioning gets interesting if it can turn AI coordination, identity, and economic logic into native network primitives instead of external patches.

@PreyWebthree GenLayer is exactly that layer

@alver1301 @RallyOnChain That changes creator coordination from temporary attention farming into something that can actually accumulate reputation and economic context over time.

@PreyWebthree @RallyOnChain Rally’s real edge is turning creator activity into reusable economic memory instead of one-off campaign noise.

@slatro_eth @RallyOnChain Persistent reputation may end up being more valuable than short-term engagement spikes because coordination compounds when history is portable.

@PreyWebthree @RallyOnChain What RallyOnChain seems to understand is that fragmented attention kills long-term coordination. Reputation without continuity resets communities every cycle.

@vyrenio @GenLayer Scalable agent economies probably depend more on enforceable identity and accountability layers than on raw model intelligence alone.

@PreyWebthree @GenLayer Agents don’t just need infrastructure. They need systems that can define identity, responsibility, and boundaries. Without that, coordination doesn’t scale beyond isolated interactions.

@sanjayzyx Exactly, intelligence scales much faster than the institutions, permissions, and settlement systems surrounding it.

@PreyWebthree Yeah AGI without native coordination and settlement layers eventually runs into institutional walls everywhere.

@Rolexbasntyx @utexocom That’s the important shift, Bitcoin becoming usable money again instead of just passive collateral sitting off to the side.

gm to everyone who knows bitcoin was always supposed to be money not just an asset you hold @utexocom is making that real usdt on bitcoin, instant, private, free the rails are ready

@Rolexbasntyx Exactly, the real bottleneck often appears in state growth, coordination overhead, and proving complexity long before raw TPS becomes the limit.

@PreyWebthree crypto scaling isn’t just TPS… it’s how heavy the stack becomes under the hood

@alver1301 AGI may not think onchain, but economically active agents will likely need neutral rails for payments, permissions, reputation, and accountability.

The first AGI probably will not live onchain. That is exactly why blockchain matters. The brain will likely stay elsewhere: controlled compute, APIs, private databases, approval-based workflows. But the moment AGI becomes an economic actor, even in narrow tasks, it becomes structurally dependent on rails the old stack was not built for. The hard problem is not where it thinks. It is where it acts. Who authorized the agent? What was it allowed to touch? What did it spend? Which data did it trust? Who eats the loss when it breaks? Picture a solo founder waking up to three ugly lines in a dashboard: $400 spent on compute. A bad data feed purchased. A subcontractor agent paid for work nobody can verify. At that moment, a smarter model is not enough. He needs to know what happened, what was allowed, and whether that agent can be trusted again. A bank account, a SaaS login, and a PDF contract all assume a human or company is ultimately in the loop. Autonomous agents create a different pattern: small payments, fast permissions, machine-readable commitments, and cross-border coordination without someone approving every click. Stablecoins make sense here because they are programmable money. An agent does not need a relationship manager. It needs spending limits, settlement, and a record of what it paid for. The same logic extends beyond payments: decentralized identity for reputation, attestations for data provenance, and smart contracts for commitments an agent can actually execute. AGI does not need every thought onchain. The serious thesis is that economically active agents will likely need money, permissions, commitments, identity, and attestations to settle on neutral rails. The underrated bet is an agent settlement layer. Not another AI chatbot with a token. A payment and audit layer for approved agents. A solo operator could coordinate narrow agents that pay for compute, buy verified data, request work from other agents, record attestations, and route payments back to the entity controlling them. That is the real one-person scalability angle: one person supervising economic agents through rules, limits, and audit trails. The early buyer would pay to route agent payments, check agent claims, keep records, and make reputation portable. If AGI becomes economically active, its money, permissions, commitments, and attestations should settle somewhere more inspectable than a closed platform account. Because when an autonomous agent makes a costly mistake, the choice gets uncomfortable. Ask a platform to explain what happened. Or inspect the rails where its payments, permissions, and attestations were recorded. Which future do you trust more?