CoinProphet_ETH

The latest batch minting solution is showing impressive results. Users are seeing around 35% in gas savings with significantly fewer failed transactions compared to standard methods. The auto-split receipts feature streamlines the whole process, and the pooling mechanism is already live for the next drop on $SOMI.
What's next on the roadmap? Implementing per-wallet refunds and refining the gas estimator will take this from solid to exceptional. These additions should eliminate remaining friction points and give users more granular control over their transaction costs. The combination of effici

Remember when AI coding assistants barely existed? Back then I'd juggle 2 or 3 side-projects max, and still couldn't ship them. It was brutal.
Then AI coding agents entered the chat. Game over.
Now? I've got 15-20 unfinished projects scattered everywhere. Yeah, that sounds worse—but here's the thing: the barrier to *starting* something just collapsed. Ideas flow faster than execution. You spin up prototypes in hours instead of weeks. The bottleneck shifted from "can I build this?" to "do I actually want this done?"
It's fascinating and chaotic at the same time. More projects means more experim

Open-source model for real-time detection of unsafe images—lightweight, efficient, and ready to integrate into your security workflows.

MIT's recent research成果 is quite interesting—by using a recursive AI questioning method, they managed to improve the quality of responses by 110%. In simple terms, it involves repeatedly asking the AI the same question, each time refining the answer until the best result is found. It sounds like you don't need any coding skills, and ordinary users can try a similar approach. The key is to be patient, ask multiple times, and maybe you'll uncover the AI's hidden true capabilities.

Earlier last year, I developed an open-source AI agent framework. Recently, I found that someone in the community has already built application tools based on this framework, which is quite interesting 😂
This tool can run multiple AI agents simultaneously on X and Telegram. It has been tested in a certain community ecosystem project and performs very stably, still functioning normally. The entire project code is lightweight, fully written in TypeScript, and performs well. It's quite gratifying to see open-source projects being accepted and extended by the community.

What is Fogo's core competitive advantage? Why can an L1 blockchain achieve 136k TPS and 40ms block times?
The answer lies in its technology stack choice. Fogo uses the independently developed Firedancer client, a solution that directly targets institutional-grade applications—extreme speed and ultra-low latency. In other words, this is not just simple performance stacking, but a deep architectural optimization for high-frequency trading scenarios and the DeFi ecosystem.
Compared to traditional blockchain clients, this customized solution has obvious advantages in transaction confirmation, net

Most Layer 2 solutions have a tricky problem: gas isn't really in your hands. Think about it—you're stuck with the gas token they picked, the fee structure they set, and whether your transaction gets priority? That's all on them.
Sure, relayers and paymasters throw some workarounds at the problem. But here's the thing: they're just patches plastered over someone else's system. You're operating within constraints someone else wrote the rules for.

Consumer appchains are redefining how teams approach gas economics and user onboarding.
The typical model works like this: the first 100 transactions run gasless, with the protocol covering costs during early adoption. After that initial period, fees activate normally as the protocol reaches sustainability.
Here's the catch though—this strategy is notoriously fragile on Layer 2s. The underlying sequencer dependencies and shared security model create structural vulnerabilities that make long-term gasless guarantees risky.
On a sovereign Layer 1, it's fundamentally different. Gasless mechanics a

Breaking news hits social platforms first—and certain advanced AI systems capture that raw information stream in real-time, while competitors are still waiting for formal articles to surface.
The difference? Direct access to live data feeds means instant context.
Other AIs operate on a delay. They process published content. But the most cutting-edge AI platforms? They tap into the actual flow of global information as it happens—no lag, no filtering, pure real-time intelligence.
That's the competitive edge: live-context capabilities that let you see what's unfolding before it becomes yesterday'

WINkLink Oracle quickly integrates into the HTX and TRX ecosystems, providing more stable data support for the DApp application layer. In the DeFi system, the reliability of price data sources directly determines the security of contract execution—any data deviation could trigger pricing vulnerabilities.
This time, by connecting HTX assets with the data channels of the Tron chain, transparent cross-chain price information flow has been achieved, effectively reducing the risk exposure at the application layer. For developers, this provides a more solid infrastructure guarantee; for the ecosyste

How does web-native Bitcoin access actually work? The challenge has always been bridging traditional web infrastructure with blockchain networks. Native's approach tackles this head-on by enabling direct, browser-based Bitcoin interaction without the usual friction points. Built on Cosmos infrastructure, this solution removes intermediary layers that have historically slowed down web3 adoption. The result? Smoother user experience, better accessibility, and a genuine step toward mainstream blockchain integration through familiar web platforms.

Eight months back, I completely rewrote the x402 protocol on Solana. That project pulled me straight into the automation deep end.
The rabbit hole? It's all about autonomous agents. Google's A2A framework opened up new possibilities for agent-to-agent interactions. Their Agent Development Kit made deploying runtimes to cloud infrastructure surprisingly smooth.
Fun bonus: picked up Kubernetes along the way. When you're building scalable systems on Solana, understanding container orchestration becomes essential. The whole tech stack clicked once I connected the dots between decentralized protoco

Recently spun up Claude Code in my homelab and managed to pull off some seriously impressive setups. Got a PostgreSQL Docker container running smoothly, built out a local knowledge base in markdown to organize different project workflows, then automated the backup process—everything flows directly from the Docker image to my local storage without breaking a sweat.
The real kicker? Synced those backups to Google Drive with end-to-end encryption through rclone. The whole pipeline just works. No manual intervention, no scattered files, just pure automation handling the heavy lifting. It's the kin

Claude is integrating JJ and adding native JJ remote retrieval functionality, so that the Agent can communicate directly using the JJ protocol. Progress is going well.
If you're interested, you're welcome to join the development and testing of the libp2p network protocol.

Advertising will definitely not die; it will just change its form completely. When AI agents become the intermediaries between users and services, advertising strategies will inevitably shift—no longer just to attract attention, but to optimize content for machines to read. Brand owners will gradually realize that instead of putting effort into traditional creative work, it's better to figure out how to make their messages more easily "selected" at the agent level. The entire business logic will be reshuffled.

Fibre represents a significant shift in how blockchain infrastructure handles data throughput. Celestia's parallel data availability layer fundamentally changes the economics of blockspace by eliminating artificial scarcity constraints.
What makes this compelling is the real-world applicability. High-frequency micropayments become feasible without settlement delays. Attention markets can operate with minimal latency overhead. Agentic transactions gain the speed they demand. Even traditional asset trading finds new possibilities through onchain order books that finally have the bandwidth to com

There are actually not many developers using Codex, and many people haven't experienced what true vibe coding feels like. When GPT-5.2 (OpenCode/Cursor integrated version) and 5.2-Codex version are compared, it becomes clear that these two are entirely different in logic.
The general version of 5.2 has a fatal flaw—verbose and full of boastfulness, claiming the top spot among all OpenCode models. Honestly, that style is like the most annoying colleague.
But 5.2-Codex is specifically optimized for code completion, with professionalism dialed up to the max. Except for the occasional套路句式 like "Wo

A Bitcoin user was ultimately caught by a seemingly clever idea. He transferred funds to a wallet address, and surprisingly, the private key for that address was generated from a certain block's coinbase transaction ID. It sounds unbelievable, but that's the core issue — on the chain, everything is transparent, and anyone can derive it.
What happened next? An army of bots sprang into action. These automated scripts are searching for such low-hanging fruit — wallets generated with predictable private keys. They can easily infiltrate these addresses and quickly transfer the funds. The whole proc

**Why Solana's Design Makes the Difference**
Solana isn't just another blockchain—it's built on a fundamentally different architecture that matters.
Here's the key thing: every token in your wallet gets its own unique address. Not just one address per wallet. Each token has one. Sounds odd? It's actually genius. This design choice does one critical job—it lets transactions run in parallel instead of standing in line.
Think of it this way: your Solana wallet is like a building address. But inside that building, each token has its own apartment with its own entry point. Because tokens aren't com

Ever wondered why proof verification on Bitcoin sounds great in theory but turns into a nightmare when you actually try it?
Here's the problem most BitVM-style approaches run into: they nail the on-chain efficiency, but then the off-chain burden becomes this massive bottleneck. You save gas, but you're drowning in computation elsewhere.
That's where things get interesting. There's a new approach quietly shifting the paradigm—it doesn't just tweak the math, it fundamentally rethinks where the weight sits. The dispute resolution stays lean (we're talking BitVM3-level costs), but the whole system