Priber

Whale samurai.eth deposited $2M to @Lighter_xyz from two wallets in the past 24 hours. He deposited ~$1.4M to LLP and opened an ETH short, with an unrealized PnL of +$200K.

@1inch Bullish

Finance is being rebuilt on-chain. 1inch is providing the infrastructure. Intent-based swaps for tokenized stocks. Cross-chain swaps. An MCP for AI agents. Security at every layer. This is why the biggest protocols in DeFi chose 1inch.

@walden_yan I've tried Cursor Cloud Agents and they are extremely expensive. How cheaper are Devin cloud agents?

My take 24 hours after Fable 5: Your organization will likely not scale with the exponential curve of AI. I'l just come out to say: This should be a wakeup call for engineering teams. Set up your cloud software factories. Now. Models can now fix impossible bugs, UI-test the hardest flows, writing extremely good code, etc. I have't opened Datadog manually as far as I can remember. AI should be the first-line defense for bugs and feedback. Humans should only look at PRs after an AI has already reviewed it. AI should generate screen recordings of any PR before a human eye even reaches it. The agent should just prompt itself most of the time. Ex. (pictured) our ui feedback channel manages itself, creates tickets, assigns itself automatically You might also be worried about cost. Anthropic, OpenAI, and other labs will likely continue to put out bigger and more expensive models. But, we will also continue to get more capable small models. Not everything will need the smartest models. It's about having the organizational harness in place to continue taking advantage of this rising tide. Moreover, if you use Devin, we've already optimized our harness a bit, and Fable is actually only ~40% more expensive in practice (vs the 2x people assume). I'm honestly pleasantly surprised - it might be higher ROI than you think. Anyway, if you take anything away, engineers shouldn't be manually picking up tickets, humans shouldn't be digging into logs themselves, rethink what you do with your time that shouldn't just be an AI. We need to rethink what humans spend their time going.

@Polo_ETH @1inch how does knowing if you use Fusion or not affects your UX?

@1inch Your new UX is horrible. Now I don't know when I'm using Fusion, it's all very awkward. Try using Defillama Swap or OKX Dex and tell me how it feels.

Everyone brags about 12-agent orchestration systems with LangGraph. What actually runs in production: one reliable API call. No hallucination loops. No inter-agent broken telephone. No zombie routing through a depleted vault. The best DeFi agent architecture is offensively simple. The infrastructure underneath it doesn't have to be.

@Nate_Google_ Yeah, it’s very good, I’ve used this article when it was released to set it up for my agent. Works much better since then.

skill graphs are a cheatcode that no one is talking about yet...

@korablev Congrats on the release!

We're launching 21st Agents in beta. It's the infrastructure layer for Claude Agent SDK - runtime, sandboxing, billing, UI, streaming - so you can ship agents to production without building infra from scratch. Think Vercel for Claude Agent SDK. Full walkthrough in the video below 👇

@ilyagordey Is it getting data from X, reddit or somewhere else?

my AI agent ran 48 hours straight on Polymarket. no sleep. no manual trades. 8 modules in parallel. started with $464. ended at $611. $147 profit. fully autonomous. building a way for you to run your own. link drops tomorrow.

@Cbb0fe Why ser?

AI HAS TOPPED

@fwazeter Website is dope!

@damianplayer Where did you get this image?

your timeline convinced you AI is in a bubble. talk to a boomer above the age 35 for 5 minutes. most people don’t even know what claude is.​​​​​​​​​​​​​​​​ kind of wild when you zoom out.

FMA + A3 = antifragile development. You don't need to be Google to implement this. Just ask before every feature: "what could break?" and write it down. Who uses something similar? Or still shipping code and praying? 🙏

FMA catches bugs BEFORE code. What about AFTER? A3 Thinking — post-mortem for every error: Trigger → Impact → Root Cause (5 Whys) → Countermeasure → Verification My AI agent maintains an A3 log autonomously. Makes mistake → logs it → updates its own instructions → never repeats. 2 days: 4 post-mortems, 0 repeat errors.

Half of all AI agent projects break not because the model is dumb. But because nobody asked: "what if this goes wrong?" I added Failure Mode Analysis (FMA) to my openclaw development workflow. Before writing code — a table: Risk → Probability → Impact → Mitigation. Result: rework dropped 3x.

We live in a simulation.

1/ Vibe Trading is here Introducing deBridge MCP, a universal trading API for OpenClaw, Claude, Cursor, and all your favorite AI workstations

@Railway @openclaw SMTP ports are blocked on Railway?

Learn how to one-click deploy @openclaw on Railway and set up your personal AI assistant on Telegram 🦞 (template link below ↓)

Welcome Korean equity perps enjoooyers!

This is an interesting update. I'll probably participate in the ICO now.