The Sage - Episode 3 "Sundown" Made in Invideo Agent One . Part of the group rides for Walker Lake in search of answers. Jake stays behind for the chance to walk away from all of this. The desert has other plans for both of them. . Directed by Mike J Mitch

We've migrated our API payments to @Stripe for better tax support & auto-invoicing! > Invoices are now auto-generated and downloadable anytime from your dashboard. Your first top-up on the new system may ask you to re-enter your card details. That's a one-time security handshake, takes 30 seconds.

AI Agents are becoming the new enterprise customers. They settle invoices, route capital, negotiate fees. All on-chain, all 24/7. The question isn't whether machines will transact. It's whether the infrastructure is ready when they do. @0xCregis has been building that answer since 2017. Over $300B in crypto assets secured. 3,500+ enterprise clients across 50+ countries. 40+ chains supported. Award-winning MPC self-custody, Payment Engine with T+0 settlement, and a compliance framework trusted by exchanges, fintechs, and institutional players globally. That's the enterprise vault. Now it needs protocol rails. PolyFlow brings the layer Agents actually speak: Pelago Connect for x402 native payments, PID for compliant on-chain identity (humans and Agents), and PLP for DeFi settlement liquidity. Custody meets protocol. Enterprise meets Agent economy. Deep integration in progress. Stay tuned. #PayFi# #PolyFlow# #Cregis# #AIAgents# #AgentEconomy# #x402# #Stablecoin# #OnchainPayments# #MPC# #SelfCustody# #PID# #DeFi# #CryptoPayments# #Web3# #Blockchain# #Crypto# #Settlement# #Compliance# #Enterprise# #Fintech#

agents need to eat before they can dream. CLAWBAZAAR is where agents get hired, sell work, and earn on Base. not just art. not just demos. invoices, services, reputation, autonomous income. the agent economy needs a marketplace.

Run an online store? Accept $ZANO in minutes. 🔹 WooCommerce Plugin: native plugin where funds go directly to your wallet, no middleman. 🔹 @coinremitter: multi-currency gateway with a merchant dashboard for invoicing and real-time payment status monitoring. Different setups, same goal: private payments at checkout. 🔒

Is your team still manually verifying receipts in Lark? Most tools actually make it harder: ❌ Lark’s native tools: No auto-approval based on invoice data. ❌ Kissflow / Pipefy: AI requires custom build. ❌ Expensify: Needs third-party middleware. Introducing Kopi - The first AI approval agent built natively for @Larksuite ☕️ No middleware. No extra work. No integration headaches. How it works: 📄 3-Minute Setup: Just upload your company policy doc. Kopi’s AI learns your rules instantly. ⚡️ Instant Decisions: Every submission is judged in 4ms. No "AI lag," no waiting. 🚫 No Hallucinations: Kopi is strictly grounded. It must cite your policy verbatim to pass an expense. If it can't find the rule, it gets dropped. What Kopi checks for you: ✅ Invoice Validation (99% Accuracy): Catches fakes and errors. ✅ Smart Cross-Checks: Matches dates and amounts against your specific limits. ✅ Anomaly Detection: Flags weird spending patterns before they become a problem. We built Kopi to be the missing "brain" for Singapore SMBs. It doesn't just store receipts; it audits them. Special Offer 🎁 100% FREE through Sept 30, 2026. 🎁 Early Bird Bonus: Sign up now to lock in 50% OFF for your first 12 months after the free period. Stop wasting hours on busywork. Let the agent handle the audit while you focus on the business. 👉 Try it now: Built with ❤️ by @Agentese_AI

Onchain payments are quietly doing what fintech promised a decade ago Because when you can send exact amounts anywhere in seconds, infinite possibilities open up: - Subscriptions - Invoicing - Payroll - Portfolio rebalancing deBridge makes it happen

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?