Hi there! 👋 I'm looking to connect with reliable, US-based professionals who are interested in exploring AI training opportunities and building long-term professional collaborations. I have experience across several AI training platforms, including Outlier, DataAnnotation, Snorkel AI, Alignerr, and AfterQuery. I'm familiar with project qualification, task workflows, quality standards, and the different types of opportunities available. 💡 Explore AI Training Opportunities 🔹 Outlier — AI evaluation, coding, mathematics, and specialized reasoning tasks. 🔹 DataAnnotation — Flexible AI training projects involving writing, coding, and advanced reasoning. 🔹 Snorkel AI — Expert-driven projects across technical and specialized professional fields. 🔹 Alignerr — AI training opportunities matched to contributors' skills and professional backgrounds. 🔹 AfterQuery — Expert-written and reviewed data to help improve AI models. 💰 Compensation varies depending on the platform, project, qualifications, and demand. Contributors with strong technical skills or specialized expertise may qualify for higher-paying projects. 🤝 What I'm Looking to Build I'm interested in building a network of dependable professionals who want to explore these opportunities and establish mutually beneficial, long-term working relationships. Depending on each platform's policies, I can share general guidance on: ✅ Qualification processes and project selection ✅ Task workflows and quality expectations ✅ Understanding different project types ✅ Exploring opportunities that match your expertise ✅ Establishing clear responsibilities and compensation arrangements Each contributor would maintain control of their own account and complete their work independently, in accordance with the applicable platform rules. 🎯 Who Might Be a Good Fit? I'm especially interested in connecting with US-based professionals with backgrounds in: 💻 Software Engineering & Programming 📊 Data Science & Analytics 🧮 Mathematics & Advanced Reasoning

📝 SUMMARY This week's call was a wide-ranging mix of infrastructure talk, business updates, and honest discussion about what it actually takes to scale AI usage. Members swapped notes on managing multiple AI subscriptions and their costs, Patrick Chouinard walked through leading a large enterprise Claude rollout at a Canadian financial institution (including the token-economy culture shift and employee confusion between models and "harnesses"), and Ty Wells shared progress on his Island Flow ERP/accounting product for Bahamas businesses plus a demo of a redesigned T3 interface with draggable widgets. Juan Torres reported on deploying his AI photo booth at a high school homecoming — Wi-Fi interference near a military base included — and the feedback that he needs a proper landing page to attract institutional clients. The group also dug into technical territory: Patrick's NTFY-based secure push-notification setup tied to Tailscale, his "AOE" (Agent Operated Environment) project, Ty's multi-machine Proxmox setup, and ChatGPT's "Dots" feature. A recurring theme throughout: the gap between AI power users running multi-agent setups and "normies" just getting started, and how to navigate the cost, confusion, and adoption challenges in between. 💡 KEY INSIGHTS Ty Wells (business owner) frames his ~$2,000/month in AI subscriptions as cheaper than hiring "a senior software architect, engineer, QA tester," justifying heavy usage. Brandon Hancock noted that after Codex's usage limits were cut in half, the subscription "isn't that good anymore," and he has been timing resets to maximize usage. Patrick Chouinard described enterprise Claude rollout dynamics: personal AI subscriptions are blocked entirely at his financial-institution client due to data privacy/audit requirements — all usage must go through the company tenant. Patrick observed a cultural shift at that client: employees used to negotiate over return-to-office days; now the key negotiating point is "which model can we access," with people requesting more tokens instead of overtime or pay.