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Are We Automating the Wrong Things?
I went back to my hometown McDonald's last week. It made me rethink how I talk about AI. I grew up in this town. I know this McDonald's. And last week I walked in and it was gutted — no cash registers, no one up front. Just a row of digital kiosks. The actual workers were pushed back into the kitchen, tucked behind a corner where you could barely see them. Then they forgot one of my fries. Before, that's a 10-second fix. Walk up to the counter, say something, done. Instead, I had to walk behind the counter, into the kitchen, and try to flag someone down while everyone back there is slammed. I felt like I was doing something wrong just by being there. A problem that used to take zero effort to solve now takes effort, awkwardness, and a little bit of guilt. That's not AI making my life easier. That's AI making my life harder so a company can save on labor. And I think that distinction matters a lot. Here's where I land on all of this — I'd call myself a realistic optimist, or a cautious optimist. I'm genuinely bullish on where this technology goes. I think AI has the potential to free up a massive amount of our time — time we could spend picking up new hobbies, sharpening skills, learning things we never had bandwidth for, and actually showing up for our communities instead of being buried in busywork. I use it every day to think out loud and organize my own head. That part's real, and it's good. But I'm also watching it get implemented in ways I don't agree with, right now, not hypothetically. The McDonald's kiosk is a small example of a bigger pattern: technology getting rolled out to cut cost or friction for the business, at the direct expense of friction for the human on the other side of it. We should be way more intentional about that trade-off than we currently are. The other thing I'm protective of: our ability to think for ourselves. AI is an incredible tool for brain-dumping, organizing, drafting — I lean on it constantly. But there's a real difference between using it to support my thinking and letting it start replacing my thinking. That line is worth guarding, especially as it gets easier to just let the model decide.
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🚀 New video: the exact system I use to build and sell voice AI agents
Local businesses miss calls every single day, and every missed call is money out the door. This video breaks down the exact system I use to build, demo, and sell AI receptionists that catch those calls and pay me recurring monthly income. The whole thing runs on two tools: - Trillet AI to host and white-label the agent - Claude Code to build and configure everything for you You slap your name on it, connect your Stripe, and keep the monthly revenue. What's inside: - Why local businesses desperately need this - Building a personalized demo in 5 minutes from just a website URL - White-labeling so your client never sees the platform - Sub-accounts, onboarding, and invoicing - Letting Claude Code do the heavy lifting on the build - Knowledge base, voice, fallbacks, and SMS booking setup - Getting a phone number connected - The sales math that closes deals on the call - The full 7-step process from demo to live One 5-minute demo can turn into monthly passive income. Once you see it as a repeatable process, you just run it over and over. Drop questions below 👇
Do you love Anime, Sushi and Manga of Japan? Haha ❤️🍣🤣
First of all, I would like to thank the admin for establishing this community. I plan to make frequent use of it. I am not here to sell or promote anything. I am here to connect with meaningful people and contribute to this community. I would be truly disappointed if I were misunderstood. To briefly introduce myself, I’m an entrepreneur currently based in Tokyo, Japan. I am running my business here while working closely with Japanese clients and leading my devs. And also an experienced engineer myself We are currently working on a wide range of developments, including: • AI and machine learning systems • LLM applications, RAG systems, AI agents, and intelligent search • AI-powered customer support and business automation • SaaS platforms and subscription-based products • Custom CRM, ERP, and internal business systems • Web applications and company platforms • Mobile applications for iOS and Android • Backend systems, APIs, databases, and cloud infrastructure • Real-time platforms, dashboards, admin panels, and analytics systems • Workflow automation and integrations between existing business tools • Booking, reservation, payment, messaging, and notification systems • Marketplace and matching platforms • Logistics, dispatch, location tracking, and map-based applications • E-commerce and customer management solutions • Healthcare, education, hospitality, finance, logistics, and other industry-specific systems • Modernization of older systems and migration to new web/cloud architectures • Product MVP development through to production-ready systems and continued scaling At the moment, I also have a clear idea and vision for building something much bigger. If anyone here is currently running a company or actively doing business in the US or Europe, I’d be glad to connect and have a conversation. I would like to discuss my vision and ideas with a long-term partner. Thanks for reading this.
Why trying to build and sell AI agency solutions without a system leaves your pipeline stuck in the research phase
Trying to transition into running an AI automation agency, building AI agents and receptionists, and landing your first paying clients while letting your Claude Code workflows, client outreach notes, and service templates get scattered across random chat logs and loose text files is an absolute roadblock. When you're trying to learn how to package and sell AI solutions without a centralized setup, letting your project files and prospect tracking get buried across a chaotic maze of open browser tabs and phone memos makes consistent execution nearly impossible. Scaling your automation agency means ditching the digital clutter and anchoring your workflows into a clean, systematic framework. Instead of juggling random notes, I now rely on a centralized Notion and spreadsheet ecosystem to track my agency building milestones, client pipeline trackers, and prompt vaults without the mental noise, paired with tool integration links like claude.ai and canva.com to support my operational stack. Whenever I need to break down a tricky client workflow or structure a new outreach sequence—like designing a step-by-step prompt framework for pitching local business automation—I drop my rough thoughts into floment.ai and instantly get three targeted variation options and execution guides in seconds flat. What specific automation hurdles or client acquisition problems are you solving inside the academy right now? Let's discuss in the comments below!
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A engineer from Tokyo is currently writing this message.🙆‍♂️
First, big thanks to the ADMIN for building this community. Really appreciate the work behind it. Happy to be here, and happy to contribute where I can. Most of my work is with global clients, usually founders or companies building something with a real vision behind it. Not really looking for one-off tasks only. I prefer working with people who want to build, improve, launch, and keep growing a product over time. I’m based in Tokyo, Japan and work mainly across AI, full-stack development, SaaS, automation, mobile apps, and product development. I also have access to active development teams and individual engineers here in Japan. So depending on the project, can support either a specific technical area or a full development process. - Main areas I work in: • AI agents and multi-agent systems • LLM apps, RAG, AI search, knowledge systems • Business automation and internal AI tools • SaaS platforms • Web applications • Mobile apps • CRM and booking systems • Marketplace and matching platforms • Logistics and dispatch systems • GIS and location-based apps • AI customer support systems • Data processing and analytics • Recommendation systems • API integrations • Cloud infrastructure and scaling - Typical tech stack: Frontend React, Next.js, TypeScript, JavaScript, Tailwind Backend Python, FastAPI, Node.js, Express, Golang, REST, GraphQL, gRPC AI / ML PyTorch, TensorFlow, Hugging Face, LLMs, RAG, vector databases, AI agents, NLP, computer vision Mobile React Native, Flutter, Swift, Kotlin Database PostgreSQL, MySQL, MongoDB, Redis, Pinecone, FAISS, Elasticsearch Cloud / DevOps AWS, GCP, Azure, Docker, Kubernetes, CI/CD, GPU systems - Have worked across quite a few industries too. Healthcare, logistics, hospitality, education, finance, e-commerce, media, marketplaces, SaaS, customer support, field services, and more. - I can also help with: • Product planning • Technical architecture • MVP development • Production development • AI product strategy • Workflow design
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