Been working with software systems for more than 10 years, mostly around backend, cloud, AI, automation, and product development. One thing I’ve learned, knowing a programming language alone usually isn’t enough. The harder part is understanding the actual business. How to automate work that’s still manual. Connect systems that don’t work well together. Build AI into real workflows. Keep the backend stable when usage grows. Deal with data scattered across different tools. These are the kinds of problems I’ve spent a lot of time working on here in Japan. But I’m curious about the US side. For people running companies in the US, what technical skills are becoming difficult to find? And what skills do you think companies will need more of over the next few years?

I am an entrepreneur and a tech professional. Been working with software systems for quite a while, and one pattern comes up a lot. The first version works fine. Then customers grow, operations get bigger, and little technical problems start showing up everywhere. Too many manual steps. APIs that don’t talk properly. Slow backend. Data sitting in different places. AI added, but not really connected to the actual workflow. Usually not one huge problem. More like five small ones quietly costing time every day. For those running a company now, what’s becoming harder on the technical side as you grow?

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. 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. - 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

Every Stead install raises five workspaces, each with an agent team and a pack of skills. This is the honest inventory. It gets updated as releases land, so what you read here is what actually ships. The packs (ship with the product, free, MIT) - Career: 19 skills, a coach plus 3 specialists (comp and negotiation, advancement, interview and brand). Knowledge layers for leveling, comp benchmarking, negotiation, promo mechanics, interviews, and resumes, plus the action skills that use them. - Finance: 27 skills, a candid advisor plus 3 specialists (tax analyst, portfolio realist, cash-flow mechanic). Under it: a deterministic tax engine (US federal and state, Canada federal and province, 172 tests, every rule cited) and a retirement projection engine. - Health: 18 skills, a health lead plus 3 specialists (lab reader, training-and-fuel coach, mind clinician). Accredited knowledge layers fenced by a clinical conduct floor and a board that convenes before any diagnosis-shaped answer stands. - Personal: 16 skills, a trusted counsel plus 3 specialists (relationships, direction, practical manager). Cold-starts from your own exported contacts and calendar, presuming nothing. - Projects: 19 skills, an incubator plus 3 specialists (research scout, reality-check, execution PM). Ideas run spark to graduate, with a tested plan engine (critical path, PERT estimates) convened when something gets real. That is 99 skills and 20 agents in the five starter packs. Every pack is scanned with an independent security scanner (NVIDIA SkillSpector) before release; the current scan is zero findings across all five packs. The repo is public, so you can run the scan yourself. The seed packs (new: graduation staffs the workspace it creates) When a project graduates out of the incubator, its type draws a practitioner team from a seed pack. Seeds ride along in every install and are never raised at setup; they wake when a project earns its own workspace. - Software product: 7 skills, 5 agents. An architect-led product team (full-stack, cloud and AI, marketing, customer acquisition) standing on an engineering conduct floor.