#professorglitch
How to build an AI employee that works while you sleep. An AI agent is just a loop (goal → step → check → repeat) that can reach for tools. On its own it hits a wall: it forgets everything, waits for you, owns nothing. The ladder that turns it into staff: • ① context — files YOU write; it reads them every run so nothing's generic, and they grow (you're raising it) • ② memory — facts + your rules + how-to's; a skill is a memory • ③ a lane, not a task • ④ tools — MCP, ~1 min to connect • ⑤ a schedule — wakes on its own, pings you only for decisions • ⑥ guardrails — low-stakes it does; high-stakes it drafts and waits for your yes I run mine from a Google Sheet — it drafts every reply in my voice, I approve in 10 minutes, every 30 minutes it sends the approved ones and learns from my revisions. The moat: anyone can buy the same AI. Nobody has your context. Come build it with me. #aiemployee #aiagent #aiautomation #professorglitch
Professor Glitch536,400 просмотров • 3 месяцев назад
How to build a second brain that updates itself (like a librarian) How to build a second brain that updates itself: an AI knowledge base for your business that knows your clients, your prices and how you work, and keeps itself up to date every time you give it something new. The setup, in plain words: 1. One folder on your computer with two shelves: an inbox where you dump everything (call notes, emails, PDFs, voice memos, ideas) and the brain, with clean pages, one per client, project, pricing, and one about you. 2. One rules file that turns Claude into your librarian: never change an original, every fact points back to its source, mark old facts outdated instead of erasing them, and link everything related. 3. File it: drop a note in, and the AI updates every page it affects (often five or six) and links them back to the note. 4. When something changes, the brain updates itself. A client cuts their budget from $8,000 to $6,000 on a call: the client page, the timeline and the revenue page all update, and the old number stays, marked outdated, with the date and the source. 5. Ask it anything and it answers from your own pages, with the source. 6. Once a week, it checks the shelves: pages that disagree, facts that went stale, pages nothing links to. It's all plain text (markdown) files on your computer, and you own them. Open the folder in Obsidian to watch the connections grow. The whole job in four moves: you drop, it files, you ask, it checks. If you want to build yours, I teach it file by file, plus full courses from complete beginner to building real AI systems. Check my profile. #secondbrain #claude #aiagents #claudecode #professorglitch
Professor Glitch12,700 просмотров • 2 дней назад
Roadmap to build AI agent Team start to finish #aiagent #claude #professorglitch
Professor Glitch184,600 просмотров • 5 месяцев назад
How to build a team of AI employees — the full roadmap #aiagent ##aiautomation #professorglitch
Professor Glitch88,200 просмотров • 3 месяцев назад
If I had to learn AI automation from scratch in three months, here's exactly what I'd do, in order. Three months. October, November, December. Enough to go from nothing to AI employees doing real work, and to enter 2027 with a skill maybe one person in a thousand actually has. OCTOBER — two parts. Short one: the concepts you keep hearing and never quite get (model, context, automation, agent, employee, and the difference). Long one: get clear on what you actually want AI to do for you, map your system (what starts a job, what happens next, where somebody decides, where it ends), and make it ready: the files, the rules, the pieces written down. You can't hand off what you can't see. NOVEMBER — automation, then AI automation. Plain paths first (form → sheet, invoice → filed, reminder → sent). Then AI in the middle so the paths can read and decide: email in, AI works out what it is, drafts the reply, only the judgment calls reach you. One automation, then ten, then a hundred. DECEMBER — the team. Agents that loop until a whole job is done. The apps and tools your business needs, written by AI. Then the command center: AI employees, each with a job, context, memory, a schedule, and a gate so risky decisions wait for your yes. By New Year's Eve they work while you sleep and you approve instead of doing. #professorglitch #aiautomation #aiagent
Professor Glitch42,200 просмотров • 1 месяц назад
What to actually learn in AI right now — the 6-step ladder 🪜 You're probably learning AI in the wrong order — and it's quietly costing you months. There is a right order: six steps. Nail the sequence and three months from now you're in the one percent who actually build with AI; get it wrong and you spin forever on stuff that never connects. This is that order, free. And it's not theory — I've built with this every day for three years, ten billion tokens deep, and it's the exact path I teach my community; members ran it and automated almost their whole business. The ladder: The words. Learn the jargon — models, automation, agents — but fast. A few hours, just enough to know what each thing means so the practical clicks later. Most people get stuck here for months. Don't. Automation (no AI yet). Take something boring you do daily that needs zero brains — moving data, the same email, updating a sheet — and build it to run itself, end to end, on a schedule. This is the foundation the whole ladder stands on. AI automation. The same automation, now with a brain: the AI reads, decides, and handles the parts that take judgment. Still riding the automation underneath — which is why you build that first. AI agents. Autonomous now — give it a goal, it takes its own steps and loops until it's done. But you keep a hand on the wheel: high-stakes moves wait for your approval, so nothing goes rogue. Build with AI. Create tools and apps just by talking to an AI coding assistant. This won't teach you to code and you don't need it to — you just have to understand the shape of things: front-end, back-end, database, enough to steer. AI employees (the top rung). Go from building apps to running a team — real AI employees with their own skills and memory, your second brain and automations all in folders you own, scheduled and running themselves, doing the work you do every day. Three months of real focus — stretch it to four or five, no shame — and you're not just using AI, you're building with it. But you have to do the work, not just watch. #aiagent #learnai #aiautomation #professorglitch
Professor Glitch69,900 просмотров • 3 месяцев назад
The Complete AI & Automation Roadmap (Beginner → Expert) #professorglitch #aiautomation #airoadmap #aiagent #rag #learnai
Professor Glitch170,800 просмотров • 11 месяцев назад
Roadmap to your first AI employee #aiagents #claude #fabel5 #professorglitch
Professor Glitch69,100 просмотров • 4 месяцев назад
AI Automation + AI Agent RoadMap (Everything you need to learn) #aiagents #aiautomation #learnai #professorglitch
Professor Glitch69,200 просмотров • 4 месяцев назад
MCP explained and how to connect your AI to it #mcp #claude #professorglitch
Professor Glitch67,700 просмотров • 5 месяцев назад
What an AI agent actually is — watch one work. #aiagents #professorglitch
Professor Glitch36,000 просмотров • 2 месяцев назад
How to make multiple AI Assistant #aiassitant #aiagent #professorglitch
Professor Glitch51,300 просмотров • 6 месяцев назад