Buying a Hostinger Subscription
Place this where the course discusses choosing a host and making the first hosting purchase.
Three levels. Nine modules. Twenty-six lessons. By the end, Sofia — our running protagonist — has her own AI running on her own hardware, wired to her own messenger, and shipping work while she sleeps. This is what that journey looks like, top to bottom.
Outcome: OpenClaw is installed on the right hardware, wired to the right model, running Sofia’s first automation. 9 lessons · ~95 min.
Understands what it is, why it matters, where it fits alongside ChatGPT, Claude Cowork, and the browser assistants she already uses.
Explain what OpenClaw is and how it differs from ChatGPT, Claude.ai, and Cowork using the “three rooms of AI” framework (browser room, desktop room, pocket room).
Key takeawayOpenClaw isn’t a chatbot — it’s an AI that lives on your devices and speaks through your apps.
Evaluate whether local-first AI fits your privacy and workflow needs using a 5-question decision framework, and understand why Anthropic cut subscription access on April 4, 2026.
Key takeawayLocal-first trades a little convenience for a lot of control.
Analyze which tool to reach for in five common work scenarios using the tool-choice decision matrix.
Key takeawayDifferent AIs for different rooms — OpenClaw is the one you keep in your pocket.
OpenClaw running with the right hardware and the right model combo — decisions made before code runs.
Evaluate four hosting options (laptop / Mac Mini / Raspberry Pi / VPS) against four criteria (always-on, privacy, cost, local-model capable) and choose the right one.
Key takeawayIf it needs to run while you sleep, it can’t live on a laptop that sleeps.
Place this where the course discusses choosing a host and making the first hosting purchase.
Evaluate the three model options (cloud API / competitor API / local Ollama) and choose the right primary model for a working professional’s use case, given the April 4, 2026 subscription cutoff.
Key takeawayThe best model is rarely the biggest — it’s the one matched to your job, your wallet, and your privacy.
Use here when the lesson explains subscription-based model access and when it is the right choice.
Install OpenClaw on your chosen hardware using Docker and verify the gateway is running using openclaw doctor --deep --yes.
Key takeawayInstalling OpenClaw is closer to installing Slack than to compiling code — if doctor is green, you’re in.
Use before or during install so the gateway, channels, tools, and models have a concrete mental model.
Place this directly in the deployment/install sequence after the hosting decision has been made.
Send your first three requests to OpenClaw via Telegram and evaluate the quality of each against a simple rubric (correct, useful, context-aware).
Key takeawayYour first OpenClaw session should ship a real output, not introduce itself.
Use when Sofia moves from setup into the first real phone-based OpenClaw interaction.
First automation live and daily rhythm set. Sofia’s phone buzzes Sunday night with next week’s plan — built by her, running without her.
Write requests in the messaging-short style that gets better OpenClaw responses than full-paragraph prompts.
Key takeawayOpenClaw lives in your messaging app — write for it like you’d write to a human there.
Use where the course teaches concrete command phrasing and screen-led interaction patterns.
Design and ship a simple weekend-briefing automation (triggers Sunday 6 PM, summarizes next week from calendar, sends to Signal).
Key takeawayA working L1 automation is the moment OpenClaw becomes yours — not a toy, a tool.
Outcome: Memory, skills, TaskFlows, Canvas, voice, messaging, Tailscale — all working together in Sofia’s real workflow. 9 lessons · ~110 min.
Custom skill plus memory-wiki knowledge base running. Sofia’s agent stops being a stranger every morning.
Configure OpenClaw’s memory system AND the new memory-wiki (April 2026) to persist facts and documents across sessions using the three memory types (user, project, feedback).
Key takeawayA memory-less AI is a stranger every morning. Give yours a notebook AND a filing cabinet.
Use OpenClaw’s session branching feature to fork a conversation mid-flow, try an alternate path, and merge or abandon.
Key takeawayThe best prompt is often the second attempt — branching lets you have both.
Install a pre-built skill from ClawHub AND author a simple SKILL.md file that teaches OpenClaw to draft Sofia’s Monday standup in her team’s exact format.
Key takeawayA skill is just a markdown file with instructions — if you can write an email, you can write a skill.
Use when the course introduces reusable instructions, workspace context, and the files that shape agent behavior.
Cron plus TaskFlows plus Canvas plus Voice. Sofia’s production automation stack is live.
Configure a cron job that runs the weekly-recap skill every Monday at 8:30 AM and sends the output to Signal.
Key takeawayCron turns OpenClaw from reactive to proactive.
Build a TaskFlow that triggers when a specific Gmail arrives (e.g., from your manager) and executes a multi-step chain: summarize, draft reply, notify in Signal.
Key takeawayTaskFlows connect OpenClaw to the moments that actually matter in your day.
Use OpenClaw’s live Canvas to review agent actions in real time, and enable on-device voice mode (April 2026 MLX feature on Apple Silicon) for hands-free sessions.
Key takeawayNever let an agent act without a window you can watch it through.
Messaging plus connectors plus Tailscale remote access. Sofia talks to her Mac Mini from a Lisbon café — no open ports.
Connect OpenClaw to your primary messaging app(s), set up channel routing so work and personal agents stay separated, AND add an Apple Shortcuts trigger for one-tap home-screen actions.
Key takeawayOne agent, many channels — but give each channel a clear job.
Configure OpenClaw’s MCP connectors for Google Calendar, Gmail, and Slack to feed real context into your automations.
Key takeawayAn AI without your context is a generic chatbot. Give yours the keys to your stack.
Configure Tailscale to expose your OpenClaw gateway to your own devices (and ONLY your own devices) without opening any ports to the public internet.
Key takeawayYour agent should only be reachable by you — Tailnet makes that effortless.
Outcome: Sofia runs a multi-agent team, routes smart, runs local when needed, and knows OpenClaw’s limits cold. 8 lessons · ~110 min.
Multi-agent team running via Paperclip. Sofia’s role shifts from operator to CEO.
Analyze three real ClawHub skills to identify the four reusable design patterns (linear, branching, verification, delegation) and pick the right one for a new task.
Key takeawayThe best skills aren’t the longest — they’re the ones that match the shape of the job.
Build a blocker-detector skill that reads Slack, identifies real blockers, filters noise, and pings only on true positives — handling three common failure modes.
Key takeawayProduction skills get the filter right — the goal isn’t to ping more, it’s to ping better.
Orchestrate a main agent plus research sub-agent pair using OpenClaw’s updated sub-agent config — nested agents no longer block each other.
Key takeawaySub-agents let you decompose problems the way real teams do.
Use at the point where the course shifts from one agent doing work to a coordinated set of agents.
Layer Paperclip on top of multiple OpenClaw agents to create an org chart, assign budgets, set goals, and track cross-agent work in one dashboard.
Key takeawayOpenClaw gives you employees. Paperclip gives you a company.
Cost-optimized routing plus local fallback. Right model, right job, every time.
Configure OpenClaw’s router to send simple tasks to cheap models, complex tasks to flagship models, and private tasks to a local model — optimizing for cost, speed, and privacy.
Key takeawayThe best model is rarely the biggest — it’s the one matched to the job’s shape.
Install Ollama plus a local model and wire it to OpenClaw for tasks that must never leave your device.
Key takeawayLocal models are your “never leaves the house” option — not your default.
Full governance policy plus kill switches live. Sofia knows when to trust her agent and when not to.
Evaluate OpenClaw’s six most common failure modes (hallucination, stale memory, wrong-tool, silent cron failure, leaked context, prompt injection) using real incident logs and design a guardrail for each.
Key takeawayThe question isn’t whether your agent will fail — it’s whether you’ll notice when it does.
Use inside the failure-mode section where adversarial instructions and tool misuse become concrete.
Design a personal-use governance policy for OpenClaw covering data residency, key management, audit logs, rotation schedule, and a tested “kill switch” procedure.
Key takeawayThe day you need a kill switch is too late to design one — write it while nothing’s wrong.
Use where the course turns privacy, permissions, secrets, logs, and governance into operating rules.
How the course balances freshness, cognitive depth, and production status — the shape of what you’re shipping.
• 1 cheat sheet (PDF) — 9 total
• 1 Gamma deck per lesson — 26 total
• 1 demo script for L2+L3 modules — 6 total
• 1 knowledge check per module — 9 total
• Sofia’s sample data pack — 1 living asset folder
Sofia is the protagonist threading every lesson. She’s a working professional with a MacBook Air, €600 to spend on this, and no terminal experience before Module 1.
By the end of Level 1, she has OpenClaw installed on a Mac Mini, her first Monday-morning digest running automatically, and a Signal bot that writes better than she does on a bad day.
By the end of Level 3, she runs a 3-agent mini-company coordinated by Paperclip, with a governance policy, tested kill switch, and monthly key rotations on her calendar. The arc earns every lesson — no skipped beats.