Every other day someone announces an AI agents course. So why am I building one?
Because most of them stop at "build an agent that summarizes Wikipedia." That's not useful. You can't pay rent with that.
I'm building a course where every agent earns money or saves time. Three capstone projects:
Crypto News Agent — monitors Twitter / Reddit / news sources, sentiment-scores the data, and opens / closes positions via Binance API with stop-loss protection.
Freelance Hunter Agent — parses Upwork / Fiverr, scores leads by ICP fit, generates personalized proposals, submits them. Catches jobs human applicants miss.
Code Assistant Agent — local-first dev pair-programmer. No cloud, no data leak. Works on your machine, runs your tests, suggests fixes.
If your AI agent doesn't change a number on a balance sheet (yours or someone else's), it's a tech demo, not a product.
Why now
LangChain matured. Claude / GPT-4 / Gemini got cheap enough to call 100x in a workflow. People stopped being scared of "API costs." The infra is finally cheap enough to do things, not just talk about doing them.
What's different
Other courses: read theory → build toy agent → move on.
This course: open a real problem you have → build the agent → deploy → measure dollars saved / earned. 25 hours. 10 modules. $599 single payment (founder's pricing — first 50 customers locked in).
Launching at https://nexus-bot.pro/ai-agents in ~7 days. If you're already a NEXUS course student — cross-sell email with discount coming.
Question for you: what's the most expensive recurring task in your week right now? I'm collecting "agent ideas worth automating" — drop yours in comments and I might include it as a bonus module.
— Stas, GuardLabs
📥 Free chapter — 20 no-budget growth tactics
This launch log runs on a playbook. If you want the actual tactics — Google-ecosystem hacks, trend-jacking, the HARO authority play — grab two free sections of the Blueprint. No PDF wall, no login: it opens in your browser. Real numbers, real code, no fluff.
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