AI Superpower: Build the Agent Project That Gets You Hired — or Funded
Nathan Wang
18 AI Products · 50,000+ Students
Ship the agent project that gets you hired as an FDE — or funds your startup.
Forward Deployed Engineer is the hottest job in AI. Postings are up ~800%, and OpenAI and Anthropic pay $350–550K. The problem: everyone applying has the same resume. What gets the callback is a shipped agentic project — and almost nobody has one.
This course gets you that project. In 3 weeks you’ll use ClawBot to stand up your agent crew in week one, learn the design principles behind AgentOS — the system that powers it, more advanced than OpenClaw or Hermes — and build your own product on top of it. No reinventing the wheel: you spend your three weeks on the proof, not the plumbing.
That single artifact opens two doors. It’s the proof-of-work that gets you hired as an FDE — and the foundation that gets you funded as a one-person company (OPC).
This isn’t a tutorial. The same AgentOS powers 18 products on ai-nate.com and my own OPC operations today — ~1B tokens/day in real production use. You don’t just build a thing; you learn how agentic systems are architected, which is exactly what an FDE interview screens for.
One build. Two doors. Hired or funded.
What you’ll learn
Build one real agent product on ClawBot + AgentOS — the proof that gets you hired as an FDE, or the foundation that gets you funded.
Use ClawBot to spin up a working multi-agent crew in week one — running real tasks for your product immediately.
No environment rabbit holes: skip the weeks of setup and start where most tutorials end.
Live on web + mobile from day one.
Go under the hood of the system that powers ClawBot — more advanced than OpenClaw or Hermes: memory, skills, tools, orchestration.
Understand how agentic systems are architected — exactly what an FDE technical screen tests for.
Design principles taught directly by the person who built the system.
Ship a real multi-agent product to your own domain — not a demo, not a toy.
Build on a production-grade foundation instead of reinventing the wheel — spend your 3 weeks on the proof, not the plumbing.
Own your code, data, and deployment.
Package your build as the portfolio proof-of-work FDE interviewers ask for — the project almost no other applicant has.
Forward Deployed Engineer postings are up ~800%; OpenAI and Anthropic pay $350–550K.
Turn a generic resume into a callback.
The same stack that lands the offer is the seed of your one-person company (OPC).
Scale it into a funded product when you’re ready — the architecture already supports it.
Built on the system running 18 products at ~1B tokens/day today.
Learn directly from Nathan
Nathan Wang
30+ AI Agents Running 24/7 | 18 Products | PhD Engineer/TPM @ Apple & Meta
Who this course is for
Job Seekers Targeting FDE & AI Roles
Land the hottest job in AI. Ship the agentic project that gets you the interview.
Engineers & PMs Leveling Up
You can already build. Now learn how agent systems are architected — and prove you operate at that level.
Aspiring Founders & OPCs
Turn your build into a one-person company — the seed of a funded product when you’re ready.
What's included
Live sessions
Learn directly from Nathan Wang in a real-time, interactive format.
The OPC Stack Starter
ClawBot configured + AgentOS workspace + your first 3 specialist agents pre-wired. The foundation of a one-person company — same architecture behind 18 shipped products and one full agent operated OPC.
Foundation modules included
New to agents? You'll get the Cohort 1 and 2 self-paced foundation modules to work through before live sessions — so you start at zero, not behind. Single-agent fundamentals, step by step.
The 18-Product Operating Cadence
Nathan's system for shipping in parallel. Idea → live AI product in 7 days, then 18 products in 18 weeks. The Founder Console workflow: One Pipe, Memory & Skills, The Crew.
AI Prompt & Architecture Library
Battle-tested prompts for memory, agents, and AI coding - the same library behind 18 shipped products.
Certificate of completion
Prove you can build and deploy production AI agent systems. Share on LinkedIn or with your employer.
Lifetime access
Every recording, template, and resource - yours forever. Revisit as AI tools evolve and your agent army grows.
Private operator community
A Slack group of fellow OPCs-in-training. Get feedback, share wins, and find collaborators for your agent crew.
Free ClawBot Subscription During the Cohort
Full ClawBot access for the entire cohort — a $200 value, included free. Build and run your agent crew on the same platform that powers 18 live products.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
4 live sessions • 34 lessons • 7 projects
Week 1
🏗️ Module 1.1: The OPC Operating Model — Operator → Crew → Channels
🧠 Module 1.2: AgentOS Primitives — Memory, Skills, Tools, Sandbox
👨🏻💻 Project: Configure ClawBot + Hire Your First Agent
📚 Bonus: The Digital Restaurant Architecture (Cohort 1–2)
📚 Bonus: Environment Setup — The Boring Stuff (Cohort 1–2)
📚 Bonus: Project 1 — One-Pager Blueprint (Cohort 1–2)
📚 Bonus: Project 2 — Build Your Landing Page (Cohort 1–2)
Jun
13
Optional: Week 1 Q&A Session
Jun
13
Live Session 1: The OPC Operating Model + AgentOS Primitives
📚 Bonus: Live Session 1 Materials — Foundation & API Waiter
📚 Bonus: Project 3 — Frontend & Backend Build (Cohort 1–2)
Week 2
👥 Module 2: Designing Your Specialist Crew + Approval Gates
👨🏻💻 Project: Wire Your 3-Agent Crew (Publisher / Researcher / Support)
📚 Bonus: LangChain Setup — The Kitchen (Cohort 1–2)
Jun
20
Live Session 2: Designing Your Specialist Crew + Approval Gates
📚 Bonus: Live Session 2 Materials — Designing the Brain
📚 Bonus: Project 4 — AI Agents Intelligence (Cohort 1–2)
📚 Bonus: Reading — ReAct Paper (Reasoning + Acting in LLMs)
Free resource
Build a 5-Agent Crew in 30 Min with ClawBot + AgentOS
Install ClawBot + AgentOS — your crew runtime in 5 min
Sign in on web + mobile, install AgentOS, and bring up your first agent. The runtime is the table — everything else stac
Configure 5 specialist agents with skills + memory
Spin up a researcher, a writer, a coder, a scheduler, and a publisher. Each gets its own skills, memory, and tools via A
Chat your crew into action from ClawBot web + mobile
Offer a concrete and concise explanation of how you will help students understand and apply this lesson.
Schedule
Live sessions
2 hrs / week
2-hour weekly live build. Short demos, guided implementation, Q&A. Leave each session with real features shipped - building toward your agent army.
Sat, Jun 13
2:00 AM—2:30 AM (UTC)
Sat, Jun 13
3:00 PM—5:00 PM (UTC)
Sat, Jun 20
3:00 PM—5:00 PM (UTC)
Sat, Jun 27
3:00 PM—5:00 PM (UTC)
Hands-on Project
2-4 hrs / week
Build your own AI agent: wire APIs, auth, memory, AI logic. By the end, your agent runs on your domain - the first soldier in your system.
Testimonials
I came into this with zero coding background—I was mostly 'vibe coding' and guessing my way through. I hit a few real hurdles, like wrestling with a login bug on a Sunday afternoon and dealing with data ambiguity (finding the right 'Bergen'!), but Nate’s step-by-step logic and analogies made the technical mechanisms finally click.
I went from feeling like a novice to actually building and deploying a functional weather intelligence platform that now automates data exports directly into our Azure Data Lake for demand planning. This course proved I don't need a CS degree to build serious, integrated tools for my job.
Student Showcase: GC Rieber Minerals Weather
Erik D.
Senior ERP and Technology ManagerI'm a Senior Machine Learning Engineer building GenAI applications and AI agents. I use Claude Code and Cursor daily - I thought I knew this space well. But Nathan's course completely shifted how I think about building AI products. It's not just about single agents - it's about designing agent operating systems where multiple agents share memory, learn over time, and grow with the user. Watching Nathan build 18 products in real-time and break down every architectural decision was unlike any course I've taken. It's such a pleasure to learn from someone who's actually doing this every day.
Yiyang Z.
Senior ML Engineer, Tech Incubator in Silicon Valley
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Frequently asked questions
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