Build Trading Agents: Markets, AI Engineering, and Autonomous Systems
From Engineer to Trader-Architect
Learn trading, AI-native architecture, and how to put autonomous agents to work. Twelve weeks of labs you can start today.
What you use in the labs
Trade. Engineer. Automate.
Trading Fundamentals & Strategy
Learn trading psychology, technical analysis, options, and risk management. Leave with a mechanical plan you can actually follow.
AI Engineering & Orchestration
Build agents with LangChain, LangGraph, and MCP. Design multi-agent graphs, add memory, and run them on your machine.
Agents that trade on a schedule
Wire agents that read paper markets, place orders, and enforce your risk rules. ⚠️ Trading involves risk of loss.
How the 12 weeks work
Learn Trading Fundamentals & Setup
Learn trading psychology, technical analysis, and mechanical plans. Connect MCP tools, set up your environment, and pull your first market data.
Week 0Build AI Agents & Orchestration
Use LangChain and LangGraph to build trading agents. Generate signals, apply risk checks, and execute automatically.
Weeks 1-6Orchestrate and scale
Add LangGraph orchestration, data pipelines, and a second strategy. Finish with a paper-trading graph you can run on a schedule.
Weeks 7-12What You'll Build
🔧 MCP-Powered Trading Tools
Access Alpaca Trading API through Model Context Protocol. Get real-time quotes, place orders, and manage positions via AI agents.
🔄 LangGraph Agent Orchestration
Build sophisticated agent workflows with LangGraph. Design multi-agent systems with memory, checkpoints, and state management.
📊 Alpaca market data
Pull quotes and bars through the starter MCP tools. Generate signals and place paper orders from that data.
🛡️ Risk Management Built-In
Position sizing, stop losses, and portfolio-level risk controls. Build discipline into your system from day one.
🚀 Architecture you can explain
Agents, checkpoints, and risk controls you own. Stage 4 is a walkthrough and a writeup of that system.
⏰ Agents that run on a schedule
Run the graph locally on paper. Live capital stays on you. ⚠️ Results depend on strategy and market conditions.
From a student
"ArchStack course has been extremely helpful in changing my way of utilizing AI to make me more productive in how I work day to day. Isaac has developed a course that is easy to follow in learning how to create MCP tools, agents, and getting ahead of new tools."
Individual results vary. Trading involves risk of loss.
Frequently Asked Questions
No. ArchStack is built for engineers. You start with market data and work up to a paper-trading system.
Yes. You move through five stages of labs on your own schedule. Most engineers finish in about 12 weeks.
Yes. You get a community with other engineers taking the course. Ask when you get stuck, compare setups, keep moving.
Pick it back up when you can. Each stage has a checklist so you always know what to do next.
Yes. You connect Alpaca paper, pull market data, and run a graph on a schedule. Live capital stays on you.
A coding agent that can call MCP tools (Cursor, Claude Code, Codex, or VS Code), Python 3.10+, and a free Alpaca account. After you enroll, you download the lab starter and start building.
We offer a 14-day conditional refund window. Refunds are available within 14 days of purchase, but only if you have not accessed Stage 1 content. Once you access Stage 1, all sales are final. See our Terms of Service for full details.
You'll build a system that can place trades. Whether it makes money depends on your strategy, your risk rules, and the market. Trading involves substantial risk of loss. ⚠️ Past performance does not guarantee future results.
You'll have a scheduled paper-trading agent by Stage 3, around week 9. From there you keep iterating on strategy and risk.
You will build a paper-trading system. Making money still takes a strategy, risk management, and time in the market. Trading involves substantial risk of loss. ⚠️ Past performance does not guarantee future results.
Ready to build your first trading agent?
Join engineers learning to trade, architect AI systems, and run agents that work on a schedule. ⚠️ Trading involves risk of loss.