Practical AI Education
For Busy Professionals.
Clear, concise guides built for developers, managers, and builders. Each module is structured to deliver immediate conceptual clarity in about 90 seconds.
1. LLMs Demystified: Core Mechanics
Tokens, context windows, and RAG without the mathematical jargon
Understand what frontier models actually do under the hood. Learn how tokenization affects cost, why context windows are working memory, and how Retrieval-Augmented Generation (RAG) grounds probabilistic answers in verified facts.
2. Coding with AI Agents & Harnesses
Leveraging Claude Code, OpenCode, and OpenAI with strict guardrails
How to transition from simple chat prompts to autonomous terminal coding agents. Explore agent harnesses, permissions, file system boundaries, automated verification scripts, and failure recovery.
3. Real-World Workflow Automation
The 4-step framework: Trigger, AI Synthesis, Human Review, Action
Transform noisy manual workflows into dependable automation pipelines. Why the "Human-in-the-Loop" gate prevents costly operational mistakes while unlocking 10x throughput.
4. AI in Financial Trading & Research
Research synthesis, quantitative rules, backtests, and risk boundaries
How machine intelligence can process market reports and generate trading hypotheses — and why mathematical backtesting, paper trading, and hard risk limits must always control capital execution.
Prefer to see these concepts in production?
Check out Professor Turtle (syllabus question generation & AI grading) and Puzzle Arena (real-time bots).