Comprehensive AI Foundations to Build, Operate & Evaluate Systems
Master production AI mindset: from model inference and architecture customization, to autonomous AI Agent operations and rigorous quality evaluation. No coding prerequisites.
EcoCart AI Decision Sandbox
Interactive PM Logic Model
Understands style intent and context. Requires prompt constraints and real-time inventory guardrails.
Grounded in Real Production on EcoCart
All 14 lessons connect through a realistic AI deployment project on the EcoCart e-commerce platform (50k daily orders) - from prompt design and token budgeting to agent operations and safety guardrails.
EcoCart E-Commerce Platform
Every lesson solves a concrete production challenge: refund automation, outfit styling, and internal policy RAG lookup.
5 Concrete PM Deliverables
1 production artifact per module
Deliver real PM artifacts after each lesson: System Prompt specs, Token ROI budgets, Pass@k evals, and Safe Fallback specifications.
Production Risk Governance
Eliminate hallucination & runaway cost
Eliminate hallucination and runaway token spend with dual-layer sandwich guardrails and Human-in-the-Loop triage workflows.
5 Modules & 14 In-Depth Lessons
Each lesson focuses on a core concept, paired with an EcoCart running example and actionable product decision frames.
What are AI and Models?
Distinguish traditional Rule-based software from Model-based AI systems, pattern learning from data, and trade-offs between determinism and adaptability.
How Models Generate Output from Input
Probabilistic inference, token-by-token generation mechanics, root causes of hallucinations, and Human-in-the-Loop workflows for risk control.
What is a Prompt?
Prompts as the primary interface between PMs and Models (LUI), 4 core components of production prompts, and Open Prompt Bars vs. Structured Prompt Builders.
How AI 'Understands' Requests
Attention Mechanism & Weighting, how word choice shifts tone, and boundaries between Parametric Knowledge and Ground Truth Verification Layers.
Everything You Need to Know
Do I need coding experience to take this course?
Not at all. The curriculum is specifically designed for Product Managers, focusing on mental models, architectural trade-offs, system prompt specs, and risk governance rather than writing Python code.
How is the course structured and paced?
It is 100% self-paced. Each lesson takes approximately 45–60 minutes and includes editorial deep-dives, interactive decision visuals, and real-world EcoCart deliverable practice.
What concrete capabilities will I gain?
You will master Rule vs Model triage, production system prompt design, context window budgeting, RAG vs Fine-tuning selection, and systematic Pass@k quality evaluation suites.
What is the recommended next step after this course?
After completing AI Literacy, you are ready for AI Product Management or the advanced AI Agents for PM curriculum covering Autonomous Agent Loops, MCP Tool Protocols, and multi-agent coordination.
Ready to Master Your AI Product Mindset?
Start immediately with Lesson 1: Rule-based vs. Model-based on EcoCart - 100% free.