v2.0

🎯 AlphaEdge AI PM Learning Roadmap

Master AI Product Management - From Concepts to Market Leadership

1
Basic Concepts

🧠Machine Learning Fundamentals

  • Supervised Learning - Classification & Regression
  • Unsupervised Learning - Clustering & Dimensionality
  • Reinforcement Learning - Agent-Environment Interaction
  • Deep Learning - Neural Networks & Architectures

🏗️AI Architectures

Neural Networks
Transformers
LLMs
CNNs
RNNs
GANs

🎯Model Types & Applications

LLM
Language Models
LCM
Logic Models
LAM
Action Models
MoE
Expert Models
🔗 WTF is AI Product Manager 📊 LLM Visualization
2
Prompt Engineering

📚Learning Resources

  • GPT-4 Prompting Guide - Advanced Techniques
  • Anthropic Prompt Engineering - Best Practices
  • System Prompts with Claude 4 - Architecture
  • Anthropic Prompt Generator - Tools
  • Anthropic Prompting Course - Certification

⚡Advanced Techniques

CoT
Chain of Thought
RAG
Retrieval Augmented
Few-Shot
Example Learning
Fine-Tune
Model Training
Production-Ready Prompts:
  • Step-by-Step: Break complex tasks into manageable steps
  • Constraints: Define clear boundaries and requirements
  • Examples: Provide high-quality input-output pairs
  • Persona: Define the AI's role and expertise level
3
Fine-Tuning

🔧Methods & Approaches

  • Supervised Fine-Tuning (SFT) - Task-specific training
  • Direct Preference Optimization (DPO) - Human feedback
  • Parameter Efficient Fine-Tuning - LoRA/QLoRA
  • Multi-task Learning - Simultaneous optimization

🛠️Best Tools & Platforms

📊Key Metrics & Evaluation

Training Loss ↓
Model Learning
Accuracy ↑
Prediction Quality
Validation Loss ↓
Generalization
F1 Score ↑
Balanced Performance
  • Training Data: Curated datasets for model learning
  • Validation Data: Unseen data for performance testing
  • Epoch: Complete pass through training dataset
  • Batch Size: Number of samples processed together
  • Learning Rate: Step size for model updates
  • Beta (DPO): Temperature parameter for preference learning
4
RAG Systems

🗄️Vector Databases

Weaviate
Pinecone
Chroma
Qdrant
Milvus
FAISS

📄Document Databases

OpenSearch
Elasticsearch
MongoDB
PostgreSQL

🕸️Knowledge Graphs

Weaviate
Vector + Graph
Neo4j
Graph Database
Amazon Neptune
Managed Graph
Vector Store
Embeddings & fast semantic search
Document DB
Structured data & metadata

Use vector stores for embeddings and semantic search. Use document DBs for metadata storage and structured queries.

5
AI Agents & Workflows

🤖Agent Frameworks

⚙️Advanced Techniques

Tool Use
Function Calling
MCP
Model Context Protocol
A2A
Agent-to-Agent
RAG+
Enhanced Retrieval

📊Industry Reports

🔍 Google Agent Companion 🏗️ Anthropic Building Agents 🤖 IBM Agentic Process Automation
  • ReAct Pattern - Reasoning + Acting
  • Multi-Agent Systems - Collaborative workflows
  • Tool-Augmented Agents - External API integration
  • Memory-Enhanced Agents - Persistent context
6
AI Prototyping & Building

🚀No-Code Solutions

Lovable
Bolt
Databutton
Firebase Studio

💻IDE & Development

Replit
v0
Windsurf
Cursor
Codex
Jules

🛠️Infrastructure Tools

Frontend
React, Next.js, v0
Backend
Supabase, Firebase
AI Layer
OpenRouter, LangChain
Deploy
Netlify, Vercel
7
Foundational Models

🧠Leading AI Models

📊Model Comparison Matrix

GPT-4
General Purpose
Claude
Reasoning & Safety
Llama
Open Source
Gemini
Multimodal
  • Claude Sonnet: Best for reasoning, analysis, and safety-critical applications
  • GPT-4: Excellent for creative tasks, coding, and general conversation
  • Llama 3.1: Open-source option for custom deployments
  • Gemini Pro: Strong multimodal capabilities for vision + text
  • DeepSeek: Cost-effective for mathematical and coding tasks
8
AI Evaluation Systems

🔄Virtuous Cycle

📊
🧪
📈
🔄
Data Collection
Gather performance metrics
Model Testing
Evaluate on benchmarks
Analysis
Identify improvements
Iteration
Deploy & monitor

📋Evaluation Techniques

Unit Tests
Component Testing
LLM Judge
AI-based Evaluation
Error Analysis
Failure Pattern Analysis
RLHF
Human Feedback Loop
Human Eval
Expert Assessment
Model Eval
Automated Testing
Train/Test/Dev
Dataset Splitting
A/B Tests
Performance Comparison
📖 Mastering AI Evals: Complete Guide for PMs
9
Essential Resources

📚Must-Read Resources

  • AI PNRD: Free GPT template by Miodrag Jafjer (OpenAI)
  • Awesome Generative AI (GitHub): Comprehensive resource list
  • Prompt Hackers AI: All LLMs in one subscription
  • MCP.so: The largest collection of MCP servers
  • Anthropic MCP Servers: Official Anthropic collection
  • Microsoft/Markitdown: Converting docs to Markdown

🎯Specialized Learning Paths

Technical PM
Deep AI/ML focus
Business PM
Strategy & adoption
Design PM
UX/UI for AI products
Growth PM
Scaling AI solutions
Junior AI PM
0-2 years • Focus on learning
Senior AI PM
3-5 years • Product ownership
Principal AI PM
5-8 years • Strategy & vision
AI PM Director
8+ years • Team leadership
📊
Your Learning Progress

🎯Overall Completion

0% Complete - Keep learning! 🚀

🏆Learning Milestones

0/4
Basic Concepts
0/5
Prompt Engineering
0/4
Fine-Tuning
0/6
Resources