AI
AI components
Basic
Intermediate
Advanced
Basic
LLMs - Large Language Models
Hosted models such as Grok, GPT, Claude, Gemini and others.
Local models available through OLLAMA, LM Studio and more
Custom models.
Embeddings and Vector Databases
Storing and retrieving semantic information.
Databases such as Pinecone, Weaviate, FAISS
Prompt Engineering
Designing and optimizing prompts to improve AI responses and accuracy.
API's and External Data Access
Connecting AI to external data sources via APIs.
OpenAI, Hugging Face, LangChain
Intermediate
Context Management
Handling log conversations, session history and user interactions.
Memory in LangChain, RAG
Memory and Retrieval Mechanisms
Short Term and Long Term memory
Retrieval-Augmented Generation (RAG), ChromaDB.
Function Calling and Tool use
Allowing AI to call external tools and execute actions
OpenAI Functions, Autogen
Multi-Step Reasoning
Planning and breaking down tasks into smaller steps for execution
Chain-of-thought prompting
Agent-Oriented Frameworks
Tools for orchestrating multiple AI agents
LangChain Agents, AutoGen, CrewAI
Advanced
Multi-Agent Collaboration
AI Agents interacting, delegating ands solving problems in teams
CrewAI, MetaGPT
Agentic Workflows
Structured Workflows where AI Agents can decide and act autonomously
AutoGPT, BabyAGI
Autonomous Planning and Decision making
AI making independent decisions based on user goals
Reflection, Ada Planner.
Self Learning AI Agents
AI improving itself based on feedback or past experiences
Adaptive AI, AutoRL.
Fully Autonomous AI Agents
AI executing real-world tasks with minimal human intervention
Devin AI, OpenDevin.