1.1 Core AI/ML Knowledge

Machine Learning Basics

• Supervised, unsupervised, reinforcement learning
• Model training and evaluation
• Feature engineering

Deep Learning Fundamentals

• Neural networks architecture
• Backpropagation
• Optimization techniques
• Training deep models

Natural Language Processing

• Text preprocessing and tokenization
• Word embeddings (Word2Vec, GloVe)
• Sequence models (RNN, LSTM)
• Attention mechanisms

1.2 Large Language Models (LLMs)

Transformer Architecture

• Self-attention mechanism
• Multi-head attention
• Positional encoding
• Encoder-decoder structure

Pre-trained LLMs

• GPT series (GPT-3, GPT-4)
• Claude (Anthropic)
• LLaMA, Mistral
• BERT and variants

Prompt Engineering

• Zero-shot prompting
• Few-shot prompting
• Chain-of-Thought (CoT) prompting
• Tree-of-Thoughts (ToT)
• ReAct prompting
• Self-consistency
• Prompt templates and patterns

LLM APIs and Integration

• OpenAI API
• Anthropic API
• Hugging Face models
• Local LLM deployment (Ollama, LM Studio)

1.3 Programming & Software Engineering

Python Advanced Concepts

• Async/await programming
• Decorators and context managers
• Error handling and logging
• Type hints and validation

API Development

• REST API design
• FastAPI/Flask
• Authentication and security
• Rate limiting and error handling

Data Structures

• Queues and stacks
• Hash tables and dictionaries
• Priority queues

1.4 System Design Basics

• Scalability principles
• Microservices architecture
• Message queues (RabbitMQ, Redis)
• Caching strategies
• Database design (SQL and NoSQL)

2.1 Agent Theory & Architecture

Agent Concepts

• Definition and characteristics of agents
• Autonomy, reactivity, proactivity, social ability
• Rational agents
• Agent environments (fully observable, partially observable, deterministic, stochastic)
• Single-agent vs multi-agent systems

Agent Types

• Simple reflex agents
• Model-based reflex agents
• Goal-based agents
• Utility-based agents
• Learning agents
• BDI (Belief-Desire-Intention) agents

Agent Architectures

• Reactive architectures
• Deliberative architectures
• Hybrid architectures
• Layered architectures
• Blackboard systems

2.2 Planning & Reasoning

Classical Planning

• STRIPS (Stanford Research Institute Problem Solver)
• PDDL (Planning Domain Definition Language)
• Forward search planning
• Backward search planning
• Hierarchical Task Networks (HTN)
• Partial-order planning

Modern Planning Approaches

• Graph-based planning
• Constraint satisfaction problems
• Temporal planning
• Contingent planning
• Probabilistic planning
• Monte Carlo Tree Search (MCTS)

Reasoning Techniques

• First-order logic
• Propositional logic
• Probabilistic reasoning
• Causal reasoning
• Common sense reasoning
• Analogical reasoning
• Abductive reasoning

2.3 Decision Making

Decision Theory

• Utility theory
• Expected utility
• Multi-attribute utility theory
• Decision trees
• Influence diagrams

Sequential Decision Making

• Markov Decision Processes (MDPs)
• Partially Observable MDPs (POMDPs)
• Value iteration
• Policy iteration
• Q-learning for agents

Multi-Criteria Decision Making

• Pareto optimality
• TOPSIS method
• AHP (Analytic Hierarchy Process)
• Weighted sum models

2.4 Memory Systems

Memory Types

• Short-term (working) memory
• Long-term memory
• Episodic memory
• Semantic memory
• Procedural memory

Memory Management

• Memory consolidation
• Memory retrieval strategies
• Forgetting mechanisms
• Memory indexing
• Vector databases for memory

Context Management

• Context windows
• Context compression

3.1 Function Calling Fundamentals

Concepts

• Function schemas and definitions
• Parameter extraction from natural language
• Function selection and routing
• Function chaining
• Parallel function execution

Implementation Patterns

• JSON schema for function definitions
• Tool description best practices
• Error handling in function calls
• Retry mechanisms
• Fallback strategies

3.2 Tool Integration

API Integration

• REST API calls
• GraphQL queries
• SOAP services
• Webhooks
• API authentication (OAuth, API keys)

External Tools

• Search engines (Google, Bing, DuckDuckGo)
• Databases (SQL, MongoDB, Redis)
• File systems and storage
• Email and communication tools
• Calendar and scheduling
• Web scraping tools
• Image generation APIs
• Code execution environments

Custom Tool Development

• Tool wrapper design patterns
• Tool documentation
• Tool testing and validation
• Tool versioning
• Tool discovery mechanisms

3.3 Tool Orchestration

Sequential Tool Usage

• Pipeline design
• Data flow between tools
• State management
• Error propagation

Parallel Tool Usage

• Concurrent execution
• Race conditions handling
• Result aggregation
• Timeout management

Conditional Tool Usage

• Decision trees for tool selection
• Rule-based tool routing
• ML-based tool recommendation
• Dynamic tool loading

4.1 LangChain Deep Dive

Core Components

• Chains (LLMChain, SequentialChain, TransformChain)
• Agents (Zero-shot, Conversational, OpenAI Functions)
• Tools and Toolkits
• Memory (ConversationBufferMemory, VectorStoreMemory)
• Retrievers and document loaders
• Output parsers
• Callbacks and logging

Advanced Features

• Custom chains
• Custom agents
• Agent executors
• Async execution
• Streaming responses
• Error handling
• LangSmith for debugging

LangGraph

• State graphs
• Node and edge definitions
• Conditional edges
• Cycles and loops
• Checkpointing
• Human-in-the-loop
• Subgraphs
• Multi-agent orchestration

4.2 Alternative Frameworks

AutoGPT / AutoGen

• Architecture and design
• Plugin system
• Memory management
• Autonomous operation
• Multi-agent conversations

CrewAI

• Agent roles and goals
• Task definitions
• Crew composition
• Process types (sequential, hierarchical)
• Agent collaboration
• Tool sharing

LlamaIndex (GPT Index)

• Index structures
• Query engines
• Agent abstractions
• Data connectors
• Response synthesis

Semantic Kernel (Microsoft)

• Skills and functions
• Planners
• Memory connectors
• Kernel composition
• Plugin architecture

Haystack

• Pipeline components
• Agents and tools
• Document stores
• Retrievers
• Readers and generators

OpenAI Assistants API

• Assistant creation
• Thread management
• Function calling
• File handling
• Code interpreter
• Retrieval tools

4.3 Agent Development Patterns

Architectural Patterns

• ReAct (Reasoning + Acting)
• Plan-and-Execute
• Reflection and self-critique
• Tree of Thoughts
• Graph of Thoughts
• Self-Ask
• Multi-agent debate

Design Patterns

• Agent factory pattern
• Strategy pattern for agent behavior
• Observer pattern for monitoring
• Chain of responsibility
• Command pattern for tasks
• State pattern for agent states

Best Practices

• Error handling strategies
• Logging and observability
• Testing agent behaviors
• Cost optimization
• Latency reduction
• Security considerations

5.1 RAG Fundamentals

Core Concepts

• Retrieval vs generation
• Dense vs sparse retrieval
• Embedding models
• Similarity search
• Re-ranking

RAG Pipeline

• Document ingestion
• Chunking strategies
• Embedding generation
• Vector storage
• Query processing
• Context injection
• Response generation
• Citation and attribution

5.2 Vector Databases

Popular Vector DBs

Vector DB Operations

• Indexing strategies (HNSW, IVF)
• Query optimization
• Filtering and metadata
• Hybrid search
• Batch operations
• Scalability

5.3 Advanced RAG Techniques

Retrieval Enhancement

• Query expansion
• Query rewriting
• Hypothetical document embeddings (HyDE)
• Multi-query retrieval
• Parent-child document retrieval
• Ensemble retrieval

Context Optimization

• Context window management
• Relevance scoring
• Re-ranking algorithms
• Context compression
• Lost-in-the-middle mitigation
• Adaptive context selection

RAG Architectures

• Naive RAG
• Advanced RAG
• Modular RAG
• Agentic RAG
• Self-RAG
• Corrective RAG (CRAG)
• Graph RAG

5.4 Knowledge Graphs for Agents

Graph Fundamentals

• Nodes, edges, properties
• Graph databases (Neo4j, ArangoDB)
• Graph query languages (Cypher, Gremlin)
• Graph schemas

Knowledge Graph Construction

• Entity extraction
• Relation extraction
• Knowledge graph embedding
• Graph completion
• Temporal knowledge graphs

Agent-Graph Integration

• Graph-based reasoning
• Path finding for reasoning
• Subgraph retrieval
• Graph neural networks for agents
• Hybrid RAG with KGs

6.1 Multi-Agent Fundamentals

Concepts

• Cooperation vs competition
• Communication protocols
• Agent coordination
• Task allocation
• Resource sharing
• Consensus mechanisms

Interaction Patterns

• Peer-to-peer communication
• Hierarchical structures
• Market-based coordination
• Contract net protocol
• Blackboard systems
• Publish-subscribe patterns

6.2 Agent Communication

Communication Languages

• FIPA-ACL (Agent Communication Language)
• KQML (Knowledge Query and Manipulation Language)
• Custom protocols
• Message ontologies

Message Types

• Inform / Request
• Query / Response
• Subscribe / Notify
• Propose / Accept / Reject
• Call for proposals

6.3 Coordination Mechanisms

Coordination Strategies

• Centralized coordination
• Distributed coordination
• Hierarchical coordination
• Market-based mechanisms
• Voting and consensus
• Negotiation protocols

Task Allocation

• Contract net protocol
• Auction mechanisms
• Coalition formation
• Task decomposition
• Load balancing
• Deadlock prevention

6.4 Multi-Agent Architectures

Collaborative Architectures

• Swarm intelligence
• Team-based agents
• Shared workspace
• Workflow-based coordination
• Pipeline architectures

Competitive Architectures

• Game-theoretic agents
• Nash equilibrium
• Evolutionary strategies
• Adversarial agents

Hybrid Architectures

• Manager-worker pattern
• Expert panels
• Debate frameworks
• Reflection-based systems

7.1 Learning & Adaptation

Online Learning

• Incremental learning
• Active learning
• Transfer learning for agents
• Meta-learning
• Continual learning

Reinforcement Learning for Agents

• Agent-environment interaction
• Reward shaping
• Exploration strategies
• Multi-agent RL
• Hierarchical RL
• Inverse RL

Self-Improvement

• Self-reflection mechanisms
• Error analysis
• Strategy refinement
• Automated prompt optimization
• Constitutional AI principles

7.2 Planning & Execution

Advanced Planning

• Hierarchical planning
• Contingency planning
• Probabilistic planning
• Temporal planning
• Resource-constrained planning
• Multi-agent planning

Plan Execution

• Plan monitoring
• Plan repair and replanning
• Execution traces
• Failure detection
• Recovery strategies

Task Decomposition

• Recursive decomposition
• Goal hierarchies
• Subgoal generation
• Dependency analysis
• Critical path identification

7.3 Reasoning & Problem Solving

Advanced Reasoning

• Causal reasoning
• Counterfactual reasoning
• Analogical reasoning
• Meta-reasoning
• Symbolic reasoning integration

Problem-Solving Strategies

• Heuristic search
• Constraint satisfaction
• Optimization techniques
• Satisficing vs optimizing
• Anytime algorithms

7.4 Code Generation & Execution

Code Understanding

• Code parsing and AST analysis
• Code summarization
• Dependency analysis
• Code similarity

Code Generation

• Function generation
• Test generation
• Documentation generation
• Code refactoring
• Bug fixing

Safe Code Execution

• Sandboxing (Docker, Firecracker)
• Code validation
• Resource limits
• Timeout mechanisms
• Security scanning
• Output validation

8.1 Interface Design

Conversational Interfaces

• Natural language understanding
• Dialogue management
• Context tracking
• Intent recognition
• Slot filling
• Confirmation strategies

Multimodal Interfaces

• Voice interfaces
• Visual interfaces
• Gesture recognition
• Mixed reality integration

Transparency & Explainability

• Action explanation
• Reasoning traces
• Confidence scores
• Decision justification
• Uncertainty communication

8.2 Human-in-the-Loop Interaction Patterns

Interaction Patterns

• Approval workflows
• Feedback mechanisms
• Clarification requests
• Progressive disclosure
• Guided autonomy

Oversight Mechanisms

• Action approval
• Monitoring dashboards
• Intervention points
• Emergency stops
• Audit trails

8.3 Trust & Reliability

Trust Building

• Consistency in behavior
• Predictability
• Error acknowledgment
• Transparent limitations
• Gradual autonomy increase

Reliability Engineering

• Fault tolerance
• Graceful degradation
• Redundancy
• Health checks
• Performance monitoring

9.1 Orchestration Patterns

Workflow Orchestration

• DAG (Directed Acyclic Graph) execution
• Event-driven architectures
• State machines
• Saga patterns
• Choreography vs orchestration

Resource Management

• Compute allocation
• Memory management
• Token budget management
• Rate limiting

9.2 Scalability & Performance

Horizontal Scaling

• Load balancing
• Stateless agents
• Distributed task queues
• Sharding strategies

Performance Optimization

• Caching strategies
• Batch processing
• Parallel execution
• Async/await patterns
• Connection pooling

Latency Reduction

• Response streaming
• Speculative execution
• Predictive prefetching
• Edge deployment

9.3 Monitoring & Observability

Metrics & Logging

• Agent performance metrics
• Token usage tracking
• Error rates
• Latency monitoring
• Success rates
• Cost tracking

Tracing

• Distributed tracing
• Request flow tracking
• Dependency mapping

Alerting

• Anomaly detection
• Threshold-based alerts
• SLA monitoring
• Incident management

9.4 Production Deployment

Deployment Strategies

• Blue-green deployment
• Canary releases
• Feature flags
• A/B testing
• Shadow deployment

Infrastructure

• Containerization (Docker)
• Kubernetes orchestration
• Serverless deployment (AWS Lambda, Cloud Run)
• API gateways
• Load balancers

CI/CD for Agents

• Automated testing
• Integration tests
• Regression testing
• Deployment pipelines
• Rollback strategies

10.1 Agent Safety

Safety Mechanisms

• Input validation
• Output filtering
• Action constraints
• Sandbox environments
• Kill switches
• Rate limiting

Risk Assessment

• Failure mode analysis
• Security vulnerabilities
• Privacy risks
• Bias assessment
• Adversarial attacks

Guardrails

• Content filtering
• Action whitelisting
• Budget limits
• Scope restrictions
• Human approval gates

10.2 Ethics & Alignment

Ethical Frameworks

• Value alignment
• Constitutional AI
• RLHF (Reinforcement Learning from Human Feedback)
• Red teaming
• Fairness constraints

Alignment Techniques

• Instruction fine-tuning
• Preference learning
• Inverse reinforcement learning
• Debate and amplification
• Recursive reward modeling

Data Privacy

• PII detection and masking
• Data minimization
• Encryption at rest and in transit
• Access controls
• GDPR compliance

Security Best Practices

• Authentication and authorization
• API key management
• Prompt injection prevention
• Jailbreak protection
• Audit logging

10.4 Governance & Compliance

Governance Frameworks

• Usage policies
• Access controls
• Approval workflows
• Change management
• Documentation requirements

Compliance

• Regulatory requirements
• Industry standards
• Certification processes
• Audit trails
• Reporting mechanisms