AI Agents and LLMs
LLMs Beyond Chat: Real Business Use Cases
Chatbots are just the entry point. Discover how enterprises are using Large Language Models for automated search, summarization, and complex decision support.
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AI Agents and LLMs
The Agentic Shift: How AI Agents Are Redefining Software Architecture
Move beyond simple chat interfaces. Explore how autonomous AI agents are transforming software design from static code to dynamic, self-optimizing systems.
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Agentic AI
Final Capstone: The Autonomous Market Analyst
Bringing it all together. Build a complete, secure, and sovereign multi-agent system that researches stocks and generates a report.
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Agentic AI
Module 1 Lesson 1: What Agentic AI Is
The shift from generative to agentic. Understanding the third wave of AI development.
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Agentic AI
Module 1 Lesson 2: Agents vs Chatbots
Defining the boundary. Why adding a 'Search' tool to a chatbot doesn't make it an agent.
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Agentic AI
Module 1 Lesson 3: Reasoning, Planning, and Acting
The engine of agency. Understanding the ReAct pattern and how LLMs navigate complexity.
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Agentic AI
Module 1 Lesson 4: Deterministic vs Non-Deterministic Systems
Stability in the storm. Managing the unpredictability of LLMs within structured software environments.
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Agentic AI
Module 1 Lesson 5: When You Should Not Use Agents
Avoiding the 'Everything is a Nail' trap. Understanding the cost, latency, and reliability trade-offs.
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Agentic AI
Module 1 Lesson 6: Real-World Agent Use Cases
From theory to production. Where agents are actually providing business value today.
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Agentic AI
Module 1 Wrap-up: Your First Agentic Decision
Hands-on: Compare a chatbot vs an agent workflow and identify agent-worthy problems.
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Agentic AI
Module 10 Lesson 1: What ADK Solves
Standardizing the agent factory. Understanding the need for enterprise-grade management, configuration, and policies.
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Agentic AI
Module 10 Lesson 2: Agent Lifecycle Management
From cradle to grave. Managing versioning, rolling updates, and retirement of AI agents.
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Agentic AI
Module 10 Lesson 3: Configuration-Driven Agents
Separating logic from code. Using YAML and JSON to define agent personas, tools, and constraints.
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Agentic AI
Module 10 Lesson 4: Policy and Guardrails
Governance at scale. Implementing global rules that restrict agent behavior regardless of the prompt.
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Agentic AI
Module 10 Lesson 5: Enterprise Integration
Connecting to the real world. Integrating agents with SQL, ERP systems, and internal authentication.
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Agentic AI
Module 10 Wrap-up: Scaling with Governance
Hands-on: Design a configuration-driven agent with a global PII-filtering policy.
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Agentic AI
Module 11 Lesson 1: Side-by-Side Comparison
The Framework Showdown. Comparing the architecture, complexity, and performance of the top 3 agent frameworks.
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Agentic AI
Module 11 Lesson 2: When to use LangChain
The Speed Demon. Understanding the scenarios where LangChain's core abstractions outshine more complex frameworks.
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Agentic AI
Module 11 Lesson 3: When to use LangGraph
The Enterprise Choice. Why LangGraph is the standard for high-reliability, long-running agent systems.
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Agentic AI
Module 11 Lesson 4: When to use CrewAI
The Creative Engine. Scenarios where specialized roles and collaborative personas result in superior quality output.
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Agentic AI
Module 11 Lesson 5: Mixing Frameworks
The Hybrid Approach. How to combine LangGraph's control with CrewAI's collaboration for the ultimate system.
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Agentic AI
Module 11 Wrap-up: The Strategic Selection
Hands-on: Use a decision matrix to select the right framework for three real-world business scenarios.
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Agentic AI
Module 12 Lesson 1: Why Agents Hallucinate
Understanding the glitch. The psychological and technical causes of AI hallucinations in agentic systems.
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Agentic AI
Module 12 Lesson 2: Prompt Engineering for Accuracy
Words that matter. Advanced prompting techniques like Chain-of-Thought and Few-Shot that reduce agentic errors by 40%.
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Agentic AI
Module 12 Lesson 3: Output Parsing and Validation
Structured safety. Using Pydantic and JSON schemas to ensure the agent's output is machine-readable and error-free.
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Agentic AI
Module 12 Lesson 4: Self-Correction Loops
The double-check. Implementing internal loops where one agent reviews and corrects the errors of another.
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Agentic AI
Module 12 Lesson 5: Benchmarking Agent Performance
Measuring progress. How to build an Evals suite to test your agent's accuracy, tool usage, and cost over time.
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Agentic AI
Module 12 Wrap-up: Engineering for 99% Accuracy
Hands-on: Build a self-correcting agent loop that uses Pydantic to validate outputs.
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Agentic AI
Module 13 Lesson 1: Prompt Injection Attacks
Hacking the brain. Understanding how users can trick your agent into bypassing its own rules.
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Agentic AI
Module 13 Lesson 2: Data Privacy and PII
Protecting the user. How to handle Personally Identifiable Information (PII) and ensure your agent is GDPR/CCPA compliant.
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Agentic AI
Module 13 Lesson 3: Sovereignty and Local Models
Zero data leakage. Running high-performance agents on your own hardware using Ollama, MLX, and Llama.cpp.
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Agentic AI
Module 13 Lesson 4: Rate Limiting and Cost Guards
Economic security. Preventing runaway costs and protecting your API keys from exhaustion.
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Agentic AI
Module 13 Lesson 5: Compliance and Ethics
The Responsible Engineer. Navigating the legal and ethical landscape of autonomous agents.
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Agentic AI
Module 13 Wrap-up: The Secure Perimeter
Hands-on: Secure an agent against jailbreaking and implement a PII redaction layer.
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Agentic AI
Module 14 Lesson 1: The Reliability Gap
Why LLMs aren't enough. Understanding the limit of probabilistic reasoning in deterministic business systems.
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Agentic AI
Module 14 Lesson 2: Finite State Machines (FSMs)
Old school intelligence. Learning how to define states, transitions, and triggers to create unshakeable logic.
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Agentic AI
Module 14 Lesson 3: Using LLMs as State Transitions
The bridge. How to use an LLM to classify user intent and trigger a specific state change in your FSM.
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Agentic AI
Module 14 Lesson 4: Constraining Output with Outlines
Mathematically impossible to fail. Using libraries like Outlines and Guidance to force the LLM to follow a specific grammar or regex.
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Agentic AI
Module 14 Lesson 5: FSMs in Customer Service
The support architect. Designing an automated ticket system that uses an FSM for policy and an LLM for empathy.
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Agentic AI
Module 14 Wrap-up: The Sovereign Architect
Hands-on: Build a state-machine governed agent that handles a login and payment flow.
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Agentic AI
Module 15 Lesson 1: Vector Databases for Agents
The Long-Term Memory. Learning how to use Pinecone, Chroma, and PGVector to give your agents a massive knowledge base.
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Agentic AI
Module 15 Lesson 2: Semantic Caching
Save time, save money. Using GPTCache to avoid calling the expensive LLM for identical (or similar) queries.
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Agentic AI
Module 15 Lesson 3: Monitoring and Logs
The eyes of the system. Implementing real-time tracking for agent health, token usage, and user sentiment.
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Agentic AI
Module 15 Lesson 4: Scaling Agent Concurrency
Handling the crowd. How to manage thousands of concurrent agents without crashing your database or hit API limits.
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Agentic AI
Module 15 Lesson 5: CI/CD for Agents
Pipelining intelligence. How to automate the testing, benchmarking, and deployment of your agentic code and prompts.
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Agentic AI
Module 15 Wrap-up: Engineering for the Millions
Hands-on: Build a simple RAG agent that retrieves context from a local Vector DB before answering.
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Agentic AI
Module 16 Lesson 1: The Chat Box is Not Enough
Breaking the box. Why traditional chat interfaces fail to communicate the complexity of multi-agent systems.
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Agentic AI
Module 16 Lesson 2: Generative UI
Beyond text. How to use Vercel AI SDK and specialized tokens to render interactive UI components (dashboards, charts) on the fly.
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Agentic AI
Module 16 Lesson 3: Streaming Intermediate Steps
Watch the agent work. How to capture and stream the 'Thought' and 'Action' phases to the UI in real-time.
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Agentic AI
Module 16 Lesson 4: Designing for Long Latency
Patience is a virtue. How to handle research tasks that take minutes to finish using notifications and async status pages.
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