Skip to content

Advanced Agentic AI Tools

Week 01 Foundations of Agentic AI

Agentic AI vs Generative AI: Comparing Autonomy, Workflows, and Use Cases

Lesson overview
Overview

The Agentic AI Operating Model

Lesson overview
What Makes an AI System an Agent
The Core Agent Loop: Observe, Think, and Act
Why Context Grows During Agent Work
The Definition of Done
Parallelization as a Core Agent Advantage
Agent Environments and Their Common Operating Pattern
Model Characteristics and Practical Selection
A Practical Operating Method for a Single Agent
Lesson 1 Summary

Persistent Instructions, Skills, Reverse Prompting, and Prompt Contracts

Lesson overview
Why Ordinary Prompts Do Not Compound
Persistent Instruction Files
Self-Modifying and Self-Correcting Instructions
The Limits of a Growing Rule Set
Global, Local, Memory, Skill, and Inline Layers
Agent Skills as Reusable Standard Operating Procedures
The Algorithmic Art Example
Skills and Context Efficiency
Why Vague Tasks Fail
Prompt Contracts
Balancing Vagueness and Over-Specification
Reverse Prompting
Chaining Reverse Prompting Into a Prompt Contract
The Website Contract Examples
Applying Contracts Outside Software
A Complete Prompt-Architecture Workflow
Lesson 2 Summary

Multi-Agent Orchestration, Model Routing, Video-to-Action, and Parallel Browser Work

Lesson overview
Moving from One Agent to a Managed Workforce
The Router as the Decision Hub
Specialization and Small Quality Differences
The Full-Stack Image Generator Example
Manager Instructions
Model Context Protocol as a Connection Layer
Practical Setup Requirements and Trade-Offs
Video-to-Action: Learning from Visual Procedures
The Blender Donut Example
The n8n Workflow Example
Multi-Agent Browser Automation
Separate Workspaces, Shared Chat, and Task Control
The Personalized Outreach Example
The Vancouver Rental Example
Risks and Boundaries of Browser Scale
A Complete Multi-Agent Orchestration Blueprint
Lesson 3 Summary

Multi-Agent Consensus, Debate, and Verification

Lesson overview
Using Variability as a Design Feature
Traversing the Search Space
Parallelism Reduces Elapsed Time
The Stochastic Multi-Agent Consensus Workflow
Consensus, Divergence, and Outliers
The Tiktok Growth Example
When Stochastic Consensus Is Useful
From Independent Analysis to Agent Chat Rooms
Structuring the Debate
The Tiktok Debate Example
Consensus Versus Debate
The Limits of Multi-Agent Strategic Advice
Why an Agent Becomes Biased Toward Its Own Work
Subagent Verification Loops
The Rate-Limiter Example
The Splinter Codebase Review
Parallel and Serial Multi-Agent Patterns
The Connection to Statistical Model Behavior
A Decision Guide for Multi-Agent Reasoning
A Complete Reasoning-to-Verification Workflow
Lesson 4 Summary

Context Engineering, Model Routing, Cost Control, and Scaling

Lesson overview
Why Context Is Part of the Agent Architecture
Tokens, Words, and Working Capacity
Why Quality Can Decline as Context Grows
A Practical Context-Usage Example
Tool Definitions Also Consume Context
What Happens When the Context Fills
Information Density and Compression
The Iceberg Technique
Store Access, Not Everything
Selective File and Code Retrieval
Selective Web Retrieval
Skill Discovery Through Compact Metadata
Summarizing Tool Results
Context Management as Quality and Cost Control
Matching Model Capability to Task Difficulty
The Cost-Quality Trade-Off
The 60/30/10 Model-Allocation Pattern
The Cost Calculation Example
The Lead-Processing Pipeline Example
Batch Processing
Parallelism Also Has a Cost
Connecting Context, Quality, and Cost
A Master Operating Framework
Common Failure Modes at Scale
Final Mastery Principles
Lesson 5 Summary

Week 02 Mastering the Model Context Protocol (MCP)

Why MCP Exists

Lesson overview
Overview

The Host-Client-Server Architecture

Lesson overview
Overview

Tools, Resources, and Prompts

Lesson overview
Overview

Communication Lifecycle, JSON-RPC, and Transports

Lesson overview
Overview

Connecting to and Using an Existing MCP Server

Lesson overview
Overview

Building a No-Code MCP Server

Lesson overview
Overview

Building a Code-Based MCP Server

Lesson overview
Overview

Development Environment, SDKs, and the Build Sequence

Lesson overview
Overview

Testing and Debugging MCP Implementations

Lesson overview
Overview

Authentication, Authorization, and Permissions

Lesson overview
Overview

Prompt Injection, Tool Poisoning, and Dynamic Tool Changes

Lesson overview
Overview

Supply-Chain Security and Secure Operations

Lesson overview
Overview

Designing Reliable MCP Tools and Workflows

Lesson overview
Overview

Deployment, Scalability, and Enterprise Infrastructure

Lesson overview
Overview

Agentic, Multimodal, and Real-Time Applications

Lesson overview
Overview

Applied MCP Case Studies

Lesson overview
Introduction
Customer Support
Healthcare
Financial Services
Multi-Agent Travel Planning
Workflow Automation
Real-Time Documentation
Conversational Study Planning
API Management
Browser Automation

A Hands-on Learning Path

Lesson overview
Introduction
Stage 1: Learn the AI Development Environment
Stage 2: Connect an Agent to an Existing Server
Stage 3: Build a Custom Weather Server
Stage 4: Build a Developer Automation Server
Stage 5: Build a Complete Tools-Resources-Prompts Server
Stage 6: Build an Enterprise Project

Community, Packaging, and Contribution

Lesson overview
Overview

Ecosystem Directions and Advanced Projects

Lesson overview
Overview

MCP Mastery Assessment

Lesson overview
Introduction
Definition and Purpose
Architecture
Server Features
Communication
Implementation
Testing
Security
Production Design
Applied Capability

Week 03 Mastering RAG

RAG Foundations and the Shift to Agentic Retrieval

Lesson overview
Overview

End-to-End Architecture for a Multi-User RAG Application

Lesson overview
Overview

Building with AI Agents - Planning, Context, Validation, and Version Control

Lesson overview
Overview

From Application Shell to Managed RAG - Fast Start and Black-Box Limits

Lesson overview
Overview

Owning the Retrieval Pipeline - Ingestion, Embeddings, Configuration, and Security

Lesson overview
Overview

Maintaining Knowledge Quality - Deduplication, Metadata, Parsing, and Performance

Lesson overview
Overview

Improving Retrieval Quality - Hybrid Search, Filtering, Reranking, and Tool Loops

Lesson overview
Overview

Retrieving Beyond Documents - Text-to-SQL, Web Search, and Database-Level Control

Lesson overview
Overview

Whole-Document Reasoning with Subagents and a Transparent Streaming Interface

Lesson overview
Overview

Testing, Debugging, Local Operation, and Production Readiness

Lesson overview
Introduction
Ingestion
Retrieval
Tools
Interface

Week 04 Memory Layer for AI Agents

Why Conventional RAG Is Not Enough for Stateful AI Agents

Lesson overview
Overview

Represent Memory with Relational, Vector, and Graph Layers

Lesson overview
Overview

Turn Raw Data Into Searchable, Structured Memory

Lesson overview
Overview

Manage the Complete Memory Lifecycle

Lesson overview
Overview

Partition Memory by Domain, Session, and Agent Role

Lesson overview
Overview

Combine Vector Retrieval with Graph Traversal for Multi-Hop Answers

Lesson overview
Overview

Use Feedback to Improve Future Retrieval and Decision Making

Lesson overview
Overview

Orchestrate Multiple Agents to Resolve a Cross-System Incident

Lesson overview
Overview

Design for Persistence, Observability, Latency, and Deployment

Lesson overview
Overview

Understand the Trade-Offs and Choose the Right Memory Use Case

Lesson overview
Overview

Week 05 Mastering the Essentials of Kimi K3

Start with a Real Workflow Problem

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Match the Model, Context, and Interface to the Workload

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Design Goal Loops Instead of Chasing Perfect Prompts

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Decompose Large Work Into Specialized Subagents

Lesson overview
Core Idea
How It Works
Manual Parallelism
Orchestrated Parallelism
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Turn Successful Procedures Into Reusable Skills

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Engineer Context Continuity with Projects and Shared Memory

Lesson overview
Core Idea
Task Context
Project Context
Why It Matters
Practical Application
Layer 1: Current-Task Context
Layer 3: Cross-Agent Memory
Trade-Offs and Limitations
Key Takeaway

Extend the Agent with Tools, But Control the Trust Boundary

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Deploy Recurring Work Where It Can Actually Run

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Name: Daily Automation-News Research
Frequency: Daily
Trade-Offs and Limitations
Key Takeaway

Make Validation and Recovery Part of the Build Loop

Lesson overview
Core Idea
How It Works
Progress Inspection
Artifact Inspection
Functional Testing
Requirement Checking
Recovery
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Separate the Model from the Harness and Compose an Agent Operating System

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Week 06 Mastering the Essentials of Agentic Engineering

The Agent Harness Is the Operating Layer

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Compress Context and Layer Instructions

Lesson overview
Core Idea
How It Works
Global Layer
Local Layer
Why It Matters
Practical Application
Project Purpose
Project Map
Commands and Workflows
Conventions and Preferences
Capabilities
Lab Notes
Trade-Offs and Limitations
Key Takeaway

Turn Every Run Into Persistent Learning

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Parallelize Independent Work and Synthesize the Results

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Use Stochastic Consensus and Debate to Explore the Solution Space

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build Lean Specialist Pipelines with Fresh Review Contexts

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Name
Description
Prompt or Procedure
Tools
Model
Handoff
Trade-Offs and Limitations
Key Takeaway

Design Autonomous Improvement as a Measured Experiment Loop

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Target
Change Surface
Assessment
Constraints
Baseline
Reversal Method
Log Format
Trade-Offs and Limitations
Key Takeaway

Choose the Least Complex Automation Layer That Works

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Treat Workspace Organization as Part of Context Engineering

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Root
Each Project or Client
Trade-Offs and Limitations
Key Takeaway

Contain Security Risk with Simple Controls and Independent Review

Lesson overview
Core Idea
How It Works
Conversation-History Leakage
Database Exposure
Public-Service Exposure
Payment-Data Liability
Biased Self-Audit
Why It Matters
Practical Application
Secrets
Dependencies
Databases
Public Exposure
Payments
Permissions
Audit
Trade-Offs and Limitations
Key Takeaway
Conclusion

Week 07 Mastering Git & GitHub

Version Control, Git, and GitHub

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

The Git Workflow and Repository Setup

Lesson overview
Core Idea
How It Works
Repository Creation by Initialization
Repository Creation by Cloning
Checking Installation and Repository State
Why It Matters
For Example
Practical Application
Trade-Offs and Limitations
Key Takeaway

Staging Changes with Control

Lesson overview
Core Idea
How It Works
Unstaging Changes
Why It Matters
Practical Application
Decision Logic
Trade-Offs and Limitations
Key Takeaway

Commits, Identity, History, and Comparison

Lesson overview
Core Idea
How It Works
Viewing Commit History
Checking Out an Earlier Commit
Comparing Commits
Why It Matters
Practical Application
Example
After Inspection
Trade-Offs and Limitations
Key Takeaway

Undoing, Restoring, Removing, and Reversing Changes

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Branching for Isolated Development

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Example
Branch Naming and Roles
Trade-Offs and Limitations
Key Takeaway

Merging Branches and Resolving Conflicts

Lesson overview
Core Idea
How It Works
Automatic Merge
Merge Conflict
For Example
Why It Matters
Practical Application
Conflict Resolution Example
Then
Trade-Offs and Limitations
Key Takeaway

Remote Synchronization and Pull Requests

Lesson overview
Core Idea
Pushing Local Commits
Fetching Remote Updates
Run
Pulling Remote Updates
Pull Requests
Why It Matters
Practical Application
On GitHub
Trade-Offs and Limitations
Key Takeaway

Preserving Unfinished Work with Git Stash

Lesson overview
Core Idea
How It Works
Pop Versus Apply
Listing and Removing Stashes
Why It Matters
Practical Application
Then Inspect
Decision Logic
Trade-Offs and Limitations
Key Takeaway

Rebasing for a Linear History

Lesson overview
Core Idea
How It Works
Comparison with Merge
Why It Matters
Practical Application
Decision Logic
Trade-Offs and Limitations
Key Takeaway

Week 08 Mastering ComfyUI

Building a Local ComfyUI Environment and Model Foundation

Lesson overview
Core Idea
How It Works
ComfyUI/Models/Checkpoints
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Understanding the Node Graph and the Text-to-Image Pipeline

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Controlling Generation with Resolution, Seeds, Steps, Cfg, Samplers, and Denoise

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Organizing, Reusing, and Debugging Workflows

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Extending ComfyUI with Manager, Models, and Custom Nodes

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Upscaling Images and Controlling Which Outputs Continue

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Using Image-to-Image to Balance Preservation and Change

Lesson overview
Core Idea
How It Works
Load Image -> Vae Encode -> Ksampler Latent Image Input
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Producing Detailed Enlargements with Tiled Image-to-Image Upscaling

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Controlling Pose and Composition with ControlNet

Lesson overview
Core Idea
How It Works
Positive Prompt Conditioning -> Apply ControlNet -> Ksampler Positive Input
Load Image -> Av ControlNet Preprocessor -> Apply ControlNet Image Input
Why It Matters
Build an Openpose-Guided Generation
Trade-Offs and Limitations
Key Takeaway

Integrating External AI Tools and Consistent-Face Workflows with InstantID

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Week 09 Detailed Workflow for AI Coding

Manage the LLM Context as a Limited Engineering Resource

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Reach a Shared Design Concept Before Requesting a Plan

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Create a Destination Document Without Turning It Into a Specification-to-Code Contract

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Turn the Destination Into Vertical-Slice Issues and a Dependency Graph

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Separate Human Planning from AFK Implementation

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Use Test-Driven Development and Feedback Loops as the Agent's Control System

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Review in a Fresh Context and Use Manual QA to Restore Human Judgment

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Shape the Codebase Around Deep Modules with Simple Interfaces

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Control Instructions with Push and Pull, and Prevent Documentation Rot

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Scale the Workflow with Planners, Isolated Implementers, Reviewers, and Mergers

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway
End-to-End Workflow Summary

Week 10 Setting Up an LLM Council

Use an LLM Council for Consequential, Ambiguous Decisions

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build the Decision Process Around Stochastic Consensus

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Create Perspective Diversity with Specialized Agent Prompts

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Install and Register the LLM Council Skill

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Operate the Default Single-Model Council

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Add Model Diversity with a Cross-Vendor Council

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Configure Cross-Vendor Access and Protect the API Key

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Run and Inspect the Cross-Vendor Workflow

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Choose Between Default and Cross-Vendor Mode

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Week 11 Advanced AI Engineering Workflows

Move from Tactical Programming to Strategic Programming

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Optimize the Harness, Not Only the Model

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Design Skills as Reusable Procedures Without Bloated Context

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Use Adversarial Interviewing Before Implementation

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build Stateful, Mission-Centered AI Learning Workflows

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Treat Human Knowledge, Skill, and Wisdom as the Performance Ceiling

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Run Scoped Agents Away from the Keyboard Inside Sandboxes

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Orchestrate Agent Work with Queues, Not Endless Loops

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Move Human Checkpoints Rightward While Preserving Review and Observability

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Keep Product Vision and Customer Discovery Human-Owned

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Week 12 How-To Guide: Hermes Agent

Distinguish the Model from the Hermes Agentic Harness

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Design Hermes as a Self-Improving AI Employee

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Choose a Runtime, Cost Model, and Recovery Path

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Grant Computer Access Without Surrendering Control

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build a Multi-Channel Operating Layer

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Shape Behavior with Identity Files and Profiles

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Engineer Durable, Time-Aware Memory with Honcho

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Add Observability and Deterministic Project Tracking

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Scale from One Agent to Profiles, Squads, and Model Routing

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Connect External Applications Through MCPs, CLIs, and APIs

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Turn Repeated Work Into Cron Jobs, Skills, and Agentic Workflows

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Use /Goal for Long-Horizon, Self-Checking Execution

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Assemble a Visual Creation and Deployment Stack

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build a Content Production and Distribution Engine

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Create Personalized Lead-Generation and Property Marketing Workflows

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Operate Community Management and Customer Support Agents

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build a Paper-Trading Agent with Separate Execution and Strategy Layers

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Build a Private Health Accountability System

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Create a Jarvis-Style Personal Command Center

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Trade-Offs and Limitations
Key Takeaway

Productize Hermes Systems as Outcome-Based Services

Lesson overview
Core Idea
How It Works
Why It Matters
Practical Application
Stress-Test and Decision Logic
Trade-Offs and Limitations
Key Takeaway

Course › Week 6 — Mastering the Essentials of Agentic Engineering › Design Autonomous Improvement as a Measured Experiment Loop › Baseline

WEEK 6 · LESSON 7 · TOPIC 9 OF 13 · Baseline

Baseline

Lesson progress

0% Complete

SECTION 1 OF 1

In this topic · 1 sections

Overview

Overview

The starting score and current best score.

← Previous topic Constraints Next topic → Reversal Method

Advanced Agentic AI Tools — 12-week learning module