Crafting Custom Agentic AI Solutions

Design and implement individual agents with AutoGen, LangGraph, and CrewAI frameworks. Agentic AI foundations cover key characteristics, the differences from traditional AI and RPA, benefits and...

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$3,000USD
Duration 3 days
Course Code GAI-3101
Available Formats Classroom, Virtual
Next Class: Sep 30, 2026

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Overview

Course Description

Design and implement individual agents with AutoGen, LangGraph, and CrewAI frameworks. Agentic AI foundations cover key characteristics, the differences from traditional AI and RPA, benefits and challenges, real-world applications, and potential impact across sectors. Agent architectures and frameworks cover reactive, deliberative, and hybrid architectures, framework comparisons, and the AutoGen, LangGraph, and CrewAI landscape. Memory, context, tool use, and function calling cover working, long-term, and episodic memory, advanced context management, the OODA loop applied to agents, observation versus action tools, direct and indirect tool-use methods, and validation. Planning, reasoning, and single-agent application design cover rule-based, goal-based, and utility-based planning, hierarchical task decomposition, reasoning under uncertainty across deductive, inductive, abductive, and case-based methods, architecture selection, testing, performance optimization, and error recovery. Hands-on labs produce simple agents, reactive agents in AutoGen, deliberative agents in LangGraph, a personal assistant agent, and a data-analysis agent. The course is designed for software developers and data scientists with Python and prior generative-AI experience.

Skills Gained

By the end of this course, participants will be able to:

  • Apply the fundamental concepts of agentic AI systems
  • Configure individual agents using reactive, deliberative, and hybrid architectures
  • Integrate memory management plus context handling into agent systems
  • Configure agents to use tools plus function calls for enhanced capabilities
  • Implement planning plus reasoning mechanisms in agentic applications
  • Build production-ready agentic applications through tested error-recovery patterns

Who Can Benefit

This course is designed for:

  • Software Developers
  • Data Scientists

Prerequisites

Participants should enter this course with:

  • Practical Python programming experience
  • GenAI application development experience (GAI-1101 or equivalent)

Organizational Objectives

This course assists organizations to:

  • Reduce time-to-prototype for agentic AI through working framework patterns and templates
  • Lower production failure rates through tested architectures plus deliberate error-recovery patterns
  • Build a working agentic-AI development discipline across the engineering team
  • Establish reusable single-agent patterns that compound across projects

Software

All attendees must have a modern web browser and an Internet connection.

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Course Details

Course Details

Introduction to Agentic AI and Autonomous Systems

By the end of this module, you will be able to define agentic AI, differentiate it from traditional AI and RPA, articulate its benefits and challenges, and reason about its impact on key sectors and complex problem solving.

  • Defining Agentic AI and its Key Characteristics
  • Differentiating Agentic AI from Traditional AI and Robotic Process Automation
  • Understanding the benefits and challenges of Agentic AI
  • Real-world applications of Agentic AI
  • Potential Impact of Agentic AI on Key Sectors
  • Agentic AI for Solving Complex Problems
  • Hands-on Lab: Implement a simple agent in Python and exercise round-robin communication between two agents.

Agent Architectures and Frameworks

By the end of this module, you will be able to compare reactive, deliberative, and hybrid agent architectures, design a blend of reactive and deliberative behaviour, and choose between AutoGen, LangGraph, and CrewAI for a given application.

  • Overview of Architectures - Reactive, Deliberative, and Hybrid
  • Comparison of Architectures
  • Exploring Reactive Architectures
  • Exploring Deliberative Architectures
  • Blending Reactive and Deliberative Architectures
  • Agentic Frameworks - AutoGen, LangGraph, CrewAI, etc.
  • Hands-on Lab: Implement a reactive agent in AutoGen alongside a deliberative agent in LangGraph and compare their behaviour.

Agent Memory and Context Management

By the end of this module, you will be able to recognize the role memory plays in agents, distinguish working, long-term, and episodic memory, supply memory to agents as context, and apply advanced context-management techniques.

  • The role of memory in agentic AI
  • Types of memory — working, long-term, episodic
  • Challenges of memory management plus limitations of simple memory models
  • Memory as a form of context
  • Supplying memory to agents as context
  • Advanced context management techniques
  • Hands-on Lab: Implement short-term memory and long-term memory in two agent variants and compare their behaviour on multi-turn tasks.

Tool Use and Function Calling in Agentic AI

By the end of this module, you will be able to apply the OODA loop to agent design, distinguish observation from action tools, use direct and indirect tool-use methods, blend agentic AI with function calls, require tool use, and validate inputs and outputs of tools.

  • The OODA Loop in Agentic AI - Observe, Orient, Decide, Act
  • Observation vs. Action Tools
  • Methods of Tool Use - Direct, indirect
  • Blending Agentic AI with Programming using Function Calls
  • Requiring Tool Use in Agents
  • Validating Inputs and Outputs of Tools
  • Hands-on Lab: Integrate one observation tool and one action tool into an agent and validate their inputs and outputs.

Planning and Reasoning in Agentic AI

By the end of this module, you will be able to recognize the role of planning, apply rule-based, goal-based, and utility-based planning, design hierarchical planning with task decomposition, and apply deductive, inductive, abductive, and case-based reasoning under uncertainty.

  • Role of Planning in Agentic AI
  • Types of Planning - Rule-Based, Goal-Based, Utility-Based, etc.
  • Hierarchical Planning and Task Decomposition
  • Reasoning in Agentic AI
  • Types of Reasoning - Deductive, Inductive, Abductive, Case-Based, etc.
  • Reasoning in Uncertain Environments
  • Hands-on Lab: Implement a hierarchical planning strategy and a rule-based reasoning agent on the same task.

Building Single-Agent Applications

By the end of this module, you will be able to design single-agent applications end-to-end, select architectures and frameworks suited to individual agents, test and debug agents, optimize performance, integrate them with other systems, and build error recovery patterns.

  • Designing single-agent AI applications
  • Selecting architectures and frameworks for individual agents
  • Testing, debugging, and performance optimization for single agents
  • Integration patterns for single agents
  • Error handling and recovery in single agents
  • Best practices for single agent development
  • Hands-on Lab: Build a personal assistant agent and a data analysis agent with deliberate error-recovery behaviour.

Schedule

2 options available

FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

The class and material is good. I think some of the software needs to be updated.

Exit certified was great as it is very in depth and hands on learning which made it very easy to learn this type of work.

The class covered the concepts needed for the AWS Cloud Practitioner Certification.

the course is good, covers many aspects, wish the lab is a little bit more in depth

The course was informative, and I learnt a new skill. The instructor was up to the point.