Practical AI Adoption for Software Developers

Why this course exists

Adopting AI as a developer isn't hard — but the exploration phase does consume valuable time. Testing tools, figuring out which ones actually work, discovering the patterns that produce consistent results, building a workflow that makes sense: all of that can take months of trial and error.

This course exists so you don't have to go through that alone.

Jorge Domínguez has spent over two years working daily with Claude Code, Claude AI and the tools in the AI-assisted development ecosystem. What he teaches here isn't theory or official documentation: it's the distillation of what he wished he'd had from day one — the patterns that work, the mistakes not worth making, and a proven workflow framework you can start using the very next day.

When the course ends, participants don't leave with an introduction: they leave with an operational foundation ready to use — a technical prompt system, an agentic workflow, and the structural understanding of how to integrate AI into their daily work as developers.

What makes this course different

Learning outcomes

By the end of the course, participants will have strengthened their ability to:

1. Understand the developer's new role Grasp how the engineer's profile shifts in an AI-assisted development context.
2. Build effective technical prompts For code generation, debugging, refactoring and technical documentation.
3. Use Claude Code and Claude AI as co-pilots Inside real engineering workflows, not just as Q&A chatbots.
4. Apply the BMAD framework To structure AI-assisted projects in an organized and scalable way.
5. Understand the MCP protocol And its integration possibilities with real tools and development environments.
6. Integrate AI into the daily workflow In a sustainable and progressive way, without breaking existing processes.
7. Solve an end-to-end practical case Applying all course knowledge in the closing integrative workshop.

Course content

6 modules, 24 hours. Progressive structure: each module builds on the previous one toward the integrative workshop.

1. Introduction to AI adoption for developers Current landscape of AI-assisted software development. Evolution of the developer role toward an AI-assisted profile. Comparative tool exploration (Claude Code, Claude AI, Google AI Studio) and identification of daily-work opportunities. 3h — 1h conceptual / 2h hands-on.
2. Practical prompting for engineering and development Fundamentals and advanced techniques: multi-step prompts, chain-of-thought, few-shot. Building prompts for code generation, debugging, refactoring and documentation. Personal reusable prompt library. 4h — 1.5h conceptual / 2.5h hands-on.
3. AI-assisted development with Claude Code and Claude AI Practical use of Claude Code and Claude AI as co-pilots in realistic engineering workflows. Prototyping, analysis, code generation, refactoring and assisted documentation. The most intensive module of the course. 6h — 2h conceptual / 4h hands-on.
4. Applied introduction to the BMAD framework BMAD as a structure for organizing AI-assisted development work. Framework phases, relationship between discovery, design, execution and continuous improvement. Guided structuring exercise. 3h — 1h conceptual / 2h hands-on.
5. Integrating agents with tools and environments: introduction to MCP Concept and value of connecting agents to real tools. MCP as an integration protocol. Use cases with IDEs, repositories, AWS, Jira and other environments. Identifying your own integration opportunities. 4h — 1.5h conceptual / 2.5h hands-on.
6. Integrative practical workshop Guided end-to-end case that consolidates prompting, AI-assisted development, BMAD and integration vision. Workflow design, tool application, results sharing and adoption recommendations. 4h — 0.5h conceptual / 3.5h hands-on.

Hour breakdown by module

Methodology

The course combines conceptual foundations with intensive practical application, ensuring actionable operational skills from the very first session:

Course tools

The course is designed for participants with a Claude Pro subscription, which includes full access to Claude.ai and Claude Code.

Note: Participants must have an active Claude Pro subscription before the course starts. The instructor will guide the initial Claude Code setup in the first session.

Who is this course for?

This course is aimed at software developers who want to incorporate artificial intelligence into their daily workflow.

Recommended profile

• Software developers with practical experience in at least one programming language
• Software engineers, development analysts and solution architects
• Tech professionals who write or review code regularly
• DevOps, QA or related professionals interested in AI-assisted automation

No prior experience with AI tools is required, but willingness to experiment is essential.

Prerequisites

• Basic programming knowledge in any language
• A computer with a stable internet connection
• Familiarity with a development environment (IDE, terminal or code editor)

About the instructor

Jorge Domínguez — Independent Consultant & Instructor in Generative AI and Agentic Development. Systems Engineer with over 15 years of experience in software development, solution architecture and technology innovation. MBA from the University of Leipzig (Germany). Graduate of the MIT xPRO executive program "Designing and Developing AI Products and Services" (2025).

Has trained over 60 companies and institutions — including Bancolombia, Comfandi and Universidad de los Andes — in AI adoption at three levels: C-Level, Senior Management and Innovators. Led the continuing education area in AI for professionals and organizations at Universidad de los Andes.

Currently works as an AI Solution Architect implementing workflows with MCP, AI agents and cloud-native architectures on AWS. Uses Claude Code, Claude AI, Cursor and ChatGPT daily in real production projects.

Certifications

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