CF

AI Software Development with opencode

8h 17m 4s
English
Paid
Added to CourseFlix

AI Software Development with opencode is a 4-lesson 8 hours 17 minutes self-paced course by Jorge Miralles Fernández. AI Software Development with opencode is a practical course for developers who want to use artificial intelligence in programming without full dependency on cloud services, maintaining control over the code, data, infrastructure, and…

Course facts

Lessons
4
Duration
8 hours 17 minutes
Language
English
Added to CourseFlix
October 2026
Instructor
Jorge Miralles Fernández
Price
Premium

AI Software Development with opencode is a practical course for developers who want to use artificial intelligence in programming without full dependency on cloud services, maintaining control over the code, data, infrastructure, and development process.

About the Course

Modern software development using artificial intelligence is no longer limited to simple chatbot queries. To create reliable, secure, and scalable solutions, it's important to understand how to configure AI tools, isolate environments, manage context, and build the development process based on clear specifications.

In this course, you will learn opencode—an open AI agent for software development. It helps automate code writing, analyze projects, handle tasks, and accelerate functionality creation, while keeping you in control of architecture, security, and workflows.

What You Will Learn

  • How to use opencode for AI software development.
  • How to build a local and secure development environment.
  • How to launch an isolated environment using Docker.
  • How to work with AI not through scattered prompts, but through specifications.
  • How to apply BDD and SDD in real development tasks.
  • How to structure instructions for AI using the AGENTS.md file.
  • How to use Git Worktrees for parallel development of multiple features.
  • How to mitigate risks when working with an AI agent on the codebase.

Key Topics of the Course

Local AI Development Environment

You will learn to deploy a working environment where an AI agent can assist with development without sending unnecessary data to external services. This approach is especially important for teams working with private code, internal products, or projects with heightened security requirements.

Docker and Environment Isolation

The course shows how to use Docker to create a reproducible and secure environment. Isolation helps test changes, manage dependencies, and minimize the impact of AI experiments on the main development system.

Specification-Driven Development

Instead of chaotic text requests, you will learn the SDD approach—specification-driven development. This allows for more precise requirement formulation, more predictable outcomes from AI, and a reduction in errors during code generation.

Behavior-Driven Development

You will get acquainted with BDD principles and learn how to describe system behavior so that the AI agent better understands business logic, user scenarios, and expected outcomes.

AGENTS.md for Managing the AI Agent

Special attention is given to the AGENTS.md file. You will understand how to set rules, constraints, coding style, architectural principles, and instructions that help opencode work consistently and safely with the project.

Git Worktrees for Parallel Development

You will learn to use Git Worktrees to conduct multiple development directions simultaneously: testing different implementations, isolating tasks, and managing codebase changes more efficiently.

Who This Course Is For

  • Developers who want to integrate AI into their daily coding work.
  • Backend, frontend, and fullstack engineers interested in AI-assisted development.
  • Technical leads evaluating the secure use of AI within a team.
  • DevOps specialists working with local and containerized environments.
  • Anyone who wants to use AI tools without full reliance on closed cloud platforms.

Practical Outcome

After completing the course, you will be able to set up your own AI development environment with opencode, organize safe agent interaction with the project, describe tasks through specifications, and apply AI to accelerate software development.

You will gain a systematic approach to AI development: from environment preparation and agent operation rules to parallel function implementation and quality control of changes.

Why You Should Learn opencode

opencode helps you transition from random AI usage to a managed development process. Open approach, local setup, working with specifications, and integration with familiar tools make it a valuable solution for developers who value transparency, security, and flexibility.

The course will help you not just try AI in programming, but integrate it into a professional workflow to increase productivity while maintaining engineering control over the result.

Who teaches AI Software Development with opencode? Jorge Miralles Fernández

Jorge Miralles Fernández thumbnail

The author is a software engineer with over 15 years of experience in developing enterprise full-stack systems using C#, ASP.NET, and Azure, as well as creating machine learning solutions with Python. In his work, he adheres to the principles of clean code, the Agile approach, and modern DevOps practices, paying special attention to the reliability, security, and quality of software solutions.

In addition to his engineering activities, he is the founder of the EdTech startup Daktika Technologies SL and is actively involved in training specialists. Over the years, the author has spent hundreds of hours mentoring, helping more than 200 students master modern technologies through boot camps and corporate programs.

What lessons are included in AI Software Development with opencode?

This is a demo lesson (10:00 remaining)

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#1: 001 Starting (15 JULY)
All Course Lessons (4)
#Lesson TitleDurationAccess
1
001 Starting (15 JULY) Demo
03:04:17
2
002 Practice (17 JULY)
02:18:21
3
003 Complete workflow with Skills. Using Figma. (22 JULY)
03:43
4
004 API + Postgres - Render (24 JULY)
02:50:43
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Frequently asked questions

Do I need programming experience before starting?
You'll get more out of the course if you already write code and have some experience working in a software project. It's aimed at developers, with practical work involving Docker, Git Worktrees, an API, and Postgres rather than an introduction to programming. There isn't a formal prerequisite list, so don't assume you need to be an expert in every tool, but expect to engage with development workflows rather than just chat with an AI.
What will I actually get to practice?
You'll practice setting up an environment for an AI coding agent and giving it structured instructions instead of relying on disconnected prompts. That includes working from specifications, organizing project guidance in AGENTS.md, and using Git Worktrees to keep parallel feature work separate. Later sessions bring Figma into the workflow and work with an API, Postgres, and Render. The available outline doesn't establish one specific finished application, so don't choose it expecting a particular portfolio project.
Is this useful if I've already tried AI coding assistants?
Yes, if your next question is how to make an agent part of a controlled development process. The emphasis is on environment isolation, project context, specifications, and managing the risks of letting an agent work on a codebase. You'll encounter BDD and SDD as part of that approach. It's a closer fit for improving how you organize AI-assisted work than for simply collecting more prompts or comparing chatbot answers.
Will I work locally, or does everything depend on cloud services?
You'll work with a local development setup and use Docker to create an isolated environment. A central concern is keeping control over your code, data, and infrastructure rather than making the whole process dependent on cloud services. That doesn't mean every part is necessarily offline: Render also appears in the API and Postgres session. The outline doesn't specify model providers, hardware requirements, or whether a fully offline setup is possible.
Is this a course on training AI models?
No—the focus is using an AI agent to help develop software, not building or training the models behind it. You'll spend your attention on how opencode interacts with a project, how you give it instructions, and how you structure the surrounding development process. Model training, fine-tuning, and machine-learning theory aren't part of the stated scope. If those are your main goals, this isn't the right match based on the available outline.
How much time should I set aside?
The listed runtime is 8 hours and 17 minutes across four lessons. That's the viewing time, not a promise that you'll finish the practical work in the same amount of time. If you want to follow along with environment setup and try the workflows in your own codebase, leave extra room to pause and experiment. There's no separate estimate for exercises or setup, so your total commitment will depend on your familiarity with the tools.
What could I take back to my everyday development work?
The most reusable parts are ways to organize work around an AI agent: turning a task into a clear specification, providing persistent project instructions, isolating the working environment, and separating parallel changes with Git Worktrees. Those practices can inform how you approach other AI-assisted projects, even when the tooling differs. The hands-on setup is centered on opencode, though, so don't expect instructions that apply unchanged to every coding assistant.