AI Coding Training for Teams

Since releasing our AI Coding Training, we’ve received overwhelmingly positive feedback from participants. Shortly after launching the training for individual developers, engineering managers and tech leads began asking for a structured way to adopt the workflow across entire teams. Today, we are excited to introduce our AI Coding Training for Teams — a guided program that helps engineering organizations move beyond ad-hoc prompting and adopt a shared, reliable workflow for AI-assisted development.

Why Teams Struggle With AI Coding

Most organizations are now experimenting with AI coding tools such as Copilot, Cursor, Claude Code, Windsurf, Theia IDE, and others. While some developers achieve good results, others see AI behave unpredictably, produce partial or architecture-breaking code, or require multiple retries to get something usable.

The result is familiar:

• every developer uses AI differently
• outcomes vary widely across people and projects
• onboarding becomes harder, not easier
• quality depends on individual prompting habits
• experimentation doesn’t scale beyond early adopters

This might be acceptable in small demos.
In real, long-lived codebases, it’s a serious obstacle.

Teams told us clearly:

“We don’t need more tools — we need a workflow to use them efficiently.”

The Structured Workflow Behind the Training

The AI Coding Training is built around a structured, tool-agnostic workflow also referred to as the Dibe Coding methodology.

It teaches a complete end-to-end process for using AI productively in real projects — not just prompt patterns or isolated tricks. The workflow covers:

• Decide which tasks to delegate and how to scope them
• Define tasks clearly through Task Engineering and Context Engineering
• Invoke AI coding tools effectively and reuse context across iterations
• Review & Decide on the right next step from predictable options
• Follow up until a high-quality result is reached and integrated

Participants also learn a fundamental understanding of how AI coding agents operate, enabling teams to apply the method across any current or future tool.

This is especially important for teams because:

1. The workflow is tool-agnostic, so it survives changing tools and LLM generations.
2. It creates a shared vocabulary and structure that aligns developers, tech leads, and architects.

After completing the training, teams can talk about AI coding decisions using the same concepts — instead of relying on ad-hoc personal habits.

From Individual Learners to Team Adoption

The training is built on years of hands-on experience introducing and refining AI coding workflows across real-world projects. Previous participants included:

• senior engineers wanting predictable results
• developers stuck in trial-and-error prompting
• team leads trying to introduce AI coding within their teams

The feedback is strong:

💬 “It bridges the gap between experimentation and reliable practice — exactly what we needed to turn AI from hype into day-to-day productivity.” — Engineering Manager

💬 “A didactic masterpiece.” — Dr. David Faragó, inventor of Vise-Coding on the Dibe Coding Training

💬 “The training not only teaches the technical process but also addresses the emotional side of AI adoption. It helps experienced developers feel secure in their role and shows how their creativity and structure remain central.” — Team Lead, Industrial Software Division

This raised a new question:

“How do we get everyone on the team aligned on an efficient AI-native development workflow?”

That’s the purpose of the AI Coding Training for Teams.

AI Coding Training for Teams — Two Ways to Get Started

Organizations can adopt the training in two complementary ways.
Both options start with access to the online course, which teaches the complete workflow through structured lessons and real-world examples.

You can choose the level of support that matches your goals — and switch or combine options at any time.

Option A — Course-only (self-paced team training)

In this option, you:

• purchase course seats for your developers
• integrate the training into your internal learning programs
• let internal champions or tech leads guide adoption

This works well for:

• smaller teams
• pilot groups
• organizations with existing enablement structures

Each developer receives full course access and can progress at their own pace — while still using the same structured workflow and vocabulary.

👉 **Details & team course access

We support invoice-based purchases, procurement processes, and structured team rollouts (see option B).

Option B — Guided adoption package (workshops + hands-on support)

For teams who want structured rollout support, we offer a guided adoption package that builds on the course and adds tailored services:

• Leadership briefing (optional)
• Environment & tooling enablement workshop
• Hybrid training day with live Q&A sessions
• Custom demo using your own project or codebase
• Follow-up Q&A after two weeks of real usage

The goal is to help your team:

• move beyond isolated experiments
• establish a shared workflow for AI-assisted development
• adapt the method to your architecture and codebase
• align on best practices and guardrails

Guided adoption packages start at €2,900 per team
(plus individual course seats).

👉 Talk to us about the guided adoption package

👉 Learn more about the team training

Which Option Should You Choose?

Both options help teams adopt AI coding professionally and sustainably.

In our experience:

• Course-only is ideal for motivated teams with internal champions.
• Guided adoption is best when you want faster alignment, multiple teams involved, or support adapting the workflow to your environment.

If you’re not sure which option fits, we’re happy to discuss your situation.

How to Get Started

If your team wants to move beyond trial-and-error prompting and adopt a reliable AI coding workflow, this training provides the structure you’ve been missing.

Three simple entry points:

1. Explore the team training page

2. Start a small pilot
   Provide course access to 5–10 developers and review the outcome.

3. Talk to us about guided adoption
   or email [email protected]

AI is changing how developers work — but structure, clarity, and engineering judgment remain essential.
Our goal is to help teams keep these strengths at the center while using AI productively and confidently.

We’re looking forward to supporting your team’s adoption journey.