TRAINING FOR
AI DEVELOPMENT

We train your team to build with AI in production: maintaining architecture control, avoiding context loss, and optimizing model usage.

Visual Studio Code+GitHub+Open Router / Opper

Autonomous Dev (AI-Driven)

Delegating complete control to AI (a practice known as Vibe Coding, heavily promoted by autonomous agents from platforms like Claude) works exceptionally well for rapid prototyping from scratch. However, applying this blind autonomy in real production environments and legacy code is not only highly dangerous, but also very expensive.

Models lose project context after a few interactions, burning thousands of tokens unnecessarily.
They introduce unapproved dependencies and alter architecture without supervision (Architecture drift).
Generate infinite repair loops where they break more code than they fix, skyrocketing inference costs.

Assisted Dev (AI-Assisted)

The only disciplined and viable operational model for corporate software development. AI is used to drastically accelerate the execution of complex tasks, legacy code investigation, and boilerplate writing, but engineers maintain absolute responsibility over design, security, and strategic decisions.

The AI: Investigates code, proposes implementation plans, generates blocks, and audits diffs.

The Human: Sets the context, chooses the right model, approves the architecture, and ensures security.

THE CURRICULUM

A structured program in 4 theoretical-practical sessions where the team will apply theory directly to your own code, followed by a dedicated supervision phase.

Setup, Tooling & Instructions

1.5h · Admins & Tech Leads

We establish operational foundations. We teach how to configure tools like GitHub Copilot and gateways like OpenRouter to control which models are used, isolating costs and securing the corporate environment.

Model selection by cost/complexity (DeepSeek vs OpenAI).

Privacy rules and budget caps.

.github/copilot-instructions.md creation: Persistent context ensuring AI respects architecture and business rules in every prompt.

Frontend Engineering & Controlled UI/UX

2.0h · Entire Team

How to transform product requirements or screenshots into maintainable code without generating monstrous 800-line components.

Component mapping and Design Systems.

Strict separation of state (logic) and view.

Real product states: Forcing AI to code Loading, Empty, Error, and Unauthorized states it typically forgets.

Quality, Auditing & Security

1.5h · Entire Team

We use AI to accelerate analysis and code review, not just generation. Teach your team to audit PRs and protect the security perimeter.

AI-Assisted Code Reviews (Diffs).

Security audits and authorization (RBAC).

Sensitive Boundary: Techniques so passwords, tokens, and production .env files never enter the model's context.

Debugging & Testing with AI

2.0h · Entire Team

How to use AI to accelerate reasoning when facing a bug without falling into infinite repair loops where the AI breaks a different file on each attempt.

Root-cause analysis.

Test Matrix generation.

Stop Conditions: When to stop the AI, discard changes, and rethink the problem.

4 Weeks of Production Supervision

The training does not end with theory. During the month following the sessions, we actively accompany the team by auditing the prompts, token consumption, and models used in their daily work, allowing us to redirect and optimize the development strategy.

Week 1: Intensive SupervisionReview of real prompts, correction of context leaks, and oversight of proper model selection to reduce token spending and fine-tune results.

Weeks 2 to 4: Follow-up & HandoverWe continue supervision at a lower intensity, progressively handing over monitoring responsibilities to the company's Tech Lead to guarantee team autonomy.

Complete Training Program

Accelerate your technical team's delivery without losing control over your code or skyrocketing inference costs.

4 Practical Sessions (Remote)

Up to 8 Developers

4 Weeks of Production Supervision

Flat Corporate Fee

2,800 €