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Team training

Practical programmes built on your own code and your own processes. Taught by someone who still builds production software, not by someone who stopped ten years ago.

Abstract illustration of a graduation cap with lines reaching a group of people

The problem

Generic training is forgotten in a fortnight

A recorded course about a sample project does not change how a team works. What changes things is practising on the real codebase, with the real problems, and leaving with agreements that apply on Monday.

Signs this is you

  • The team uses new tools without shared criteria
  • Everyone solves the same problem a different way
  • Code review is either a formality or a source of conflict
  • Best practices live in a document nobody opens
  • Junior hires arrive with nobody to mentor them
  • Nobody has set any order around how AI is used in the team

What we do

What we do

Modern web development

JavaScript and TypeScript, Vue and Nuxt, front-end architecture, testing and Docker. With exercises built on your domain, not on a sample to-do list.

AI in daily work

How to use coding assistants and language models with judgement: where they help, where they get in the way, how to review their output and what conventions to set so the whole team moves together.

Engineering practice

Useful code review, version control, continuous integration, reproducible environments and technical debt management. What separates a team that ships from one that firefights.

Ongoing mentoring

Regular technical mentoring sessions on the team’s real work — more useful than an intensive course that fades.

8+ years
leading and mentoring engineering teams
Bootcamp
lead front-end teacher at Ironhack
ES/CA/EN
languages of delivery

How we do it

How we do it

  1. Team assessment

    Short interviews and a look at the code to find where the team actually stands, beyond what the org chart says.

    DeliverableTailored programme

  2. Practical sessions

    Short theory blocks and a lot of guided practice, on one of your repositories or a replica of it.

    DeliverableMaterial and exercises

  3. Written agreements

    Each block ends in concrete decisions: conventions, templates, checklists. Training that leaves a trace in the repository.

    DeliverableTeam conventions

  4. Follow-up

    A review session four to six weeks later to see what stuck and what fell by the wayside.

    DeliverableAdoption review

Technologies

  • JavaScript
  • TypeScript
  • Vue.js
  • Nuxt
  • PHP / Laravel
  • Docker
  • Git
  • CI/CD
  • AI tooling

FAQ

What people ask us

On site or online?

Both. The practical format works well remotely with small groups; for teams above eight people, or for kick-off sessions, on site gets more out of it.

What group size?

Between four and twelve. Below that, individual mentoring is better value; above it, the hands-on part suffers, which is exactly what makes the training work.

Can you train non-technical people?

Yes, especially in applied AI and in understanding technical decisions. It is one of the most frequent requests from leadership and operations teams.

Is the material tailored?

Always. The skeleton is reused, but exercises and examples are built on your domain and, where possible, on your own code.

Next step

Half an hour well spent

Walk us through the problem on a short call. You leave with a first read on how we'd approach it and what it would involve — no commitment, no sales deck.