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Bootcamps that produce engineers, not certificates.

Custom learning paths: applied AI, DevEx, platform engineering, prompt design. Real projects, not slides. Final evals, not attendance certificates.

Engagement2 — 8 weeks
Team1 — 2 senior
OutputPortfolio + measured skill
DisciplineProject-based + Eval
01 · The premise

Training that works produces artifacts. Everything else is entertainment.

Traditional courses teach information. Training that produces capability teaches practices, in short feedback cycles, with a real project as the pretext.

Our model is rooted in XP / learn-by-doing: every module has a lab, every lab has a deliverable, every deliverable is reviewed like a real PR. No multiple-choice quizzes.

The Extreme Contract of training: at the end of the bootcamp every participant has a portfolio of real artifacts they can show in an interview or reuse at work. Measured, not promised.

02 · What we deliver

What we deliver.

/01

Custom curriculum

Defined with the client based on real stack and goals. No "one size fits all" templates.

/02

Hands-on workshops

60% lab, 40% theory. Sessions happen on code, not slides.

/03

Capstone project

Every participant ships an end-to-end project using all the practices learned.

/04

Eval framework

Measurable skill assessment: pre/post bootcamp. Management sees the delta, not just classroom attendance.

/05

Reusable material

Repository of examples, sample ADRs, runbook templates — owned by the client.

03 · XP in action

How we operate.

XP / Pair Programming
Pair as a teaching method.

You learn by doing, in pairs, with a trainer who pairs with each person at least once a day.

XP / TDD
Write the test first, even in training.

The bootcamp isn't theory. Day one the participant writes a failing test. Day two they make it pass.

Contracts / Definition of Skill
Knowing ≠ being able to do.

We define at the start what "competent in X" means. We measure it with an executable task, not a quiz.

Contracts / Portfolio Output
Every participant leaves with artifacts.

Public repo (or client-private), signed ADRs, code in production or pre-production. Not promises — files.

04 · The contract

Pre-conditions, post-conditions, invariants.

Every engagement has explicit pre-conditions, measurable post-conditions, and invariants we never violate. You know what we need at the start, what comes out at the end, and what we don't negotiate in the middle.

Pre-conditions / what we need from you
  • Participants selected and committed to lab hours (not optional).
  • Measurable goal: what must they be able to do at the end?
  • Access to a real technical environment (cloud sandbox, dedicated repo).
  • Management that judges results on deliverables, not on attendance.
Post-conditions / what we guarantee
  • Portfolio of artifacts for each participant.
  • Documented skill assessment delta (pre/post).
  • Reusable repo material for future onboardings.
  • Structured feedback to management with next-step training plan.
05 · When it works

Right fit, wrong fit.

YESRight fit if…
  • You have a team adopting a new stack (AI, cloud, edge) and need a serious accelerator.
  • You want to build a sustainable internal academy.
  • You want to train new hires with a structured, measurable path.
  • You're willing to invest real hours — training that works isn't "in spare time".
NOWrong fit if…
  • You're looking for an after-hours optional course because "training is good for the company".
  • You want a certificate to hang on the wall — we don't issue certificates.
  • You have no real project to practice on.
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