Ignite26/27
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Phase 01

September 2026

Foundations

Foundations establishes the cohort. Onboarding on 1–4 September lays the groundwork: the cohort meets, teams form and expectations are set. The month holds the two shared courses the rest of the year rests on — what a language model actually does, and what responsibility comes with putting one into production at a client.

Learning objectives

  • Establish shared language and mental models for working with language models
  • Explain where an LLM fails — hallucination, bias and drift
  • Know the responsibility that follows an AI delivery: traceability, risk classes and client confidentiality
  • Build cohort dynamics and working habits that last the year

Core topics

  • 01Responsible AI: risk, traceability and the EU AI Act in practice
  • 02LLM Foundations: how the models work, and prompt patterns
  • 03Onboarding: team formation, expectations and shared standards
  • 04Dojo and Frontier Friday get under way

Technologies and frameworks

  • Anthropic Claude · OpenAI · local development
  • OpenTelemetry principles · basic tracing
  • GitHub organisation · PR flow

Sessions in this phase

  • Onboarding — in-person gathering 1–4 September (4 days)
  • Introductory masterclass on Responsible AI
  • First Dojo: 'what I met at the client in week one'

Artefacts Ignitere deliver

  • 01Personal learning plan for the year
  • 02First GitHub repo with structured agent project
  • 03Reflection after Onboarding: where am I, what do I want out of this

Courses in this phase

Shared coursesAll Ignitere

  • Responsible AI

    Establish the ground rules for AI work: accountability, traceability, client confidentiality.

  • LLM Foundations

    The groundwork: how language models reason, answer and use context.

Cross-cutting threads

  • Consultant craft
  • EU AI Act practice
Phase 02Discover