Foundations

Foundations establishes the cohort. We build shared mental models, shared habits and shared standards. Before we build anything, we become a team. The kickoff in September is the year's emotional anchor — you meet each other, form the cohort, and set the bar for what Ignite means.

Learning objectives

Establish shared language and mental models for agentic AI
Learn Git workflow and CI/CD basics on client projects
Turn on traceability and responsible AI practice from day one
Build cohort dynamics that last the year

Core topics

01Responsible AI and the Ignite code
02Basic LLM use and prompt patterns
03Team work, DoR and DoD for AI delivery
04Tool setup: Git, VS Code, terminal, Python + Node

Technologies and frameworks

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

Sessions in this phase

Kickstart — physical gathering in September (2 days)
Intro masterclass on Responsible AI
First Dojo: 'what did I meet at the client in week one'

Artefacts Ignitere deliver

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

Courses in this phase

Shared coursesAll Ignitere

Responsible AI og Ignite-kodeks
Etabler grunnreglene for AI-arbeid: ansvar, sporbarhet, kundekonfidensialitet.
LLM-grunnmur og prompt-patterns
Fundamentet: hvordan LLM-er tenker, svarer og bruker kontekst.
Team-arbeid og DoR/DoD for AI
Ignite-lagets arbeidsvaner. Hva 'klar' og 'ferdig' betyr på et AI-prosjekt.

Track courses · Ignite Builder

Multi-provider stack: Anthropic, Azure, AWS
Hvorfor du bør snakke tre språk med LLM-er.

Cross-cutting threads

Consultant craft
EU AI Act practice

Phase 02Discover