Schița de curs
Block 1 — Shared Foundations (Days 1–2)
Day 1 — Morning: The Human Factor in AI Adoption
• Trust / reliance calibration: when to use AI, when to stop.
• Team agreement structure (trigger / action / evidence / owner).
• Prompt Curator role: validation, decision, sign-off. AI incident response plan.
Day 1 — Afternoon: Constraints, Risks and Compliance
• Real LLM capabilities — prompt risk vectors: injection, data leakage, hallucinations.
• Legal framework: GDPR, EU AI Act — sector standards (DICOM, HL7, HIPAA).
• Practical exercise: translate a domain standard into a prompt guardrail.
Day 2 — Morning: Technical Architecture of Prompts
• Agent architecture: memory, context, goals — from a prompt design perspective.
• API integration and domain data sources, multi-agent and prompt chaining.
Day 2 — Afternoon: Enterprise Prompt Anatomy
• The 6 layers: Role / Context / Constraints / Domain Standards / Format / Examples.
• Prompt hierarchy: System (org-wide) — Domain (team) — Task (individual).
• Demo: deconstruct a naive prompt, rebuild it. Team brief for Days 3–5.
Block 2 — Co-Construction Workshops (Days 3–4–5)
Day 3 — Discovery and Standards Audit
- Parallel team workshops: Architects, Domain-Specific Devs, Back-End, QA.
- Mapping enterprise standards and constraints — identifying cross-team conflicts.
- Day 3 Deliverable: Standards Map + impact/effort priority matrix.
Day 4 — Convention Design and Template Construction
- Naming conventions, versioning, tag system (team, domain, target tool).
-
Building first validated templates: TypeScript DICOM, code review, QA tests, API
documentation. - Day 4 Deliverable: 4+ operational templates + conventions guide.
Day 5 — Library Assembly, Governance and Official Handover
- Library organization, GitHub Copilot / Cursor / internal LLM API integration.
- Prompt Curator role, quality metrics, team rituals, 30-day deployment plan.
- Final Day 5 Deliverable: Documented Library v1.0 + Governance Charter + 30-Day Plan.
Cerințe
- Having completed at least one AI training (introductory or advanced).
- Technical profiles: development experience in the company's stack.
- Management profiles: basic familiarity with AI tools (ChatGPT, Copilot, etc.).
- Company commitment: active participation of team leaders in Days 3–5.
- Prior provision: existing standards documentation (README, coding guides).
Target audience
- Software architects
- Developers (domain-specific, back-end, front-end)
- QA engineers / Code technicians
- Team leaders and middle managers
- IT managers, decision-makers and AI project leads
Mărturii (2)
Am dobândit cunoștințe despre biblioteca Streamlit din Python și cu siguranță voi încerca să o folosesc pentru a îmbunătăți aplicațiile din echipa mea, care sunt realizate în R Shiny.
Michal Maj - XL Catlin Services SE (AXA XL)
Curs - GitHub Copilot for Developers
Tradus de catre o masina
Formatorul este capabil să ajusteze nivelul cursului în timpul instruirii pentru a se potrivi nivelului nostru de înțelegere al temei, astfel încât să putem dobândi cunoștințe mai utile care ne vor ajuta ulterior să folosim instrumentele în munca noastră zilnică.
Tatt Juen - ViTrox Technologies Sdn Bhd
Curs - Intermediate GitHub Copilot
Tradus de catre o masina
