Course Outline
Module 1 — Shared Foundations (Days 1–2)
Day 1 — Morning: The Human Element in AI Adoption
• Trust and reliance calibration: determining when to utilise AI and when to exercise restraint.
• Structuring team agreements (trigger / action / evidence / owner).
• The Prompt Curator role: validation, decision-making, and sign-off. AI incident response planning.
Day 1 — Afternoon: Constraints, Risks, and Compliance
• Realistic LLM capabilities—prompt risk vectors: injection, data leakage, and hallucinations.
• Legal frameworks: GDPR, EU AI Act—and sector standards (DICOM, HL7, HIPAA).
• Practical exercise: translating domain standards into prompt guardrails.
Day 2 — Morning: Technical Architecture of Prompts
• Agent architecture: memory, context, and goals—viewed from a prompt design perspective.
• API integration and domain data sources, multi-agent systems, and prompt chaining.
Day 2 — Afternoon: Enterprise Prompt Anatomy
• The six layers: Role / Context / Constraints / Domain Standards / Format / Examples.
• Prompt hierarchy: System (organisation-wide)—Domain (team)—Task (individual).
• Demonstration: deconstructing a basic prompt and rebuilding it. Briefing for the team for Days 3–5.
Module 2 — Co-Creation Workshops (Days 3–4–5)
Day 3 — Discovery and Standards Audit
- Parallel team workshops: Architects, Domain-Specific Developers, Back-End, QA.
- Mapping enterprise standards and constraints—identifying conflicts between teams.
- Day 3 Deliverable: Standards Map + impact/effort priority matrix.
Day 4 — Convention Design and Template Construction
- Naming conventions, versioning, and tag systems (team, domain, target tool).
- Creating initial validated templates: TypeScript DICOM, code review, QA tests, and API documentation.
- Day 4 Deliverable: 4+ operational templates + conventions guide.
Day 5 — Library Assembly, Governance, and Official Handover
- Library organisation, GitHub Copilot / Cursor / internal LLM API integration.
- Prompt Curator role, quality metrics, team rituals, and 30-day deployment plan.
- Final Day 5 Deliverable: Documented Library v1.0 + Governance Charter + 30-Day Plan.
Requirements
- Completion of at least one previous AI training module (introductory or advanced).
- Technical roles: Relevant development experience within the company’s technology stack.
- Management roles: Basic familiarity with AI tools (e.g., ChatGPT, Copilot).
- Organisational commitment: Active involvement of team leaders during Days 3–5.
- Preparation: Availability of existing standards documentation (e.g., README files, coding guides).
Target audience
- Software architects
- Developers (domain-specific, back-end, and front-end)
- QA engineers and code technicians
- Team leaders and middle managers
- IT managers, decision-makers, and AI project leads
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customised Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from £8000 + VAT*
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Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
