Generative AI for Software Engineering Teams
- Intended audience
- Software engineers, technical leads and product teams exploring practical AI-assisted delivery.
- Learning outcomes
- Understand useful AI engineering workflows; Identify risk areas such as privacy, evaluation and reliability; Map realistic adoption steps for the team
- Prerequisites
- Basic software delivery experience.
- Session format
- Interactive workshop with discussion and practical exercises adapted to the team context.
- Hands-on exercises
- Prompting, workflow design, review checklists and small implementation patterns where appropriate.
- Take-home material
- Reusable notes, exercises or reference material aligned with the selected topic.
- Availability
- Available online; on-site requests can be discussed based on location and schedule.
- Customisation
- Examples can be adjusted for the team stack and product context.
Building Applications with LLMs
- Intended audience
- Teams planning AI-enabled product features.
- Learning outcomes
- Understand LLM application architecture; Separate deterministic product logic from model output; Plan evaluation and fallback behaviour
- Prerequisites
- Working knowledge of web applications or APIs.
- Session format
- Workshop or technical session, scoped after discovery.
- Hands-on exercises
- Architecture mapping, structured output design and review of common failure cases.
- Take-home material
- Take-home checklists or starter patterns can be included after scope confirmation.
- Availability
- Available online; on-site requests can be discussed based on location and schedule.
- Customisation
- Can focus on RAG, agents, forms, search or internal automation.
Agentic Development for Engineering Teams
- Intended audience
- Software teams exploring AI agents, coding assistants and tool-using workflows inside real engineering delivery.
- Learning outcomes
- Identify where agentic workflows are useful and where they add risk; Design task boundaries, tool access, review loops and fallback paths; Evaluate agent output for correctness, security, maintainability and cost
- Prerequisites
- Experience with software delivery, code review or technical product workflows.
- Session format
- Practical workshop or technical session focused on applying agentic patterns to realistic engineering tasks.
- Hands-on exercises
- Workflow decomposition, prompt and context design, tool-use boundaries, human-in-the-loop review and failure-case analysis.
- Take-home material
- Reusable checklists, evaluation criteria and implementation notes for applying agentic workflows responsibly.
- Availability
- Available online; on-site requests can be discussed based on location and schedule.
- Customisation
- Can be tailored for product engineering, internal developer tooling, AI-assisted code review, documentation workflows or support automation.
Full-Stack Architecture with React, Node.js and Python
- Intended audience
- Engineering teams and senior developers improving product architecture.
- Learning outcomes
- Reason about frontend/backend boundaries; Design maintainable APIs and data flows; Improve review and delivery habits
- Prerequisites
- Experience building production web applications.
- Session format
- Practical technical workshop or internal training session.
- Hands-on exercises
- Architecture review, decomposition exercises and implementation planning.
- Take-home material
- Architecture notes and review checklists can be shared after scope confirmation.
- Availability
- Available online; on-site requests can be discussed based on location and schedule.
- Customisation
- Can be tailored to React, Next.js, Node.js, Django, FastAPI or team-specific stacks.
