--- url: "https://xcademia.com/courses/genai-developer" title: GenAI Developer description: "Build production-ready GenAI apps in 4 days: RAG, tool calling, guardrails, evaluation, and prompt-to-product delivery in mentor-led labs with real-world labs." publishedAt: "2026-02-12T23:08:26.547947+00:00" updatedAt: "2026-03-30T22:50:53.7265+00:00" type: course code: "AID-0009" level: Professional duration_days: "4" track: "Generative AI & Prompt Engineering" category: "AI, Data & Analytics" credential_tier: tier1 price_gbp: "2199" --- # GenAI Developer > Build real GenAI applications end to end, from prompt-to-product delivery through retrieval, tools, and production-ready workflows. Apply guardrails, evaluation, and safe integration patterns using mentor-led labs and practical scenarios. ## Overview GenAI Developer (X-GAD) is a hands-on programme for engineers and builders who want to deliver GenAI applications that work reliably in real environments. It focuses on the full prompt-to-product workflow: shaping requirements, choosing the right patterns, building a usable baseline, and iterating with evidence. Delivered in a mentor-led format, you will build practical solutions using common building blocks such as retrieval, tool use, and structured outputs. You will learn how to design user journeys, handle failure modes, and integrate GenAI safely into business processes, rather than treating the model as a standalone chatbot. A key theme throughout is controlled behaviour and operational safety. Prompt injection and unsafe downstream actions are recognised risks in LLM applications, so you will practise guardrails, least-privilege tool design, and output handling that reduce impact in real deployments. ## Prerequisites - Confidence with Python or JavaScript basics. - Familiarity with APIs and JSON payloads. - Helpful: basic web app concepts. ## What you will learn - Design GenAI solutions aligned to user needs. - Implement retrieval and tool patterns safely. - Analyse failure modes and reduce risky behaviour. - Evaluate quality using repeatable test methods. - Communicate decisions, limits, and trade-offs clearly. - Lead prompt-to-product delivery with iteration discipline. ## Skills you will gain - Prompt-to-product delivery workflow - Structured output and validation - Retrieval design and grounding - Tool calling and action gating - Agent workflow orchestration basics - Prompt injection risk handling - Guardrails and policy enforcement - Evaluation sets and regression checks - Observability and audit logging - Release and versioning discipline ## Career progression - GenAI Developer - Applied AI Engineer - LLM Application Engineer - AI Product Engineer - ML Engineer (Product) ## Curriculum 1. **Module 1: Getting Ready** - Development setup and reference architecture for GenAI apps - Data safety, privacy awareness, and logging basics - What “good” looks like: baseline, eval, iterate 2. **Module 2: Prompt-to-Product Workflow** - Converting user needs into prompts and behaviours - Defining success criteria and measurable outcomes - Designing a minimal, usable baseline 3. **Module 3: Structured Output and Reliable Responses** - Output schemas and validation thinking - Handling uncertainty and safe refusals - Writing prompts for consistency and clarity 4. **Module 4: Retrieval for Real Use Cases** - When retrieval is the right pattern - Chunking, search intent, and grounding responses - Reducing hallucinations through evidence-first design 5. **Module 5: Tool Use Patterns** - Tool selection: what to automate vs summarise - Parameter validation and safe defaults - Tool results handling and user confirmation flows 6. **Module 6: Agentic Workflows Without Chaos** - Single-step vs multi-step orchestration - Planning, execution, and verification loops - Timeouts, retries, and failure recovery patterns 7. **Module 7: Guardrails and Abuse-Resistance** - Prompt injection risk and mitigation strategy - Least-privilege tool design and action gating - Output handling controls and safe rendering 8. **Module 8: Evaluation and Quality Management** - Creating test sets from real user intents - Golden responses, rubric scoring, and regression checks - Measuring quality, latency, and cost trade-offs 9. **Module 9: Production Readiness and Operability** - Observability: traces, audits, and error taxonomy - Feedback loops and continuous improvement workflow - Release practices: prompts as versioned assets 10. **Module 10: Capstone Build and Mentor Review** - Build a complete GenAI app with retrieval and tools - Add guardrails, evals, and deployment checklist - Present decisions, limitations, and next iteration plan ## Exam & certification This is an Xcademia role-based programme focused on applied capability. Learners receive a Certificate of Achievement upon successful completion of the capstone and participation requirements. ## Delivery options - **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible. - **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more. - **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning. - **Blended** — Combine online and in-person learning for maximum flexibility and impact. ## Frequently asked questions **Is this aligned with any certification?** This is a role-focused programme aligned to industry GenAI engineering practices, not a vendor exam. **Who is this for?** Developers, engineers, and technical professionals building GenAI features or internal assistants for real workflows. **What experience do I need?** You should be comfortable with basic coding and APIs. The course is practical and build-led. **Is it hands-on or theory-heavy?** Hands-on and mentor-led, with real app builds, debugging, and hardening through practical scenarios. **Can this be delivered to teams?** Yes. We can tailor tools, data sources, and guardrail requirements to your environment and governance needs. ## Course at a glance | Field | Value | | --- | --- | | Code | AID-0009 | | Duration | 4 days | | Level | Professional | | Track | Generative AI & Prompt Engineering | | Category | AI, Data & Analytics | | Credential tier | tier1 | | Price (GBP) | £2199 | --- ## About this content This Markdown course profile is the citation-grade twin of [GenAI Developer](https://xcademia.com/courses/genai-developer). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite. When citing or quoting, please attribute *Xcademia* and link back to the source URL above. - Source: https://xcademia.com/courses/genai-developer - Publisher: Xcademia — https://xcademia.com - Catalogue index: https://xcademia.com/llms-full.txt