Building Reliable AI Workflows

A practical 1-day workshop focused on reliability and operations. It assumes you already delivered a successful prototype, or received a demo that you believe fits your use cases precisely. The course will teach you how to ensure that the worlflow based on that AI capability is:

• Repeatable (less variance, fewer surprises)

• Testable (you can prove it works and detect regressions)

• Safe to run (guardrails + permissions + audit trail)

• Maintainable (versioning, monitoring, change control)

Who should attend

The course is equally suitable for technical and non-technical staff:

• Data Scientists treained in AI

• AI Engineers

• Managers and Business Analysts trained in Business Analysis for AI Solutions 

• AI Solution Architects 

Pre-requisites

The workshop doesn't teach:

• How to use LLM like ChatGPT

• How to implement RAG/GraphRAG solutions

• How to implement AI Agents

• How to create AI Solution Architecture

The attendants that have zero prior AI exposure are advised to attend one of the Practical AI Training courses. Contact us if you need advice

Approximate Agenda

Below is the starting point for customisation of thae course for you needs. Depending on your needs the training you receive can add some themes, skip some, and be reduced to 1 - 1.5 days

Day 1: Reliability foundations

• Workflow specification (states, I/O contracts, failure modes)

• Prompt patterns for stability (structured outputs, refusal/ask-more rules)

• “Reliability metrics”: what you measure and why (and what you can’t measure)

Day 2: Testing + safe automation 

• Evaluation harness build: golden set, rubrics, regression testing

• Testing RAG (if present): retrieval quality + grounding + injection resistance

• Testing agents/tool use (if present): permissions, confirmations, audit, rollback

• Operational checklist: monitoring, incident handling, change control