Our People

Richard Brown

Technical Director

Richard Brown is Technology Director at Audacia, bringing over 15 years of software engineering and enterprise delivery experience.

Richard is responsible for setting the technical direction across Audacia's projects, maintaining engineering and testing standards, and ensuring that architectural decisions align with best practice and long-term maintainability.

He works closely with delivery teams and senior client stakeholders across complex technology programmes, supporting operating model change and helping organisations align their technical landscape with their broader business goals.

Richard has played a central role in embedding AI within Audacia's engineering practices, leading tooling evaluation, process redesign, capability building and governance to help teams adopt AI safely, effectively and at pace. That work draws directly on lessons from real-world delivery across both engineering-led and AI-driven programmes.

Latest insights from Richard Brown

Engineer Experience: Why and How you Should Measure It

Richard Brown - 13/05/2026

Discover why measuring Engineer Experience matters and how to do it effectively – exploring how people, processes and tools shape productivity across software engineering teams.

Building What Matters – Reducing the 80% Feature Waste in Product Delivery

Richard Brown - 29/04/2026

Half of everything software teams build is wasted. This is a consistent finding across multiple studies and decades of data, and it should be the starting point for any conversation about digital product delivery. This article looks at why technology projects consistently lose focus on user outcomes, what the evidence says about the impact of user-centred delivery, and how engineering leaders can build the discipline of tying every feature to genuine user value.

AI-Assisted Engineering: Building the Foundations for Adoption and Scale

Richard Brown - 19/03/2026

Rolling out AI to engineering teams successfully depends on three interconnected phases: establishing solid foundations, executing a structured rollout and committing to continuous improvement. These observations come from our internal AI deployment at Audacia and supporting other organisations through similar transformations.

Testing AI: How to Effectively Evaluate LLMs

Richard Brown - 02/03/2026

This article examines why traditional software testing falls short for LLM-powered systems and what organisations need to do differently. It covers the scale of the hallucination problem, evaluation approaches for RAG and agentic AI systems, the emerging regulatory requirements around AI testing, and how engineering leaders can build the evaluation capability needed to deploy AI responsibly.