In this third session of the Let’s Talk Knowledge Engineering series, Ben Taylor, Rainbird CTO and co-founder, is joined by Lucie Hunt, VP Enablement at Rainbird, to explore the practices that help knowledge engineering projects scale from early ideas into reliable production systems.
Together, they look at how strong knowledge architecture, clear graph design, disciplined testing, and structured change management help teams build models that are easier to reuse, maintain, and extend over time. The session focuses on what good looks like in practice, from setting knowledge boundaries and layering expertise through to designing graphs that stay clean and manageable as they grow.
You can register for the remaining sessions in the series here or watch past episodes.
What you’ll learn
- Why knowledge architecture is a design discipline, and how setting the right boundaries helps graphs scale and remain maintainable.
- How layering knowledge across foundational, domain, policy, and jurisdictional levels improves reuse and reduces duplication.
- Why separating knowledge from data matters, and how it enables the same reasoning models to be applied across different systems and use cases.
- What practical graph design best practices look like, including naming conventions, reusable concepts, rule design, and graph hygiene.
- How testing, versioning, and structured change management help keep knowledge graphs reliable as requirements evolve.
Resources shared in the webinar
- Rainbird Studio Community Edition: Experiment, model, and bring decisions to life, visit app.rainbird.ai
- Rainbird Academy: Learn the foundations of explainable decision intelligence, visit academy.rainbird.ai
- Rainbird Forum: Ask, discuss, and shape the conversation, visit forum.rainbird.ai