They Define It, We Defend It: QA for AI Systems | 28th Calgary Meetup

When the intelligence in a product is defined outside engineering, testing becomes more complicated.

A credit risk team may own the adjudication rules. An R&D team may own the extrapolation model. Developers implement the logic, QA verifies it, but the people best qualified to confirm whether the result is correct may not be part of the testing process at all.

At The Test Tribe’s 28th Calgary Meetup, Ian Percival will explore how QA teams can bring domain experts directly into the validation process before incorrect logic reaches production.

## Event Details

Date: 26th August 2026
Time: 5:30 PM – 7:30 PM MT
Venue – Central Library, 3-16B, 800 3 St SE, Calgary, AB T2G 2E7

What's on the agenda?
Session:
They define it; we defend it.
Speaker:
Ian Percival,
Director of Software Engineering, Highwood Emissions Management

When business logic is owned by teams outside engineering, QA may be asked to verify behaviour without having full authority over what “correct” means.

Ian will cover the tooling QA teams can build to close this gap between the people who define the logic and the people responsible for testing it.

The session will explore two specific patterns:

• Control panels that allow domain experts to adjust inputs and run their own scenarios
• Test harnesses that capture an expert’s confirmation of the correct outcome as a reusable fixture with expected results

The aim is to create a workflow where the people who understand the logic can validate it directly, while QA turns that validation into something repeatable and testable.

How this meetup solves your problem :

Teams often need to test logic that depends on specialist knowledge held by risk, data science, research, compliance, or other domain teams.
Without a structured way to involve those experts, QA may be left interpreting requirements, recreating assumptions, or deciding whether an output looks correct without enough context.
This session will show how Ian’s teams use tooling to bring domain experts into the validation loop. Instead of relying on QA to infer expected behaviour, experts can run scenarios, confirm outcomes, and help create reusable test evidence.

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