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The 70% Problem

Bonus Session

70% of testing capacity goes to clerical work. Agentic QE gives every tester access to expert-level thinking from day one — not by replacing testers, but by amplifying what they can do.

Timetable

8:30 a.m. – 4:30 p.m. Monday 16th

Room

F-,E- & D-Rooms

Artificial Intelligence (AI) Quality Coaching Test Automation

Audience

Testers, QA Engineers, Test Leads, Quality Coaches, SDETs

Required

Laptop with internet access

Key-Learnings

  • Leverage 47 years of encoded expertise in context-driven testing, risk-based thinking, and deep exploration — no years of skill development needed.
  • Configure and run multi-agent pipelines live, working across 13 domain-bounded contexts coordinated by a Queen agent for hierarchical orchestration.
  • Evaluate any agentic quality system using the PACT framework (Proactive, Autonomous, Collaborative, Targeted) as a vendor-neutral standard.

Reclaiming Testing's Intellectual Core with Agentic Quality Engineering

The software testing profession has been around for approximately 70 years, yet nothing has fundamentally transformed it to deliver on what it was always capable of. Industry data shows that almost 70% of testing capacity is spent on testing-related activities — documentation, reporting, maintenance, coordination — while only 30% goes toward actual testing that creates real value: asking the right questions, evaluating risk, exploring the unknown, and informing decisions.

Organizations have been trying to automate away all things testing for decades. It never worked because the real value of testing comes from its intellectual core — critical evaluation, risk analysis, deep exploration, and informed decision-making. But mastering this craft requires years of investment that organizations see as overhead.

This hands-on workshop introduces Agentic Quality Engineering — a fundamentally different approach that gives every tester access to expert-level thinking without years of investment. Built on 47 years of combined practitioner experience and the award-winning QCSD framework, attendees will work with AI agents encoding context-driven approaches, risk-based thinking, and deep exploration techniques into 70+ specialised skills and 60+ purpose-built agents.

Attendees will configure and run multi-agent pipelines spanning the full SDLC, evaluate agentic systems using the PACT framework, and leave with a fully configured open-source environment under MIT licence — nothing held back.

Related Sessions

There are currently no related sessions listed. Please check back once the program is officially released.