Scaling Quality in a Decision Intelligence Platform: The Agentic QA Playbook
What does it take to build a quality-first culture inside a fast-moving AI company serving Fortune 500 enterprises — where the product itself is made of AI agents?
At Aily Labs, we build a Decision Intelligence platform that helps global enterprises across Pharma, CPG, and Retail make better decisions, faster. Our platform doesn't just surface data — it reasons, advises, and acts. And that changes everything about how you test it.
Traditional QA was built for deterministic systems: you define inputs, you assert outputs, you ship. But when your product is a network of AI agents that reason, collaborate, and adapt — the old playbook breaks. There are no fixed outputs to assert. There are no scripts that can anticipate emergent behavior. And when something goes wrong for a Fortune 500 client, "we didn't have a test for that" is not an answer.
So we rebuilt QA from the ground up — not as a safety net at the end of delivery, but as an intelligent, always-on system woven into every layer of how we build and operate. We gave quality a pulse. We taught agents to test agents. And we made AI the default way our QA team works.
This talk walks through that transformation — and the three things every QA engineer should take back to their team.
Key Takeaways:
Quality Needs a Pulse, Not Just a Report: How we built a real-time quality accountability system — tracking AI accuracy, defect leakage, and tenant health in one place — so quality degradation is visible to everyone, instantly, not discovered in a post-mortem.
Agents Orchestrating Agents — The New QA Architecture: How we built a network of collaborating AI agents (triage, root cause, data validation, exploratory) that hand off context, escalate findings, and coordinate autonomously — replacing manual test coordination with an always-on quality engine.
AI as the Workflow, Not the Shortcut: How AI is embedded into every layer of day-to-day QA work — from defect triage and ticket writing to on-demand exploratory runs triggered from chat — and what the shift from "engineer who uses AI" to "engineer whose entire workflow is AI-augmented" actually looks like in practice.
About the speaker
Hammad Ahmed:
Hammad Ahmed is Head of QA AI Innovation at Aily Labs, leading the development of AI-powered and autonomous QA systems for a Decision Intelligence platform serving Fortune 500 enterprises. With 16+ years in software engineering and quality, Hammad focuses on agentic testing, AI quality evaluation, autonomous test automation, and enterprise quality intelligence. His mission is to move QA from reactive testing to proactive, autonomous quality engineering — using AI to test AI.
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