Surviving and Thriving in an “AI-first” Company
What we’ll cover in this session.
How much do you really know about your company’s AI adoption strategy, and what it will mean for you as a QA, QE, or tester in any role?
Mine declared itself “AI-first.” So, it seems, many companies are doing this, through a press release or via internal communication these days. Harvard Business School already offers leaders an $1800+ course and defines what “AI-first” means.
The phrase reached me like white light: uniform, dazzling, easy to mistake for a single thing. So I held up a mental prism. It refracted the white light into a spectrum: People, Products, Processes, Practices, Quality, Profitability, and Testing. Each colour was lit differently, and each demanded something different of us.
I followed the one that was mine: Testing. But not in isolation.
This is an experiential talk, not a forecast. Together we will model the communication between our human capabilities and the AI capabilities, and ask where our cognitive functions still matter most.
My argument is plain. We survive by lowering our ignorance. We thrive by seeing the change in perspective, empathizing, and renovating ourselves on purpose, engaging AI with our judgement in place, not surrendered.
Where agentic workflows actually earn their keep in a real QA pipeline — and the two places they quietly fail.
The four control surfaces to set up before an agent touches production: scope, evaluation, failure cataloguing, human-in-the-loop.
Patterns for flaky-test triage, regression pruning, and visual-diff arbitration with receipts from three production systems.
A reference architecture you can take back to Monday’s sprint planning, plus the metrics that prove it’s working.
Sandeep Garg
Principal QA Architect
Sandeep Garg serves as a Principal QA Architect at Bridgetree, where he leads hands-on testing of modern ETL pipelines, cross platforms data migration, and data-driven B2B and B2C applications.
Across 20+ years, mostly in BFSI at FIS, Fiserv, Clear2Pay, and CashEdge, he has applied risk-based, context-driven thinking to data, functional, performance, and security testing, with deep focus on legacy enterprise applications modernization, APIs, and cloud data flows.
He approaches testing as investigation, digging into context and risk before tooling, and use different AI assistants and LLMs to testing with a practitioner’s eye.
He has spoken at testing conferences including ATA-GTR, Ai Test Fest, and Testflix. Sandeep mentors testers at every level and is always happy to connect and co-learn.
Catch this session live.
One pass, every talk, no parallel tracks. Super Early Bird
ends when the next 200 seats are gone.