Grzegorz Holak & Filip Barszcz

Join our presentation on: AI Didn’t Replace QA — It Gave Us Time to Actually Do Quality

A real-world story of how AI adoption (not just AI tools) transformed our Tribe’s SDLC workflow, accelerated quality maturity, and gave teams back time for real testing.
(Based on real use cases from Santander Corporate and Investment Banking FX Chapter)
 
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Who is Grzegorz Holak?

Santander Corporate and Investment Banking Test Architect in FX Chapter

Since 2016, I have been building a career in software quality, with a primary focus on test automation and quality architecture since 2018. I have worked in banking and investment environments with high operational and regulatory demands.
My core objective is to build durable quality capabilities: from test strategy and frameworks to organization-wide standards and risk-based decision making.
As an AI Ambassador, I combine proven engineering discipline with practical AI adoption to help teams improve how they build and validate software.

Who is Filip Barszcz?

Santander Corporate and Investment Banking FX QA Chapter Lead

QA Chapter Leader with over 10 years of experience in the IT industry. Throughout his career, he has collaborated with renowned organizations such as SCIB (Santander Corporate & Investment Banking), T-Mobile, Capital.com, and IQVIA.
On a daily basis, he focuses on building and refining software quality processes, removing roadblocks for QA and development teams, and sharing his expertise. His approach combines technical proficiency with pragmatism — while privately, he is fueled by a passion for TTRPGs, LARPs, and science-fiction literature.

What will Grzegorz Holak & Filip Barszcz be discussing?

AI Didn’t Replace QA — It Gave Us Time to Actually Do Quality

A real-world story of how AI adoption (not just AI tools) transformed our Tribe’s SDLC workflow, accelerated quality maturity, and gave teams back time for real testing.
(Based on real use cases from Santander Corporate and Investment Banking FX Chapter)
 

Talk Summary

  • Building an SDLC workflow based on Quality Culture using AI tools is not only about productivity — it’s about enabling quality ownership across the Tribe.
  • We used AI daily in Jira/Xray (Rovo), in repositories (GitHub Copilot), in development support (Devin), and as a knowledge assistant (GPT), combined with automation.

Key Points

  • How Rovo (Jira + Xray) improved ticket understanding, test coverage and reduced requirement ambiguity.
  • How GitHub Copilot accelerated test automation, refactoring and code review.
  • How Devin worked as an “AI teammate” for repetitive engineering work.
  • How GPT became a daily support layer for quick answers, summaries and knowledge sharing.
  • How automation helped build continuous quality visibility (reports, summaries, risk signals).

Main Focus: Adoption

  • Why tools alone do not change quality.
  • Why AI adoption requires structure: AI Ambassadors and AI Champions.
  • How we introduced guardrails, playbooks and shared practices to ensure AI outputs are reliable.

Outcomes

  • Improved documentation quality (created effortlessly and summarized when needed).
  • Better repository and wiki visibility even for non-technical roles (BA can validate story understanding early).
  • Accelerated maturity growth from TMMi ~0 to ~2.5/3.
  • Time saved was reinvested into higher-value quality work: exploratory testing, creative test design, better automation, stronger code reviews.

Audience Takeaway

  • A repeatable approach to using AI as a multiplier of Quality Culture, not just a productivity hack.

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