035 • 26 August 2025

Contents of this Newsletter

📱

Patterns VS Prompts

⏰ : 5 min

📓

Blog Picks

⏰ : 10 min

🤝🏼

Bangalore QAs Meet!

⏰ : 4 min

🗞️

Weekly AI News

⏰ : 9 min

MAIN STORY

Patterns – The Foundation of Traditional QA (and Their Limits)

If you’ve worked in QA automation, you’ve lived by patterns.Patterns like the page object model, arrange-act-assert, test pyramid and more. These weren’t buzzwords, they were the building blocks that made automation scalable and maintainable.

Patterns gave teams a shared language. They kept test code clean, reusable, and predictable. For a long time, this was the best way to manage complexity in automation.

But patterns have limits. They are rigid because applications often change faster than these frameworks can adapt. They are also expensive to maintain, as introducing a new user flow usually requires modifying or rewriting significant parts of the existing framework. Finally, they remain exclusive to teams with strong coding expertise, which makes them less accessible to organizations that lack specialized automation talent.

For years, that was the reality: patterns defined the structure, and everything else bent around them. But that structure is about to change.

Why Prompts Will Replace Patterns

AI is fundamentally changing the way automation works across industries. Instead of building complex frameworks around rigid patterns, we now have the ability to guide automation through prompts that clearly communicate what needs to be done. They’re high level instructions that express intent clearly, allowing the AI to interpret and execute tasks intelligently without the need for brittle scripts or predefined rules.

This is not how most QA tools operate today. Almost every major tool still relies on the traditional foundation of frameworks, scripts, and static rules. That is precisely why this moment matters: we are at the beginning of a significant shift in how testing will be approached.

Prompts are not just random commands typed on the fly. They can be structured, reusable, and standardized. In many ways, they represent everything patterns were meant to be, but without the limitations. They are dynamic, adaptive, and capable of leveraging intelligence to improve continuously.

Prompts bring flexibility because there is no need for a hardcoded structure; you simply describe the intent, and the AI executes the steps. They offer adaptability because when the application changes, the AI can adjust on its own without brittle selectors or the need for rewrites. They enable speed because teams do not need weeks of framework setup before they can begin testing; they can start immediately. Most importantly, they bring learning into the process because every execution makes the AI smarter, something static frameworks will never achieve.

In the future, teams will not be sharing design patterns for automation frameworks. Instead, they will be sharing prompt libraries—ready-to-use templates that define best practices for guiding AI-driven testing. Writing prompts will become the new equivalent of designing frameworks.

What This Means for Testers (and Why We’re Building for It)

For testers, this shift changes the way automation work is done. Instead of spending hours or days maintaining brittle frameworks, testers will focus on strategy and quality. Their work will center around writing clear, well-defined prompts that describe the right test coverage, outline critical user flows, and account for edge cases. The value of a tester will no longer come from repetitive boilerplate coding; it will come from shaping the behavior of intelligent systems to achieve better outcomes.

This is the future we see for QA, and it is the reason we built our execution engine around this philosophy. A single well-crafted prompt in Quash can achieve what once required entire frameworks and weeks of effort. Patterns defined the last decade of automation and prompts will define the next.

Check out our Recent Blogs

TEAM

Bangalore QAs Connect!

Bangalore doesn’t see many QA-focused gatherings, and that’s what sparked the idea behind The QA Connect. When Ayushi, our product intern, realized how hard it was to find a space for testers to connect and share experiences, she decided to create one.

The first meetup, co-hosted by Nidhi, brought together QAs, SDETs, and enthusiasts for an afternoon of conversations, debates, and networking. From sharing real-world challenges to discussing how testing is evolving in 2025, the room was full of energy and ideas.

What stood out was the shared vision: building a stronger, more connected QA community. With activities, discussions, and plenty of coffee, the event set the tone for what could become a regular initiative for QAs in Bangalore.

PS: If you’re a QA in Bangalore (or nearby) and want to be part of the next meetup, do reach out to Ayushi (ayushi@quashbugs.com)

News

This Week in AI

Meta Freezes AI Hiring After Talent War
Meta has paused hiring in its AI division following an aggressive spree that saw over 50 researchers recruited with high-profile offers. The move coincides with a major reorganization—splitting the Superintelligence Lab into four units (superintelligence, products, infrastructure, long-term research). Meta frames the pause as routine planning, though investors are cautious after its multi-billion-dollar AI push.

xAI Open-Sources Grok 2.5 Model
Elon Musk announced via X that xAI has open-sourced the Grok 2.5 model weights (available on Hugging Face), making last year’s top-performing model publicly accessible. He also confirmed that Grok 3 will be released as open source in approximately six months. The move reflects a growing trend toward transparency in AI, though the Grok license has been described as custom with anti-competitive terms by AI engineer Tim Kellogg.

OpenAI Launches India-First "Learning Accelerator"
OpenAI has unveiled an India-first Learning Accelerator, featuring a ₹4.5 crore ($500,000) research grant to IIT-Madras and distribution of 500,000 free ChatGPT licenses to students and teachers in government and AICTE-run institutions. The program also rolls out ChatGPT’s Study Mode, a personalized tutor-style feature, and appoints Raghav Gupta (ex-Coursera APAC) as Head of Education for India & Asia Pacific.

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How Patterns will Replace Prompts: The Next Testing Breakthrough 🤯