Insights
Customer advocacy in an AI-saturated quality space
Are conversations the key to QA-developer relationships?
How are teams like yours balancing speed, quality, security, and AI in 2026? Download your copy and get real insights.
Good practice is also about learning what to avoid
How can we manage the complexity of AI testing tools?
Learn how to debug hidden email integration failures across multiple backend layers (from SMTP authentication to application logs) instead of falsely trusting successful frontend UI messages.
The five risk categories to navigate before, during, and after an AI migration.
Sometimes the most effective guardrail isn't the most sophisticated one
AI needs guardrails to play by the rules and work better
How are teams like yours balancing speed, quality, security, and AI in 2026? Download your copy and get real insights.
Manage your entire QA lifecycle in one place. Sync Jira, automate scripts, and use AI to accelerate your testing.
With servers in >250 cities around the world, check your site for localization problems, broken GDPR banners, etc.
Bring intelligent testing to every pull requests with autonomous static analysis and unit testing.
Call for Insights
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Customer advocacy in an AI-saturated quality space
Are conversations the key to QA-developer relationships?
Sometimes the most effective guardrail isn't the most sophisticated one
AI needs guardrails to play by the rules and work better
Quality Engineering
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A great conversation on friction, influence and showing up authentically
Integrate monitoring, observability, and alerting into the core quality engineering process to ensure systems are as diagnosable as they are functional
Implement the Playwright Page Object Model (POM) to build maintainable, resilient test suites by centralizing page interactions and separating them from test logic.
How does a team’s stage of development influence the style of quality engineering it needs to thrive?
AI
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Customer advocacy in an AI-saturated quality space
How can we manage the complexity of AI testing tools?
Good practice is also about learning what to avoid
The five risk categories to navigate before, during, and after an AI migration.
Tooling
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The shift from scripting steps to designing prompts and AI guardrails has begun
Experiment with AI development tools to understand their impact on delivery speed and the quality challenges they create for engineering teams
Discover how the recruitment landscape has changed over the past 10 years, for both testers and hiring managers
Discovering a new tool is one thing, but now we have to learn how to use them.
Automation
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How can we manage the complexity of AI testing tools?
If you didn't write it, do you own it? The role of AI Guardrails in code quality.
Automation activities, like all software development work, only matter if they contribute to real business outcomes.
Are we ready? How quality coaches and engineers can use patience to support their teams.
Quality Attributes
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Integrate monitoring, observability, and alerting into the core quality engineering process to ensure systems are as diagnosable as they are functional
How do AI guardrails deal with millions of possibilities?
Modernise your design strategy with mobile-first and keyboard-centric approaches that create more resilient, accessible, and user-friendly software.
Apply a four-dimension framework to assess whether synthetic data can be trusted for performance testing.
Tech Careers
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How do you move on from a failed product launch?
What we should have been hiring for all along
Why showing up helps quality professionals acknowledge their continuous learning journey
AI's impact on quality generalists vs quality specialists
Leadership
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Do Engineering Managers hold all the power?
The sense of loss will be outweighed with the joy of influence
How is friction helping and not helping software engineering and testing teams?
How do we convince product and project people about the importance of testing?
