Testing isn’t one-size-fits-all—it depends on your industry and tolerance for risk. Shipping updates every few seconds might work for Amazon, but is it right for your industry? On Test Case Scenario, we break down why testing strategies vary so much depending on context. For example: Banks prioritize careful testing to protect transactions and avoid costly errors. Companies like Amazon rely on razor’s-edge testing, monitoring traffic patterns to spot issues fast.

Still waiting for AI to integrate into workflows seamlessly? You’re not alone. AI still feels stuck in "fantasy land" for many teams, but progress is getting faster. 2025 could be the year we finally make AI’s potential a reality—but only if we take action now. Catch the conversation on the latest episode of Test Case Scenario to explore the real-world progress of AI and what it will take to move beyond the hype.

What’s next for software testing in 2025? In this episode of Test Case Scenario, Jason Baum, Evelyn Coleman, and Marcus Merrell discuss the trends shaping the future of testing. From AI advancements to accessibility regulations, they explore what’s on the horizon for testing tools and methodologies.

There’s a new way to approach quality. In game testing, "shift-left" is all about catching issues earlier in the development process rather than waiting until production. @Mac Clark from Sauce Labs explains how game engines like Unity and Unreal allow for a shift-left approach using AI agents to automate testing before a game reaches players. This proactive method can help identify potential crashes and errors at the engine level, ensuring a more stable product launch.

Is your error reporting solution ready to handle millions of players? Without the right tools, scaling for large games can lead to overwhelmed systems and missed insights. Here’s a strategy: Prioritize Scalability: Choose tools like Backtrace that can handle the sheer volume of errors in massive releases without compromising on performance. Enable Easy Triage: Look for solutions that streamline error sorting so teams can quickly pinpoint and resolve critical issues.

Don’t rely on players to find bugs in your video games. There’s a smarter way forward. And it involves using AI agents and shift-left testing. Here’s why AI bots are game-changers: Automated Playtesting: Advanced AI agents now handle repetitive playthroughs, catching issues early and reducing developer crunch in alpha and beta phases. Comprehensive Coverage: These bots don’t just mimic players; they explore every inch of the game, uncovering bugs that would take traditional QA departments hours.

Relying solely on shift-left testing to catch issues? Think again. Testing expert @Mac Clark reveals why the best teams integrate shift-right testing as an 'insurance policy' for quality software, catching what pre-release tests might miss. Here’s why it matters: Watch the latest episode of Test Case Scenario to see how industry leaders combine shift-left and shift-right approaches for unbeatable software quality.

Can your software handle the pressure when bugs slip through the cracks? In this episode of Test Case Scenario, Jason Baum and Evelyn Coleman chat with Mac Clark, Senior Solutions Engineer at Sauce Labs, about the dynamic world of shift-left and shift-right testing. Mac shares how gaming and software industries leverage AI-driven testing, real-time error monitoring, and feature flags to catch issues before they snowball into costly problems in production.

Reality check: no team can achieve total bug prevention. But that doesn’t mean failure—it means balancing effort with impact. Instead of aiming for perfection, focus on identifying the most critical errors and creating test cases that catch the ones that truly matter. This approach helps teams save time, resources, and frustration while still maintaining high-quality releases. Perfection in bug prevention isn’t realistic, but smart prioritization is.

How do you handle a critical bug in production without causing more issues? @Titus Fortner suggests using feature-based test tagging to prioritize what matters most. Instead of running every test in your suite, focus only on the areas impacted by the fix to prevent regressions and speed up the process. This method helps teams roll out fixes faster, reduce risk, and avoid unnecessary delays by targeting the most relevant tests for each change.