Wolf tracts

Golden Datasets fall short in real-world AI projects. Discover how random sampling boosts model adaptability, cuts costs, and ensures reliable, up-to-date performance.

QA Wolf provides a managed solution for custom, fast-changing software with per-test pricing, while Mabl offers a self-service tool for simpler apps with usage-based pricing. Explore their differences to find the best fit for your QA needs.

Explore smarter ways to measure AI session performance with LLMs. We focus on key tasks using weighted scenarios and dynamic metrics, ensuring real-world accuracy and helping you improve performance.

Explore 13 notorious software failures, from the Knight Capital failure to the Toyota acceleration problem. Learn how robust end-to-end testing could have prevented these high-impact errors and what we can learn from them.

Learn the core principles of software testing, explore best practices for quality assurance, and understand how to apply effective testing strategies for optimal results.

Learn why QA Wolf built a custom LLM Orchestration Framework over LangChain or LangGraph, focusing on flexibility, customization, and robust type safety.

Integrate DevOps with automated testing to speed up software delivery and improve quality. Learn the best tools and practices today.

Discover the importance of negative testing in software development

We redefine automated test maintenance by using specialized bots for accuracy and efficiency. Here’s how our agents apply that to deliver reliable QA testing.

Announcing our $36 million Series B and the launch of mobile app testing, which is open for waitlist. The investment is led by Scale Venture Partners with participation from Threshold Ventures and Ventureforgood, and existing investors Inspired Capital and Notation Capital.

When you run E2E tests on PRs before merging, you exacerbate your maintenance burden. Unprepared teams fall into traps on this journey. Find out what they are and how to avoid them.

 You’re not imagining things. Everything that makes E2E regression testing difficult is infinitely more challenging when you’ve integrated with or built on top of Salesforce. 

The job of testing in the world of generative AI involves familiarizing yourself with new territory and revisiting some slightly familiar terrain. But the creative essence of testing remains consistent.

Look before you leap - here's what you should watch out for when considering an AI-powered testing tool.

Learn how to test generative AI applications from the best. Use this curated list to find the information you need.

Modern tools and frameworks make regular web page performance testing easier for teams. We'll provide the code samples to get your team up and running with the performance metrics you need to create a great customer experience.

Your organization will benefit from accessibility testing in more ways than you are probably aware of. We will tell you how you can build a strategy to reap those benefits.

See what we've been up to and what we're planning in Q1 2024!

End-to-end regression testing for generative AI applications is mostly undiscovered territory. We’re blazing the trail, and here are some things we’ve mapped so far.

Learn how to plan your automated test coverage in a way that sets your team up for long-term success. Take it from the pros.

The way you construct parallel tests has changed in the last five years. If you’re going to be successful, you need to change how you think about it.

Outsourcing the creation of your automated end-to-end tests and then handing them to your in-house team might seem like a good idea. Here's why your expectations likely don't match reality.

Don't stop at detecting bugs. Get to the root of your quality problem and prevent bugs from showing up in the first place.

Is the doom loop of tech debt causing escapes that take time away from refactoring?

What goes into a QA Wolf bug report, and how testers can improve their communication with developers to speed up fixes and releases.

Attention, gear heads: Learn the details of our Kubernetes implementation that enables us to execute fully parallelized test runs, whether there are 200 tests in the run or 20,000.

Full parallel testing is hard. But in the long run, other approaches to test execution cost more in productivity and dollars. Learn how you can help your team deliver a quality product faster and save money.

You learn a lot about the reality of E2E testing when you manage tens of thousands of them each week.

QA Wolf gives you 80% test coverage in just 4 months. That’s not just marketing hype. Here’s what we mean by test coverage. Spoiler: it’s not code coverage.

We've come a long way since the Browser Wars and automated cross-browser testing is probably not worth the expense, except in a handful of cases.

If you're focused on vanity metrics, you're going to miss what's really important: Shipping faster, doing less rework, and increasing profitability. And yes, automated testing has a role in all of those.

A QA engineering team that's bogged down by E2E test maintenance has so much more to offer developers and the business — here's how to unlock their full potential.

Every environment is different — that’s the point — so your end-to-end tests have to be different too.

The Playwright vs Cypress debate is sure to go on, but when it comes to testing complex workflows, Playwright is better than Cypress for QA Wolf and our customers.

If you’re building your test suite in-house, take a tip from the QA Wolves: Cover the critical workflows across your whole product first and work down to the edge cases — don’t go feature by feature.

We didn't think charging for test runs or hours worked aligned the price of automated E2E testing to the value you actually receive. Read why we charge by test under management instead and how it creates a fairer, more predictable pricing structure for everyone.

After thousands and thousands of end-to-end tests, we've picked up a few tricks to build fast, stable, and accurate ones. So come along and we'll teach you how to build automated tests the QA Wolf way.

Here's how the Triple-A framework (Arrange–Act–Assert) improves on Given–When–Then, makes tests more resilient to code change, and enables fully parallel runs.

Learn why human capacity, test complexity, and testing infrastructure limit a team's ability to reach 80% test coverage.

Learn how the Triple-A framework helps you define your test coverage needs and what you need to validate to feel confident in every build you release.

Exactly how long can a test suite survive on its own while developers continue to ship new code? Read on to find out.

As startup operators, we’ve learned that there is often a "story behind the story" that goes untold. In this post, we'll go back in time and cover the winding path that led to our first $1.1 million in funding from Sahil Lavingia, Naval Ravikant, and pre-seed lead Notation Capital.

Five cost-effective changes you can make to increase and sustain the velocity of your engineering teams that don't include hiring additional resources. Here's how to do more with less.

When automated tests are in working order they provide engineers with rapid feedback on features that are still in development. When they're flaky — when they repeatedly fail without finding a bug — they lose any value to developers, and they're a liability to the team.

When developers own black-box testing, productivity drops and coverage levels suffer. In this post we talk about how white-box testing improves code quality, and why effective teams offload black box end-to-end tests to dedicated experts.

Our evolution from an open source command line interface to a full-service QA solution actually happened very naturally as we looked deeper and deeper into the problem at the heart of test automation.

The value of E2E test coverage isn’t just in spotting regressions—it’s in the safety, security, and confidence to make the big moves that drive successful companies forward.

Get a crash course in automated end-to-end testing from the experts at QA Wolf. In this post we cover the who, what, why, when, and how — and where things tend to go sideways.

The Test Pyramid gives engineering teams an excuse to under-invest in end-to-end test coverage. In this post we debunk three common myths about automated testing: It’s too expensive, it’s too slow, and you can move fast without breaking things.

Many companies take "shifting left" to mean developers should write E2E tests—but we can tell you that shifting QA onto your developers costs you more in the end.

If you don't have automated tests yet, getting started can feel daunting. In this guide we explore three common pitfalls companies face, and provide solutions for how to avoid them.