When we say “QE,” most people think of “Quality Engineering” – a team, a role, a function. But at Relyance AI, it means more. QE is a mindset rooted in critical thinking – Question Everything – and it’s one we all share.  

From engineers and product managers to customer success and leadership, we’re committed to Questioning Everything, not to undermine, but to understand. Our critical eye examines assumptions. Our analytical mind challenges the status quo. We seek deeper insights by looking beyond surface-level explanations.

We question every aspect and not just internally, or for technical perfection but for you, the customer.

We ask hard questions not to slow things down, but to build trust into everything we ship. Every feature, every fix, every release you see has likely been shaped by questions you never knew we asked but that we asked for you.

Questioning Everything – is how we make smarter decisions, faster systems, and better experiences. It’s how we prevent problems before they happen. And most importantly, it’s how we deliver real value to you, not just working software.

Quality scales when everyone exercises this mindset, not just at the end of a project, but at every level of the system. Rest assured, next time we’re in a meeting discussing new features, running a retro, or reviewing code – we’ll ask ourselves: What have we not questioned yet?

Question Experience

Software can work perfectly and still feel broken.

We focus on what the customer actually experiences, not just what the code technically does. We challenge assumptions about how things should work because how it feels is just as important as how it functions.

• Does this feel fast, intuitive, and reliable for the customer?
  
• Are we overcomplicating something the user just wants to be simple?
• How does this change affect their day-to-day workflow?
  

Question Expectations

Every stakeholder has a different idea of what "done" means.

We care about outcomes, not just outputs. We don’t assume a feature is “obvious” or “done” without a deep understanding. We challenge assumptions about what “done” means – for you, the customer, not just the team. Getting quality right starts with defining the right target.

• What problem are we really solving here?
  
• What does success look like for the customer?
  
• Are we building the right thing — or just the requested thing?
  

Question Exceptions

Most real bugs live in the “what ifs”. 

We explore the edge cases, weird inputs, flaky networks, expired sessions, and all the invisible corners – because that’s where user frustration hides. We ask what happens when things go wrong – not just when they go right.

• What’s the worst that can happen here, and how will we handle it?
  
• Are we accounting for different roles, data states, and user behaviors?
  
• How does the system recover when dependencies fail?
  
  

Question End-to-End

You don’t interact with one screen or API – you use the whole system.

We build and test journeys, not just features. We check integrations, handoffs, and what happens when real-world use follows expectations or goes off script.

• How will we know this is working in the real world?
  
• What metrics or signals tell us customers are actually getting value?
  
• Are we monitoring the right things post-release?
  

Question Estimates

Timelines drive decisions, but they often hide risk. Time pressure should never be an excuse to sacrifice quality. 

We see estimates as starting points for discussion, not promises. We push back when going faster puts quality at risk. We make space for testing, review, and polish – because cut corners cut into customer confidence.

• What are the unknowns that could affect this timeline?
  
• Are we giving ourselves enough time to test thoroughly?
  
• Have we considered hidden work like tech debt or test coverage?
  
  

Question Engineering

Every line of code is a decision – and decisions compound.

We challenge technical decisions with the customer in mind – ensuring every solution is purposeful, practical, and built to last.

• Why was this approach chosen over simpler or more proven alternatives?
  
• Will this scale and remain maintainable and observable as we grow?
  
• Are we solving a real problem, or over-engineering a hypothetical one?

Question Environments

Real users don’t live in ideal conditions and neither should our tests. 

We validate assumptions about where and how things run. We don’t just test locally and hope. We advocate for stable, realistic test environments so what passes in staging works just as well when it reaches your hands. 

• Are we testing in environments that truly match production?
  
• Do our tests cover infrastructure, configuration, and integration points?
  
• Are dev and staging environments trustworthy?
  

Question Evidence

Confidence without proof is just hope.

We don’t settle for “it works on my machine” or “it seems fine”. We look for reproducible facts, test results, logs, usage data, and edge cases to back our confidence with proof because gut feeling (though important!) doesn’t scale to thousands of users.

• Can we reproduce this bug reliably?
  
• Is our testing evidence clear, complete, and credible?
  
• Are we over-relying on assumptions or anecdotal results?
  

Question Escapes

No system is perfect – but every bug is a chance to improve.

When bugs reach production, we dig deep – not just to fix, but to learn. We study every issue that reaches customers to make it the last of its kind.

• How did this escape past us?
  
• Was it detectable with better tests or alerts?
  
• What did we learn, and how are we preventing it next time?
  

Question Entropy

Quality doesn’t fall apart all at once. It drifts.

We monitor for that slow decay, flaky tests, skipped checks, outdated docs so customers don’t wake up to surprises.

• Is our automation suite growing smarter or just longer?
  
• Are we regularly pruning flaky or obsolete tests?
  
• Is the codebase becoming harder or easier to change safely?
  

Question Evolution

Features get added. Systems grow. Complexity creeps in.

We make sure our quality practices evolve with our product. We constantly ask whether change is improving the product or eroding it because quality is a moving target.

• Are we still testing the things that matter most today?
  
• Have new risks emerged with this architecture or feature set?
  
• Do we need to update our Definition of Done?
  

Question Empathy

Software is used by real people, in real-world situations, under real pressure.

We step into the shoes of customers, support teams, and each other. We test like you might use it: in a rush, on a bad connection, after a long day.

• How would I feel using this feature if I were a first-time user?
  
• What pain points have CSM or Support reported recently?
  
• Are we considering the impact across all roles and use cases?
  

Question Efficiency

Test coverage is not the same as test value. Redundant tests, brittle checks, and false confidence waste time and obscure real risks.

We seek smart investments, not just full coverage. We ask questions to focus on what matters.

• Are we testing at the right level – unit, integration, end-to-end?
  
• Is this test giving us signal, or just noise?
  
• Are we skipping over something fragile just because it “worked last time”?
  

Question Ecosystem

Quality isn’t just about code – it’s about the full system of people, tools, and feedback loops that shape the customer experience.

We extend this mindset beyond QE, across the product and engineering org, turning real-world insights into better decisions and fewer surprises.

• Are PMs, designers, and engineers asking critical questions early?
  
• Do CSMs and Support feel empowered to raise issues that matter?
  
• Is our system of quality collaborative, not siloed?

Final Thought

This mindset of questioning with care, intention, and empathy is something we see echoed across Relyance AI. 

Teams are constantly asking questions on your behalf:
Product asks what’s truly valuable to you.
Customer Success shares what’s working and what isn’t in your world.
Engineers explore ways to design systems to handle your scale, address your needs, and meet your expectations.

You may never see the questions we ask, the checklists we walk through, or the errors we simulate. But when you appreciate the value of Relyance, when your experience feels smooth, stable, and trustworthy – that’s the result.

By asking the right questions, we make better decisions, prevent downstream pain, and ship products that earn trust. Every question we ask makes someone’s experience better whether they’re a customer, a teammate, or our future selves.

So let’s keep Questioning Everything. Not to block. Not to slow down. But to understand, and to build better, together.

Even if you never see the questions we ask, know this: we asked them for you.