Skip to main content

Stop Blaming QA: Real Reasons Behind Project Delays

In many tech companies, QA gets blamed when a release is delayed. But what if QA isn't the problem? Let's look at real-world examples that reveal the actual root causes behind delays — and why it's time to stop blaming QA.

Example 1: Incomplete Build Handed to QA

A SaaS company rushed a build to QA with broken login and missing APIs. QA found several critical issues immediately. Leadership still wanted a demo to the client.

Outcome: Release delayed 5 days. QA was blamed. Later, devs admitted the build was not ready.

Example 2: Late Requirements, Last-Minute Testing

A banking product team finalized requirements 10 days into a 14-day sprint. Devs worked overtime and gave QA 1 day for testing.

Outcome: 3 critical bugs caught, release delayed, QA blamed — but the issue was poor planning.

Example 3: Missing Unit Tests by Developers

A logistics startup skipped unit testing. QA spent days identifying a critical bug that devs could’ve caught early.

Outcome: Delay of 7 days. QA was called “too strict.” But QA prevented a customer-impacting bug.

Example 4: Skipping Regression Testing

An insurance platform skipped regression due to time pressure, despite QA’s warnings. The release broke existing features.

Outcome: Client disruption for 24 hours. QA blamed. The real issue? Leadership ignored QA's advice.

Example 5: Broken CI/CD Pipeline

QA flagged that automation and pipelines were flaky. Releases continued with failed tests, QA had to validate everything manually.

Outcome: 2-day delay. QA was blamed, but root cause was ignored test failures in CI/CD.

Final Thought

Across all examples, QA wasn't the cause — they were the safety net. Blaming QA for delays masks deeper issues in planning, communication, and engineering discipline.

  • Involve QA early
  • Respect their timelines
  • Fix process gaps — not just bugs

Quality is everyone's job. Empower QA — don’t scapegoat them.

Comments

Popular posts from this blog

AI Agents in DevOps: Automating CI/CD Pipelines for Smarter Software Delivery

AI Agents in DevOps: Automating CI/CD Pipelines for Smarter Software Delivery Bugged But Happy · September 8, 2025 · ~10 min read Not long ago, release weekends were a rite of passage: long nights, pizza, and the constant fear that something in production would break. Agile and DevOps changed that. We ship more often, but the pipeline still trips on familiar things — slow reviews, costly regression tests, noisy alerts. That’s why teams are trying something new: AI agents that don’t just run scripts, but reason about them. In this post I’ll walk through what AI agents mean for CI/CD, where they actually add value, the tools and vendors shipping these capabilities today, and the practical risks teams need to consider. No hype—just what I’ve seen work in the field and references you can check out. What ...

Autonomous Testing with AI Agents: Faster Releases & Self-Healing Tests (2025)

Autonomous Testing with AI Agents: How Testing Is Changing in 2025 From self-healing scripts to agents that create, run and log tests — a practical look at autonomous testing. I still remember those late release nights — QA running regression suites until the small hours, Jira tickets piling up, and deployment windows slipping. Testing used to be the slowest gear in the machine. In 2025, AI agents are taking on the repetitive parts: generating tests, running them, self-healing broken scripts, and surfacing real problems for humans to solve. Quick summary: Autonomous testing = AI agents that generate, run, analyze and maintain tests. Big wins: coverage and speed. Big caveats: governance and human oversight. What is Autonomous Testing? Traditional automation (Selenium, C...

What is Hyperautomation? Complete Guide with Examples, Benefits & Challenges (2025)

What is Hyperautomation?Why Everyone is Talking About It in 2025 Introduction When I first heard about hyperautomation , I honestly thought it was just RPA with a fancier name . Another buzzword to confuse IT managers and impress consultants. But after digging into Gartner, Deloitte, and case studies from banks and manufacturers, I realized this one has real weight. Gartner lists hyperautomation as a top 5 CIO priority in 2025 . Deloitte says 67% of organizations increased hyperautomation spending in 2024 . The global market is projected to grow from $12.5B in 2024 to $60B by 2034 . What is Hyperautomation? RPA = one robot doing repetitive copy-paste jobs. Hyperautomation = an entire digital workforce that uses RPA + AI + orchestration + analytics + process mining to automate end-to-end workflows . Formula: Hyperautomation = RPA + AI + ML + Or...