The hottest Quality Assurance Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Introduction of Formal QA to Nuclear Power

Gordian Knot News • 102 implied HN points • 15 Mar 26
🕹 Technology Quality Assurance
  1. The AEC turned vague goals (Criterion 1) into mandatory but open‑ended QA rules (Appendix B), leaving huge discretion to regulators and enabling continual escalation of requirements.
  2. Formal QA became self‑reinforcing: more inspections and reported nonconformances generated more demands for tests and paperwork, driving up costs and sometimes crowding out real quality enforcement.
  3. A pragmatic, layered inspection model — yard QC, independent classification inspectors, and owner inspectors — can enforce quality effectively without drowning projects in paperwork, unlike the paperwork‑focused regulatory approach that wasn’t even applied internally.

Are AI Coding Assistants Really Saving Developers Time? Study Suggests These Tools Don’t Increase Coding Speed.

Shenisha’s Substack • 19 implied HN points • 04 Oct 24
🕹 Technology Quality Assurance
  1. AI coding tools, like GitHub Copilot, may actually slow down developers by increasing the number of bugs in their code. This raises questions about whether these tools truly help improve code quality.
  2. While some surveys show that many developers use AI tools and feel productive, a study found that these tools didn't significantly improve coding speed or help reduce burnout among developers.
  3. The rise of AI tools may require developers to spend more time reviewing the code these tools produce, which can cancel out any time they might save overall.

ESP32 Rainbow QA - A tale of three boards

atomic14 • 173 implied HN points • 02 Jan 26
🕹 Technology Quality Assurance
  1. Minor assembly or soldering faults—like lifted pads, poorly seated ICs, or cold joints—can cause big failures such as no sound, no USB, or nonworking keys.
  2. Simple bench debugging (microscope inspection, continuity checks) plus basic rework (reflowing solder, nudging parts, retouching pins) can fix many issues, though some damaged boards are only fit for spare parts.
  3. Outsourcing PCB fabrication and partial assembly is fine, but final in‑house assembly and thorough QA are essential to catch subtle manufacturing problems before shipping.

Jim Hopf on Dry Cask Cost and Quality

Gordian Knot News • 212 implied HN points • 03 Dec 25
🕹 Technology Quality Assurance
  1. Nuclear quality is defined by the N-stamp, which only shows that a vendor has followed the proper paperwork, not the actual quality of the product. This can lead to issues if the focus is more on paperwork than on the quality itself.
  2. Costs of dry cask storage have dramatically increased over the years due to strict regulations, even though the original systems worked just fine. These regulations can create barriers to innovation and make safe options much more expensive.
  3. Using non-standard materials can pose challenges in the nuclear industry, as regulations often require products to meet unnecessary criteria that don't necessarily improve safety, leading to higher costs and potential quality issues.

Testing Too Late: A Case Study

QUALITY BOSS • 139 implied HN points • 09 Jul 24
🕹 Technology Quality Assurance
  1. Testing too late can cause big delays in getting software to users. If QA is behind, it creates confusion and slows down the whole process.
  2. Good communication between development and QA teams is really important. Working in separate sprints can lead to misunderstandings and more difficult bug fixes.
  3. It's essential to define when a task is 'done' to include testing. If something isn't tested, it shouldn't be considered complete, ensuring that quality stays high.
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Bugs Optional?

Software Design: Tidy First? • 1723 implied HN points • 03 Jan 25
🕹 Technology Quality Assurance
  1. Bugs don't have to be a normal part of software development. Some teams manage to almost eliminate bugs by approaching their work differently.
  2. Instead of seeing bugs as inevitable, teams can work to understand and prevent them right from the start. This includes practices like continuous integration and team collaboration.
  3. Changing how we think about bugs from a normal part of life to something rare can help create a better work environment and improve software quality.

Finding Data Bugs in dbt Pull Requests

clkao@substack • 39 implied HN points • 17 Aug 24
🕹 Technology Quality Assurance
  1. Data bugs can be costly for companies, with bad data potentially costing up to 25% of their revenue. These issues often arise from problems in data-centric systems like dbt.
  2. Using dbt allows data engineers to implement software practices like version control and testing, helping to ensure the correctness of their data transformations. However, relying solely on post-processing tests has its limits.
  3. Manual spot checks are still crucial in ensuring data accuracy during code reviews. Tools like Recce aim to streamline this process, making it easier for developers to validate and document their changes.

Last Call for Quality

QUALITY BOSS • 39 implied HN points • 03 Jul 24
🕹 Technology Quality Assurance
  1. Testing software too late can lead to more expensive and difficult fixes. It's better to catch bugs earlier in the development process.
  2. Many teams rely too much on manual testing, which can slow things down. A mix of automated and manual testing can improve quality and efficiency.
  3. Ignoring non-functional requirements like security and performance can make software unsatisfactory, even if it meets basic needs. It's important to include these factors in testing plans.

Scrum’s Definition of Done Is Polishing Plates in a Burning Kitchen

Rethinking Software • 499 implied HN points • 20 Nov 24
🕹 Technology Quality Assurance
  1. Scrum's Definition of Done creates extra pressure on developers to deliver perfect work, even when the process is chaotic. It doesn't fix the problems; it just shifts the blame onto the team.
  2. Instead of focusing on quality, Scrum encourages speed and follows strict checklists. This leads to developers cutting corners just to meet unrealistic deadlines.
  3. Real improvements would come from changing the whole process, like allowing more time for reflection, empowering developers, and reducing unnecessary meetings, which would promote better quality work.

Everything New Has Bugs

Fish Food for Thought • 23 implied HN points • 03 Dec 25
🕹 Technology Quality Assurance
  1. When you speed up releases or adopt new systems, bugs and incidents will usually rise at first — it’s a natural tradeoff between velocity and stability.
  2. Give teams slack and real ownership so they can fix problems, learn, and improve quality instead of just reacting to fires.
  3. Invest in supporting systems and feedback loops like CI/CD, observability, error budgets, and postmortems so you can absorb turbulence and restore quality faster.

Definition of Dumb

Rethinking Software • 249 implied HN points • 30 Nov 24
🕹 Technology Quality Assurance
  1. The Definition of Done in Scrum can often mask real problems instead of solving them. It makes it seem like poor quality doesn't exist by placing all responsibility on the developers.
  2. Many companies stick to strict processes without recognizing their flaws. This leads to frustration among developers who are pushed to meet unrealistic expectations.
  3. Empowering developers to create their own processes might lead to better results. By trusting the team, companies can produce high-quality work without getting bogged down by rigid frameworks.

🐿️ Your Software Is Wrong - The Insanely Profitable Tech Newsletter

Squirrel Squadron Substack • 3 implied HN points • 06 Feb 26
🕹 Technology Quality Assurance
  1. Even careful, human-made reference works often contain hidden errors that get copied forward. Cross-checking helps but won't catch everything.
  2. Modern computing faces the same problem at much larger scale: chips and software can produce subtle wrong answers, and huge datasets often make full verification impossible.
  3. The right response is to design for detection and tolerance by using redundancy, consistency tests, and processes that reduce mistakes. Practices like pair programming and business-facing code review help you "trust but verify" and make systems more resilient.

Productivity in Software Engineering: Beyond lines of code, the importance of experience in the development cycle

VTEX’s Tech Blog • 1 HN point • 18 Sep 24
🕹 Technology Quality Assurance
  1. Productivity in software engineering is not just about how much code you write. It's more important to focus on code quality and how well the software works.
  2. At VTEX, they listen to developers to improve their work experience. This helps boost productivity by addressing the challenges developers face.
  3. Combining feedback from developers with quantitative data can help understand the impact of changes in tools and processes on productivity.

The unhindered growth of bad mobile app product management

system bashing • 137 implied HN points • 05 Jun 23
🕹 Technology Quality Assurance
  1. There is a rise in poorly made mobile apps due to the growth of bad mobile app product management.
  2. Many mobile apps have similar features and design flaws, showcasing repetitive mistakes by product managers.
  3. Consistency in user experience, from technical aspects like rotation to design elements like button styles, is lacking in many apps, pointing to a need for improvement.

Tech Debt vs Quality

Fish Food for Thought • 14 implied HN points • 10 Dec 25
🕹 Technology Quality Assurance
  1. Tech debt and bugs are different: bugs are immediate errors to fix, while tech debt is the future cost of taking shortcuts and can be intentional or accidental, so decide and plan when to incur it.
  2. Make debt visible and economic: track where it slows work, measure the "interest" it charges in developer time or incidents, and prioritize paying down high-interest items rather than treating all debt equally.
  3. Leadership and culture matter: embed maintenance into planning, keep slack for cleanup, use retrospectives and metrics to shorten recovery time, and design continuous improvement cycles so velocity and quality compound over time.

So it goes...

The Weasel Speaks • 117 implied HN points • 01 Jul 23
🕹 Technology Quality Assurance
  1. Change can be slow in software teams when it comes to the need for dedicated testers.
  2. Different organizations have varying approaches to testing, from having no dedicated testers to having very few or many testers.
  3. Consider the context when evaluating statements that you disagree with, as what may not work in one context could work in another.

Die Mokassins eines anderen

Squirrel Squadron Substack • 3 implied HN points • 26 Jan 26
🕹 Technology Quality Assurance
  1. The repair notification said the device was restored but also warned the keyboard and trackpad might not work and the display could turn off, which is contradictory.
  2. The technician explained those odd comments were automatically generated and admitted they don't use the system, so they never noticed the misleading wording.
  3. When technicians don't validate automated messages, customers get confused and the business risks lost trust and revenue.

The N-stamp

Gordian Knot News • 109 implied HN points • 24 Jan 25
💼 Business Quality Assurance
  1. The N-stamp certifies a vendor's quality assurance process but doesn't guarantee the actual quality of their products. It's more about paperwork than real product inspection.
  2. In shipbuilding, multiple independent inspection teams check quality because they want to avoid costly mistakes. This extra layer helps ensure that ships meet the specifications and are delivered on time.
  3. The nuclear industry's reliance on the N-stamp allows vendors to skip necessary inspections, leading to poor quality products. This system could result in very high costs due to failures in quality control.

The biggest time sink for engineering teams: testing

Dev Interrupted • 37 implied HN points • 05 Jun 25
🕹 Technology Quality Assurance
  1. Testing is often the biggest delay for engineering teams, slowing down new feature releases.
  2. AI-powered testing tools can automate repetitive tasks, allowing QA teams to work more efficiently and focus on strategy.
  3. The role of QA professionals is shifting towards design and analysis, rather than just executing tests, as automation takes over routine tasks.

Hidden Tasks of Product Management

Sarah's Newsletter • 159 implied HN points • 28 Jun 22
💼 Business Quality Assurance
  1. Product managers should oversee their company’s offering like any manager oversees people.
  2. Being data-driven is crucial for product managers. They need to question data, consider various types of data, and course correct based on data-driven decisions.
  3. Product managers play a critical role in owning quality assurance and getting stakeholder buy-in for successful product launches.

What Makes a Great Quality Engineer?

QUALITY BOSS • 39 implied HN points • 30 Oct 23
🕹 Technology Quality Assurance
  1. Great quality engineers need a quality mindset. This means they care about making sure the product is useful and works well for customers, not just ticking off boxes.
  2. Some key traits of top QEs are curiosity, adaptability, and persistence. These qualities help them understand the product better and keep pushing until they get to the bottom of any issues.
  3. Effective communication and problem-solving skills are also important. This ensures they can share findings clearly and work well with other teams to improve the product.

Quality Engineering Basics: Debugging

QUALITY BOSS • 19 implied HN points • 12 Feb 24
🕹 Technology Quality Assurance
  1. Debugging is like being a detective; you need to find clues to solve the problem in the software. Understanding how or when a bug happens can help get it fixed faster.
  2. A good bug report includes details like when the bug occurs and what steps to reproduce it. The more information you provide, the easier it is for developers to understand and fix the issue.
  3. Trying different methods and tools can help uncover more about the bug. For example, using different browsers or versions of software can help pinpoint what's causing the problem.

Software Quality

Engineering Enablement • 21 implied HN points • 12 Feb 25
🕹 Technology Quality Assurance
  1. Software quality has four main types: process quality, code quality, system quality, and product quality. Each type affects the others, so improving one can help improve the rest.
  2. Process quality is crucial because a good development process leads to better code quality. This means having proper testing and code reviews can help avoid defects later on.
  3. Product quality is what customers experience and it includes a product's usability and reliability. Engineers need to team up with product managers to ensure that products meet customer needs.

GroupBy #1

VuTrinh. • 19 implied HN points • 08 Sep 23
🕹 Technology Quality Assurance
  1. Kappa architecture simplifies data processing by combining batch and stream processing. This makes handling data more efficient compared to the traditional Lambda architecture.
  2. Presto is a powerful tool for querying large datasets, and Meta has valuable insights on using it effectively. Learning from their experience can help other teams improve their data operations.
  3. Data quality is crucial in analytics, and there are specific metrics to help measure it. Keeping track of these can prevent problems that arise from poor data.

Manager or short order cook?

Sunday Letters • 59 implied HN points • 28 Aug 22
💼 Business Quality Assurance
  1. Organizations often say they value things like quality, but they might not really mean it. It's important to see if they make real choices based on those values.
  2. If engineers are just completing tasks without context, it can hurt quality and user experience. This 'short order cook' approach can lead to many problems.
  3. When interviewing or leading, ask if engineers can delay releases for quality issues. It’s a good way to understand how much the organization cares about quality.

164 | Food Fraud Special |

The Rotten Apple • 21 implied HN points • 11 Nov 24
🍲 Food & Drink Quality Assurance
  1. Food fraud prevention needs dedicated teams. These teams should include members from various departments to effectively address fraud risks.
  2. Underweight ingredients can be a form of food fraud if there's intent to deceive. If companies consistently deliver less than what was ordered, it could be seen as cheating customers.
  3. Staying informed about food safety and fraud trends is crucial. Changes in supply chains and economic conditions can create new opportunities for fraud.

Inconsistency as a service

Gradient Ascendant • 13 implied HN points • 10 Dec 24
🕹 Technology Quality Assurance
  1. Testing is really important for both hardware and software, especially when things can fail sometimes. In making chips, a lot of resources go into making sure they work properly.
  2. With AI like LLMs, you have to keep checking their outputs because they can be unpredictable. It's smart to set up a test system to know if what you're getting makes sense.
  3. We're still figuring out the best ways to test AI technology. Just like with traditional software, it will take time to develop good practices for making sure LLMs work well and reliably.

Episode 36: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 15 Feb 23
🕹 Technology Quality Assurance
  1. A Continuous Delivery pipeline helps keep software always ready for release by quickly identifying problems at various stages.
  2. The workflow consists of three main stages: Commit Stage, Acceptance Stage, and System Stage, with each stage increasing confidence in the software's reliability.
  3. It's best to start building your CD pipeline now, even if it's simple, and improve it step by step as you learn.

Improving data quality in online studies

UX Psychology • 19 implied HN points • 23 Nov 21
🔬 Science Quality Assurance
  1. In online studies, factors like distractions, poor equipment, and cheating can impact data quality.
  2. Engagement levels, accuracy, outliers, and speed of responses are key indicators to assess data quality in online studies.
  3. Strategies like consistency measures, attention checks, bot detection, and serious response checks can help improve data quality in online studies.

Quality Engineering Basics: Exploratory Testing

QUALITY BOSS • 0 implied HN points • 26 Feb 24
🕹 Technology Quality Assurance
  1. Exploratory testing is a flexible approach that doesn't need detailed preparation. It lets testers use their skills and creativity to find bugs efficiently.
  2. Using test charters can help focus exploratory testing. You can define what to explore, how to explore it, and what you want to learn.
  3. To improve your testing, think about worst-case scenarios for your product. Coming up with nightmare headlines can help guide your exploratory testing efforts.

Quality Engineering Basics: Automated vs. Manual

QUALITY BOSS • 0 implied HN points • 11 Mar 24
🕹 Technology Quality Assurance
  1. Deciding which tests to automate or run manually is important. You should look at the risk level and necessary effort for each test.
  2. Using a scoring system can help prioritize tests. This involves scoring impact, likelihood, frequency, and the effort required for manual or automated testing.
  3. Starting small with your scoring approach is a good idea. You can adjust the numbers until you find what works best for your testing needs.

Quality Engineering Basics: Prioritizing Bugs

QUALITY BOSS • 0 implied HN points • 18 Mar 24
🕹 Technology Quality Assurance
  1. Understanding how to prioritize bugs is key for efficient quality engineering. It's important to have a common agreement on what each priority level means.
  2. Using a matrix to categorize bugs by their scope and impact can help in deciding their priority. This method allows teams to see which bugs are more urgent and need immediate attention.
  3. Automation tools, like GitHub actions, can streamline the bug prioritization process. They can help automatically assign priority based on set parameters, saving time and reducing errors.

Quality Engineering Basics: Bug Reporting

QUALITY BOSS • 0 implied HN points • 19 Dec 23
🕹 Technology Quality Assurance
  1. A good bug report should have a clear title that describes the issue. This helps others understand the problem quickly without needing to read everything.
  2. Including steps to reproduce the bug is essential. This allows developers to see the issue themselves and figure out how to fix it.
  3. Adding relevant details like environment information, expected vs. actual results, and visual aids like screenshots makes the report more useful and helps prioritize the fix.

Getting Started as a Quality Engineer

QUALITY BOSS • 0 implied HN points • 08 Dec 23
🕹 Technology Quality Assurance
  1. Start with exploratory testing to learn the basics of software quality. You can practice this by using any application you regularly use.
  2. Once you find bugs, learn how to document and report them properly. This practice is key to getting recognized in the quality engineering field.
  3. Familiarize yourself with essential tools like APIs and Chrome DevTools, especially if you want to move into automation. Free online courses can help you build your skills.