Bionic Testing
Software testers and testing companies are quickly becoming bionic. The best thing about AI is that it gives testers superhuman testing abilities not always associated with testing: speed, knowledge, efficiency, consistency, deep analysis, and scale. These new powers dramatically improve the real and perceived value of software testing. The best news is that with modern productized AI, testers don’t need to know how the engine in the car works or how Netflix streaming works — they can add these capabilities on the fly, and quickly without knowing AI.
Bionic: having normal biological capability or performance enhanced by or as if by electronic or electromechanical devices
Bionic Testers are the future of QA and testing. Bionic Testers deliver the value and performance of teams at just slightly more than the cost of a single tester. Most interestingly, they deliver this value faster.
Bionic Testers and testing companies are the early adopters — by definition. Not just because they will be the first to don these new AI tools, but because the slower adopters simply won’t survive due to market forces, leaving even more demand and work for the bionic ones.
Speed
Speed is king, and AI finally puts testers in the driver’s seat. Traditionally, testers are seen as ‘slowing’ down the team as everyone waits for QA processes to complete, and bugs are found long after they were introduced. Bionic Testers with access to autonomous testing agents find issues in almost real-time.
Autonomous testing agents can test every new build, even local developer builds, and dynamically and intelligently perform basic testing. If a new button is added — the Bionic Tester sees the test results from the AI before they even load the new web page. The Bionic Tester has a small team of AI Testing Agents working for them that deliver test coverage and issues for them to triage. The suggested issues can overwhelm the development team with issues that need to be fixed before they have tested the product themselves.
Testers are finally in the driver’s seat; the team is now waiting on fixes from the developers while the testers are following up on even more complex testing and quality issues.
Knowledge and Context
Bionic Testers are experts in virtually every area of testing. Testing is an amazingly broad field, and no normal tester can be an expert in all of it. Most testing teams and companies don’t even have enough context, let alone a single tester who masters it all. Traditionally, this breadth of testing has required creating a mix of internal testing experts and multiple external testing firms — but the Bionic Tester has most of this knowledge at their fingertips thanks to AI.
AI gives Bionic Testers access to the collective skills of all documented testing knowledge in the world. Consider the following partial list of testing skills needed to do a great job of testing — no single tester knows all of these areas. Few teams have this much expertise available: functionality, performance, mobile, usability, accessibility, security, privacy, visual design/UX, content, user feedback, exploratory testing, competitive analysis, automation, summarization and prioritization, and risk analysis.
Bionic Testers have far more context at their disposal to perform their testing work — and they share far more of their context with the machines. Bionic Testers have access to test results and findings not just from today’s build, but from previous builds and trends. Not just data for the app they are testing, but from other apps in the organization and even competitors’ apps.
Bionic Testers easily share more context with the machines, so they can do their job better too. Bionic Testers will gather not just specifications, Gherkin/Cucumber scenarios, and log files, but also design and business documents from across the organization. Normal testers can’t read all this context, let alone keep it in their mind when making every decision — but Bionic Testers can by sharing this context with the machines, which incorporate it into every test case and all of their analysis.
Efficiency
Just one Bionic Tester can do the work of even large team of traditional testers for a single app. Or instead, a Bionic Tester can deliver basic testing to 5 less critical apps. Testing isn’t usually known for its efficiency, but Bionic Testers might now be the smartest — and first — hire on a new software project.
The cost of AI is a rounding error compared to the cost of human labor. Yes, you still need human intelligence to manage and interpret the AI, but for basic testing tasks, Autonomous AI is easily 10X less expensive, 10X faster, and in many cases find 5–10X more issues than humans at the same tasks. The AI of today can find issues that most testers would have found, at a fraction of the cost, and are parallelizable. All this means the pairing of a human with the power of the latest AI Testing Agents can conservatively deliver efficiencies of 5X or greater. The limitation being that at some point, there are diminishing returns on testing.
Avant-garde testing services companies have already started to convert their test engineers into Bionic ones, delivering testing services that are not just mostly automated, but AI-Informed Services — faster, better, and cheaper by a wide margin versus traditional services companies.
Most larger testing services firms will fail to adapt quickly as they race to protect their margins and saturated lists of clientele. The small and medium-size vendors, with Bionic Testers, will rapidly grow their client lists and deliver far more value at a far better price. Efficiency is key to delivering value at scale in testing services, and even the notion of a 2X improvement will have a dramatic impact.
Deep Analysis and Reporting
Bionic Testers can finally recall and deliver analysis across large swaths of test results and bug reports — and even code.
Bionic Testers not only review the output of the AI — but the issues have additional analysis that not even the most technical testers, or reporting tools can deliver. The AI can understand the code behind the bug. AI Testing Agents report not just the problem, but also often deliver the ‘why this is a bug’ and even ‘how to fix it.’ The best Agents can even deliver pre-generated arguments as to why this issue should be fixed. Bionic Testers bring the what, where, how and why — not just bug reports.
When we think about test engineering, it is all about simple pass/fail and crashes, but much of the value of humanistic testing is the qualitative evaluation and intuition for an app’s quality. Does it look weird? Does it make sense? What is missing? Is it intuitive? How does it compare? These are questions once relegated to only the most experienced testers. Bionic Testers though, get the value of hundreds of feedbacks from simulated users. These users are created by the AI specifically for this app, for this page, for this feature. These users can have ‘fuzzy’ and qualitative, and different opinions on the quality of the product. The Bionic Tester simply reviews this feedback, digs a bit deeper, and suggests changes for the team.
Testers, and even test managers unburdened by daily tasks, can keep only so much in their head at once when delivering summaries of quality. The AI can look across all human and machine-generated quality data. The AI leverages broad understandings of quality in the industry. The AI can also leverage the context of the team. Modern AI can easily synthesize all this data and deliver far better, and more eloquent, summaries of application quality. The AI can also build far, far, far more useful and visually appealing dashboards versus traditional red/green spreadsheets or JIRA views, to report that quality analysis — making the team look smart and modern in the process.
Consistency
Bionic Testers are far more consistent in their testing and reporting. Testers reluctant to adopt AI conjure fears of AI not being predictable enough — the irony is that AI-Informed Bionic Testers are far more consistent and repeatable than their pure organic counterparts.
People vary widely in their judgment, speed, and skills. Unaided humans are inconsistent in their judgment day to day, hour to hour. Human judgment is even impacted by blood sugar levels. Most people only consider the consistency of their own analysis. As testers shift jobs or tasks between each other because of vacations, the testing varies. Even more so, when teams interview 5 different people for their test lead role — they will get 5 wildly different test plans and strategies. And, often those 5 are people that just happen to live nearby and have happened to opt-in to apply for that role. The variability in human-based testing is frankly extreme.
In contrast, the AI models are single files. Those weight files are consistent — forever. They don’t tire, you can clone them. For the most part, the same prompt really does generate much the same response — day after day, week after week. AI responses might vary slightly — but far, far less than humans.
The pure exactness, precision, and consistency of non-Bionic test automation is the source of most cost, pain, waste and frustration in the testing world. The fact that these procedurally coded, non-AI test automations cannot adapt to environmental or product variations makes them marginally useful in all but the most curated and predictable environments. Bionic Testers benefit from a consistent set of test cases and coverage — but in a form that is just flexible enough to adapt to changes and just dynamic enough to add coverage for new features without human intervention.
Bionic testing and automation benefits from the sweet spot of ‘mostly consistent’ test coverage and analysis. Bionic Testers both deliver thew sweet spot of consistent coverage with adaptability in practice.
Scale
Bionic Testers scale. Numbers of people, budget, and time are severe limiters on the scale of manual testing and even test automation projects. Bionic Testers are freed from most of these limitations, as the AI delivers basic test coverage and analysis — but at the scale and cost of machines. Available compute is near limitless, and the cost of the AI is an order of magnitude lower than the cost of even a single human. In the smallest of cases, not even a dedicated tester is required, as a developer or product manager becomes a part-time ‘Bionic Tester’, spending only a fraction of their time testing.
Bionic testing means most of the core testing work can scale far faster than the number of humans. This means that Bionic Testers can test not only their app, but other apps. Small groups of Bionic Testers can even test thousands of apps…
Becoming Bionic
Becoming a Bionic Tester or testing services company is now easy. A few years ago, testers were trying to learn ‘AI’, even last year testers were trying to fine-tune their own LLMs. Today, all this power of AI has been harnessed, and productized, and takes no training, code, or expertise to get started. Bionic AI for testers means the newest testers can outperform some of the most experienced testers, and experienced testers can now do the work of entire teams.
There are several ways that testers and organizations can begin their journey to become Bionic Testers:
- Many AI testing platforms now offer simple signup processes with affordable pricing that individual testers can expense
- Testing service providers are rapidly adopting and integrating AI capabilities into their offerings, transforming their teams into Bionic Testers at scale
- Organizations can partner with AI-enabled testing services to access Bionic Testing capabilities immediately
Summary
Testers can become “Bionic” today and deliver the value of 5 or more traditional testers. AI provides superhuman abilities in speed, knowledge, efficiency, consistency, deep analysis, and scale. It enables testers to find issues in real-time, access global testing expertise, handle vast amounts of data, and create comprehensive quality analysis with visualizations better than a grid of pass/fail data.
Bionic Testers gain these advantages:
- Finding defects before even loading a page, thanks to AI Testing Agents
- Accessing collective worldwide testing knowledge across all domains
- Processing huge amounts of contextual data from specs, logs, and business documents
- Delivering consistent, adaptable testing that scales effortlessly
- Creating sophisticated quality analysis and visually appealing dashboards
I’ve seen firsthand how adopting AI transforms teams into bionic powerhouses. Bionic Testers don’t just keep up; they lead, delivering faster, more consistent, and deeply insightful results.
— Stacy Kirk, CEO QualityWorks
The testing landscape is transforming rapidly, and early adopters will thrive. Those who become Bionic Testers proactively will have a significant advantage over peers who wait to become Bionic. The technology is accessible now, requiring minimal training and technical expertise to get started. In this AI-driven future, testers who embrace these capabilities will not only survive but lead the evolution of software quality.
Personal Note
I once dreamed of machines that could test autonomously. At my previous company, test.ai, we spent years conducting research on AI-based testing approaches, primarily funded by Google. We worked to determine what works, what delivers value, and how to implement it effectively. We began transforming our customers at Google, Microsoft, and Epic Games/Fortnite into Bionic Testers.
Today, my goal is to democratize these Bionic testing advantages to every software team on the planet, at scale. We genuinely need teams to sign up and provide feedback to help fund our R&D and accelerate the evolution of AI and software testing. Early adopters will be remembered and rewarded with preferential pricing and benefits — their input will help shape the future of testing.
Ad: Signup at https://checkie.ai
— Jason Arbon, founder Checkie.AI
Feel free to ping @ https://www.linkedin.com/in/jasonarbon/
or X: @jarbon
