In this episode of the Shaping Healthcare Podcast, Gaurav Shrimal, AVP – Quality &
Validation at CitiusTech, joins host Laurel to discuss how the Synthetic Quality Engineer
(SQE) is making Gen AI adoption in software testing more consistent and scalable.
Join them as they:

0:07
I am really excited to bring you this podcast on Synthetic quality Engineer the AI revolution in testing.
0:15
Today, we are joined by Gaurav Shrimal, Assistant Vice President, Quality and Validation at
CitiusTech, Gaurav brings over 2 decades of experience in IT, specializing in delivery management,
quality assurance, and consulting with healthcare and life sciences clients to help them transform their
QA and QE capabilities.
0:36
Gaurav, welcome to the podcast.
0:38
Thank you, Laurel.
0:39
Thanks for having me here today.
0:41
It's a pleasure having you.
0:43
I'm really looking forward to our conversation because everyone is talking about Gen
0:48
AI and its use in healthcare, but I want to start with those two decades of experience.
0:55
And we've really seen the evolution of technology and been a part of that over these these last
several years.
1:01
So what is the real opportunity when it comes to quality engineering and software testing?
1:10
Sure, Laurel.
1:11
So if you ask me, software testing typically accounts for 40% of the total cost of software
development.
1:18
Now it will encompass your functional testing, data verification, automation, and many more activities
that you do in software testing.
1:28
Gen AI can significantly enhance the QA process and it can help you reduce cost by effectively
managing resources, identifying patterns, detecting unusual activities, and predicting potential issues.
1:40
It can be utilized from early stages of test planning and design to the later stages of test execution
and report where it can actually help you analyze results, identify patterns, rectify test data and
environment and automation scripts also.
1:54
So if you ask me, ideally Gen AI will support quality engineers at every stage of the software testing
life cycle.
2:03
You mentioned 40% of the budget of software is in the testing portion of it.
2:09
Yes, I did Wow, that I mean, that's a that's quite a large piece of the of the pie there.
2:15
And so having more efficient and more streamlined processes, I would imagine, really helps keeps
keep costs in check and help keep everything running smoothly for for teams.
2:27
That's that gives a lot of promise, you know, for a Gen.
2:29
AI and and the quality engineering and testing.
2:32
When we're looking at the bigger picture of that, how do you see the the challenge of making its use
consistent, scalable across the whole testing life cycle?
2:43
And, and I guess ultimately is that what led to the idea of the synthetic quality engineer in that role?
2:51
Oh yeah, absolutely.
2:52
In fact, consistency and scalability were the two most important things when we conceived the idea of
SQE.
2:59
So if you look at quality engineers, everyone is is unique as an individual.
3:04
Same feature can be interpreted differently by each individual.
3:09
Some accelerate identifying positive scenarios, some at edge cases, others might identify good
negative scenarios or non functional aspects.
3:19
Now also quality engineers, everyone has a different approach to writing test scenarios, test cases,
automation scripts, in spite of they having a standard or a guideline that they might be falling.
3:31
So these are the challenges that we definitely wanted to overcome and hence the idea led to us to
create SQE for quality engineers.
3:40
Well, I suppose we should dig a little bit more into what a quality synthetic quality engineer is.
3:46
And what does that, what does that mean when it comes to this, this role in the software testing?
3:53
So SQE basically serves as a digital twin for quality engineers.
3:57
So it's helping them eliminate and automate many repetitive tasks throughout the software testing life
cycle.
4:03
So if you've seen code assist tools, they generate codes in real time.
4:07
Now test design SQE will help you generate user stories, test scenarios, test cases, and automation
scripts and all of that in the context of the application that you want to test.
4:19
So this significantly reduces the effort during the test design phase of the STLC.
4:24
So it's a major phase in the whole life cycle.
4:29
What's important to note is SQE differs from your regular automation tools in that you still need to
need an automation tool to execute the scripts generated by SQE.
4:39
Essentially SQE automates the manual effort previously spent by quality engineers during the test
design phase.
4:48
You mentioned 40% of of this budget, you know, going towards the the testing and also how those
processes help streamline and help create, I guess make everybody's role a little little easier and
make sure that there's a better product on the other side.
5:07
So a lot of value, a lot of value, a lot of impact there.
5:11
What kind of benefits can an organization expect from something like that?
5:17
For organizations, it's a transformative advantage if you ask me, especially for organizations who are
ready to embrace AI driven quality engineering.
5:25
So it helps in fostering innovation throughout the QA community and optimizing every stage of the
software testing life cycle.
5:32
It can actually help deliver measurable results.
5:35
So if you look at it, it can double the speed to production.
5:38
It can help you achieve effort savings of 40 to 50% and substantially elevate product quality.
5:45
So if you're asking me 40% of software development cost going into testing itself, just imagine 40 to
50% of that effort being saved.
5:55
How much cost savings it can bring all together, certainly a lot of value for an organization.
6:03
And those are great numbers to hear, of course.
6:05
And then we scale it down a little bit more and look at the teams themselves.
6:09
How does this help the teams or for the teams, it's a boon if you ask me.
6:16
So teams can be empowered to automate majority of the test design tasks starting from and and OK,
so it can be a boon for the teams completely right.
6:30
It can help automate majority of the test design tasks route right from the outset, driving innovation
through AI LED.
6:39
OK, yeah.
6:43
So SQE empowers the teams to automate the majority of test design tasks right from the beginning,
driving innovation through AI at every turn.
6:52
It will enhance test coverage by uncovering scenarios and test cases that traditional approaches
might actually miss as development cycles accelerate.
7:01
SQE ensures testing teams can keep pace with without compromising on quality, maintaining 100%
standardization because the outputs that are being generated are adhering to industry best practices.
7:15
It all sounds great.
7:17
I'm sure teams are, you know, executives would be on board with that.
7:20
And they're like, wonderful, now how do we adopt and implement this into our, our own companies?
7:27
You tell us a little bit more about that.
7:29
Sure.
7:30
So first and foremost, it's really important to identify what are the right use cases and what is the
technology stack that we want to use for the test design.
7:39
SQE.
7:40
Now every organization have used their own technology stack.
7:44
They have their own LLMS that they want to use their own, their own agent orchestrators that they
might want to adopt.
7:53
So once we do a POC and we assess the benefits that SQE can deliver for their organization, we can
implement it at a large scale.
8:01
Adoption based on specific project demands once we have implemented the adoption is actually very
straightforward.
8:09
Unlike chat based solutions where users have to prompt the Genii solution, we don't have to prompt
SQE.
8:16
Users just need to upload the files.
8:18
They can select what kind of output they really want to generate and everything from prompt creation,
output creation, evaluation of the output actually happens at the back end.
8:28
So all quality engineers need to do is they need to learn what kind of data to provide and how to use
the tool to an interactive UI.
8:38
Gaurav, as we wrap up our conversation together, I always like to look ahead at the future.
8:44
Technology is rapidly evolving, things are always changing.
8:48
It's an exciting time to look forward to.
8:50
And as we, we look ahead, so for you, what excites you the most about the evolution of quality
engineering and these solutions like the SSQE?
9:03
Oh, it's absolutely very exciting for me.
9:05
And why I say is being in this field for such a long time, a lot of effort goes into some of these really
mundane tasks of identifying test scenarios, test cases, right?
9:16
What SQE can do is it can enable the quality engineers to focus more on value added tasks by
adopting AI first mindset.
9:24
Acting as a digital twin, SQE supports flexible deployment, localized adoption and enable shift left
quality at a scale.
9:32
It will actually empower quality engineers to shaping healthcare possibilities by allowing them to test
healthcare applications quickly and at scale.
9:42
All wonderful and exciting things.
9:44
There's some really great points to bring up and, and like you said, allowing the engineers and the
developers to, to create and, and do what they they love to do.
9:53
And so once again, you're looking, looking forward and looking ahead to the future.
9:59
And especially for any leaders who are looking to prepare their teams for the shift, what sort of advice
do you have for them?
10:09
First and foremost, general solutions are going to become the norm and we need to embrace them
wholeheartedly.
10:15
So teams must learn how to use these solutions efficiently and effectively so that they can ensure that
they're not using it blindly without identifying the right ROI.
Secondly, solutions like SQE should be treated as an aid to engineers rather than as a
replacement for them.
10:46
Human intelligence is still crucial for delivering domain specific outcomes and teams should focus
their time and effort on this aspect.
10:56
Finally, while some team members will use these solutions, others will have to build, enhance and
maintain these Gen.
11:02
AI based solutions.
11:04
So what teams need to do is they need to establish centers of excellence for development quality
engineering to ensure continuous enablement is happening for the teams on ground.
11:15
Excellent, Gaurav.
11:16
Thank you so much for your time today and and bringing your expertise and your passion to our
conversation today.
11:23
Thank you so much.
11:24
Thank you, Laurel.
11:25
It was nice talking to you.

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