Introduction and CleverDev Overview
Release Readiness and Engineering Intelligence
Welcome back to another SPK and Associates vlog. My name is Michael Roberts, Vice President of Sales and Marketing here at SPK and Associates.
Today, we’re talking about challenges that nearly every software engineering team faces. How do you actually know when software is ready for release?
For years, teams have relied on passing tests and green dashboards as signals of quality. But as systems grow in complexity and toolchains become more fragmented, those signals are becoming unreliable.
In this conversation, we’re going to explore the idea of engineering intelligence—moving beyond reactive quality checks to more proactive identification of risks before those things show up in production.
We’ll talk about why green dashboards alone can be very misleading, how AI-driven insights can surface hidden risks across engineering data, and why that matters even more now for regulated industries and embedded software environments.
So today, I’m joined by Vibhuti Bhushan from CleverDev. Feel free to introduce yourself.
CleverDev Mission and Purpose
Thank you so much, Michael. My name is Vibhuti, and I’m the co-founder of CleverDev.
What we are trying to do with CleverDev is arm engineering leaders with data from their SDLC toolchains and help them make planning and software release decisions.
Our goal is to ensure that engineering teams will never need to manually collect data from various tools and make release decisions based on seeing a bunch of green dashboards.
Michael’s Perspective on Manual Data Collection
As someone who has manually collected data for that purpose before, I appreciate this approach. I don’t want to have to do that manually because it takes forever, and of course, I always forget something.
Can you give us maybe a 30-second overview of what CleverDev is?
CleverDev Platform Overview
Yes, sure. CleverDev is a data platform.
We ingest data from your entire SDLC ecosystem and compute a predictive risk score. We create a link for each line of code to understand why it was written, how it was tested, and how defect-prone it has been in the past.
That allows our platform to flag hotspots.
So even if your code coverage is 70%, for example, we are able to advise leaders whether the riskier code is well tested, and they can make informed release decisions based on their risk appetite.
It helps leaders focus their resources on managing riskier areas of the code and release products with fewer defects.
This essentially leads to happy customers and, importantly, developers who don’t have to spend a significant portion of their time fixing production defects and releasing hotfixes.
Moving from Firefighting to Forecasting
So essentially, if I have to summarize all of this, we move teams from firefighting to forecasting.
Instead of reacting to customer-reported incidents, we help engineering leaders assess risks continuously and in real time.
I love that.
Why Green Dashboards and Traditional Metrics Are Misleading
The Limits of Passing Tests and Green Dashboards
In a blog post that you wrote, you talked a little bit about passing tests and green dashboards and how they are no longer sufficient indicators to trust for release readiness. Why do you say that?
Green dashboards don’t equal quality.
You can have 90% code coverage, and I’m highlighting code coverage because that’s one of the key metrics people look at. You can have 90% code coverage and still ship a release full of bugs coming from the 10% of code that is not tested.
If you look at engineering teams today, they leverage many tools to build software. You have planning tools, CI/CD tools, issue trackers, coding tools, and other systems.
They all produce isolated metrics, but none of them show correlated risk.
The Problem with Fragmented Toolchain Data
To give you an example, if one of your modules has high code churn, recent changes, and a history of production incidents, it’s essentially a ticking time bomb when it comes to future defects coming from that module.
But your traditional dashboards will completely miss that.
Even if the dashboard says everything is green, you still have that risky piece of code that you have not paid attention to.
Why CleverDev Goes Beyond Surface-Level Metrics
I think that’s why I like your product so much. I’ve gotten a sneak peek at the actual product, so I can say this confidently.
It goes well beyond a green dashboard and really gets into the details.
Code coverage is a good example of that. It’s often used as a proxy for quality, but it doesn’t actually tell you where your real risk exists.
Green dashboards can give teams a false sense of security.
Transitioning to Predictive Risk Awareness
Next question. How does CleverDev help engineering and product teams shift from being reactive—finding bugs and hopefully not in production, but sometimes in production—to a more proactive approach to quality?
How do you help teams identify predictive risks before they happen?
How CleverDev Enables Continuous Risk Assessment and Proactive Quality
Eliminating Manual Release Readiness Meetings
First and foremost, you don’t have to hold release meetings where you ask people to bring metrics and explain how things are going.
This platform is continuously getting data from all your tools and performing calculations in real time.
That’s the first major shift.
Instead of manually gathering information, leaders always have access to up-to-date insights.
Two Core Areas: Planning and Software Quality
There are two major pieces to the product: planning and software quality.
With software quality, as I mentioned earlier, we create a link for each line of code.
We answer questions like:
- Why was this line of code written?
- When was it written?
- How well tested is it?
- What has been the historical defect pattern associated with it?
We perform this assessment on a regular basis.
As soon as a new line of code is checked in, we evaluate it immediately.
We determine whether that new code increases risk or decreases risk.
Real-Time Risk Monitoring and Decision Support
This gives engineering leaders the opportunity to understand their current risk profile.
They can determine whether they are operating within acceptable risk levels or whether they need to take corrective action.
Specifically, the platform highlights areas of code that need more attention.
This allows leaders to focus their teams’ efforts where it matters most.
This approach goes beyond broad metrics like overall code coverage.
You could have 60% coverage focused on the right areas and release a better product than having 90% coverage overall while still experiencing production incidents.
Coverage alone does not guarantee safety.
Risk awareness does.
Continuous Visibility into Engineering Risk
We perform these risk assessments continuously and in real time.
Engineering leaders can log into the platform and immediately see what has happened in the last 24 hours or the last 48 hours.
They can understand how recent changes have impacted planning.
They can understand how those changes have affected release quality.
This allows teams to make informed decisions quickly and confidently.
Instead of reacting to problems after release, they can proactively manage risk before release.
Shifting from Reactive to Predictive Engineering
This fundamentally changes how engineering teams operate.
Instead of reacting to customer-reported defects, teams can anticipate and mitigate risks ahead of time.
It shifts the organization from reactive firefighting to proactive risk management.
Leaders gain confidence in their release readiness based on real risk assessment, not just surface-level indicators.
Why Engineering Intelligence Is Critical for Regulated Industries
The Unique Challenges of Regulated Environments
I love it.
A lot of SPK’s clients are in highly regulated industries. We’re talking about medical devices, automotive, and environments with embedded software.
What tangible value do you see in adopting an engineering intelligence platform approach that goes beyond just having a cleaner dashboard or a better dashboard than they had before?
That’s a great question.
When you talk about these industries, the cost of defects is obviously very high.
There have been studies examining the cost of production defects in the software industry, but specifically in the industries you’re referring to, the impact goes beyond simply releasing a patch.
The consequences can include compliance failures, safety risks, and regulatory violations.
Testing Optimization: Focusing Resources Where Risk Is Highest
Using something like CleverDev, you can identify three key areas where organizations benefit significantly.
The first is testing optimization.
Many of these industries have very long testing cycles.
With CleverDev, teams can focus their QA resources on the areas that truly require testing.
This reduces the overall time required for testing while simultaneously reducing risk.
Instead of testing everything equally, teams test intelligently.
They focus on the areas where defects are most likely to occur.
Defect Avoidance: Catching Regression Risk Before Release
The second area is defect avoidance.
One of the key capabilities of CleverDev is identifying regression risk.
This involves detecting risks associated with existing functionality that might be impacted by new code.
This is extremely important for clients in regulated industries.
Regressions can result in compliance failures.
They can create safety risks.
They can introduce defects in systems that must meet strict regulatory requirements.
By identifying regression risk early, organizations can prevent these issues before they reach production.
Audit Readiness: Complete Traceability Across the SDLC
The third area is audit readiness.
As we discussed earlier, the platform creates a link between all your SDLC tools.
It provides complete visibility into why a line of code was written, how it was tested, and how defect-prone it has been.
From an audit perspective, this is incredibly valuable.
Teams can quickly answer critical audit questions:
- Who made this change?
- Why was this change made?
- When was it made?
- How was it validated?
This information is available immediately.
Teams no longer need to manually gather information during audit preparation.
The data is always available in real time.
This significantly reduces audit preparation effort and improves compliance confidence.
Operational Efficiency and Immediate Access to Critical Data
I love that it’s available at your fingertips.
Some of our clients have experienced audits where teams have to run around collecting information from multiple systems.
Having that information readily available at all times is extremely important.
This approach provides enormous benefits to many of the clients SPK works with.
It improves operational efficiency.
It improves compliance readiness.
And it improves overall software quality.
Engineering Intelligence, Generative AI, and the Future of Software Quality
Redefining Software Quality Beyond Passing Tests
This has been a phenomenal discussion. I really appreciate your time.
What stands out to me is that software quality today isn’t just about whether it passed a test.
It’s about understanding where risk is hiding.
It’s about how confident you are in reducing that risk and understanding it before release.
It’s about having the right data points to make informed decisions.
I really appreciate the implementation you’ve created to help reduce risk and eliminate uncertainty around release readiness.
You’re helping teams move beyond simply looking at whether something passed or failed.
You’re helping them truly understand engineering risk.
The Growing Impact of Generative AI on Software Development
Michael, we didn’t even touch on generative AI writing a significant portion of code.
Exactly.
The amount of code being generated is going to increase dramatically.
This makes platforms like CleverDev even more important.
Organizations need systems that continuously evaluate risk automatically.
You don’t want to manually review every change.
You want a platform that continuously monitors risk as developers and AI systems generate software.
CleverDev enables this by continuously assessing risk as new code is introduced into the system.
This ensures teams maintain control over quality, even as development velocity increases.
The Rise of Engineering Intelligence Platforms
I think you’re going to hear more about engineering intelligence platforms going forward.
Platforms like CleverDev represent a shift in how engineering organizations approach quality.
Instead of relying on surface-level indicators like dashboards or code coverage, organizations are moving toward data-driven risk intelligence.
This approach provides deeper visibility.
It provides greater confidence.
And it enables smarter release decisions.
Thank you for sharing how CleverDev is approaching this problem.
I appreciate your time, and I appreciate the importance of this approach, especially for regulated industries and complex engineering environments.
Thanks, Michael. Thank you for having me.
Closing Remarks and Call to Action
Thank you to everyone who watched this discussion.
If you have questions about green dashboards and whether they truly indicate release readiness, it’s important to have a deeper conversation.
Reach out to our team through our social channels or through our website.
If you enjoyed this content, be sure to subscribe to the SPK and Associates YouTube channel for more videos like this.
We’ll see you again next time.
