The Good Tech Companies - From 120 Hours to 2: The Hybrid Validation Shift Behind Faster, Safer Releases

Episode Date: February 6, 2026

This story was originally published on HackerNoon at: https://hackernoon.com/from-120-hours-to-2-the-hybrid-validation-shift-behind-faster-safer-releases. A biographical look at how Kostiantyn Shkliar's career moved from setting up automation processes to building validation systems that stay stable as orgs scale Check more stories related to futurism at: https://hackernoon.com/c/futurism. You can also check exclusive content about #automation, #validation, #financial-services, #kostiantyn-shkliar, #validation-systems, #ai, #qa-automation, #good-company, and more. This story was written by: @nicafurs. Learn more about this writer by checking @nicafurs's about page, and for more stories, please visit hackernoon.com. A biographical look at how Kostiantyn Shkliar's career moved from setting up automation processes in large organizations to building validation systems that stay stable as Salesforce environments scale.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. From 120 hours to 2, the hybrid validation shift behind faster, safer releases, by Nika Furs. Kostjantan SHK Lyre builds test automation for systems where getting it wrong has real consequences. He has spent over 10 years in automation architecture and software quality engineering, SDIT, focusing on fintech and large enterprise CRM systems. In recent years, he has worked in the U.S. Financial Services Market as a senior Salesforce QA automation engineer, supporting platforms tied to $130 billion plus in the sets under management. A key result from his work is a measurable change in how teams validate releases.

Using a hybrid validation model, he helped reduce regression execution time from about 120 hours to about two hours. That shift mattered because it reduced release friction while keeping confidence in the system's most important requirements, security behavior and data integrity. This is a biographical look at how his career moved from setting up automation processes in large organizations to building validation systems that stay stably as Salesforce environment scale. Costington Schlier's background in high-stakes QA automation. Costington started at EPM systems, where he helped set up QA and automation processes for global banks and large retail chains. Early work in large environments shaped his habits,

focus on repeatability, clear validation signals, and automation that can be maintained over time. As his career progressed, he stayed close to systems where quality connects directly to trust and risk. That led him deeper into financial services and into Salesforce-based Enterprise CRM, where configuration changes can affect access boundaries and data correctness across many users. Why regression testing turns into a release bottleneck. In mature enterprise systems, complexity tends to build gradually. Rules grow. Integrations expand. User roles multiply. The test suite grows too, often by adding coverage whenever something breaks. Over time, regression testing becomes the slowest step in releasing. That brings predictable issues. Feedback arrives late. Issues are discovered after more work has already been built on top. Teams feel pressure to reduce validation to keep delivery moving. Costiton's work has focused on shortening regression cycles without weakening confidence in results. the 120-hour regression cycle and the two-hour outcome.

At a large U.S. financial company, Kostchinton designed and implemented a hybrid validation model that changed how regression testing ran. Regression execution dropped from 120 hours to two hours. That shift supported a move toward daily releases while maintaining confidence in data integrity. In practical terms, it meant engineers could get answers the same day a change was made, and the business could plan releases around evidence rather than longweights. Hybrid validation, explained without jargon. Hybrid validation combines different types of checks based on what needs to be proven. The goal is simple. Use the most reliable signal for each kind of risk.

1. Targeted UIA U-U-T-O-M-A-T-I-N-UI tests cover a small set of critical end-to-end flows. They confirm key user journeys without carrying the full burden of regression validation. 2. API level and metadata-driven validation. Much of the validation runs through APIs and metadata to verify business rules and configuration outcomes in a stable way. In Salesforce environments, this supports validation of security configuration behavior, including permission sets. 3. Data integrity checks with controlled test DATA validation includes confirming that data remains consistent through updates and complex operations. Caution's design's scalable test data generation systems, data factories, using JSON schemas so data sets can be created predictably

andrewsed. Together, these layers reduce noise and keep the suite fast and dependable. Why UI-only automation breaks down in large Salesforce orgs. UI automation is easy to start with, but at scale it becomes sensitive to timing and interface changes. Tests fail for reasons that don't reflect real risk, which increases false positives and time spent investigating noise. When teams spend too much time chasing noise, trust in the suite drops. Kostchinton keeps Ui automation focused and uses it as one layer, not the foundation.

This is also where the hybrid model helps. Even when the U.I changes, core validation can still run against stable interfaces. Architectural driven validation. Focus on permissions, logic, and data. Kostitin describes his approach as architectural driven validation. Verify the parts of the system that define correctness. not only what appears on the surface. That means validating, security models and access boundaries, including permission sets, business logic, system behavior through APIs and metadata,

data integrity during updates and complex operations. This approach matters most in environments where configuration changes are a frequent. Small permission adjustments, rule updates, or new automation can create unexpected side effects, so validation has to stay close to how the platform actually enforces rules and access. Core skills, Salesforce security, APIs, net and test data systems. Caution's core skills include Net 8,0 and C-sharp, with deep API level interactions. Salesforce architecture expertise, including the security model, permission sets, and LWC components. Scalable data factories using JSON schemas, SDLC optimization to reduce technical debt, education, IT foundations and business perspective.

Kostchinton holds a master's degree in information technology from Kiv Polytechnic Institute, KPI. He also holds a second degree in marketing, which supports a business-focused view of engineering decisions. That mix helps him connect validation work to outcomes leaders care about, like release reliability, rework, and long-term maintenance cost. Current role. Keeping a financial services CRM stable through change. Currently, Kostchinton works as a a senior Salesforce QA automation engineer. His responsibilities include automation architecture, security configuration validation, and automation around complex financial operations, with the goal of minimizing release risk for a mission-critical CRM platform. He maintains strict

NDA compliance and does not disclose internal program names, specific business process details, or internal policies. He presents himself Asan Independent Expert Engineer and uses only publicly safe context, such as a UM scale. How he thinks about quality, trust, evidence, and simplicity. Costington treats automation as repeatable proof that a system stayed correct through change. His principle is, quality is not something you add at the end. It's what you build the system on from day one. He is inspired by Robert C. Martin's clean architecture and the belief that complexity increases reliability risk. He aims to keep validation systems understandable and maintainable so teams can rely on them over time, even as the platform grows. What he's working toward,

hybrid validation research and AI for security weakness detection. Cautionton plans to continue research and hybrid validation approaches and introduce AI-driven elements that can identify weaknesses in Salesforce security configurations. Long-term, he aims to work as a consultant focused on architectural reliability for fintech systems, helping teams keep release speed-aligned with strong validation. This article is published under Hacker Noon's business blogging program. Thank you for listening to this Hackernoon story, read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.