In this current climate, it’s even more important to ensure that team members are as optimized as possible in order to pivot to best support and deliver in the most efficient and nimble way possible. Although sometimes overlooked, playbooks have been a successful option to continue to foster collaboration and as we all know, the right people “in the room” are highly influential in the overall quality of the SDLC.

Introduction: Defining what it means to operationalize AI—not just building models, but integrating them successfully into business operations.

Roadmapping for AI: Strategies for aligning pilots, capacity, and team structure to business goals.

“Lab vs. Crowd” Methods: Balancing deep experimentation with broader organizational buy-in.

Building Support Systems: How to grow AI skills and capabilities company-wide, starting from a lean or solo team.

Deep Dives:

Successes and challenges from scaling AI at CampMinder.

Techniques for centralizing AI processes and moving from pilots to full operations.

Capacity building, resource allocation, and nurturing a culture of innovation.

Real-World Examples: Melissa’s lessons learned through hands-on operationalization with cross-functional teams.

• Operationalizing AI requires more than technical aptitude; it’s about centralizing, scaling, and integrating AI across the whole organization, starting with good roadmapping and support systems.
• The most successful teams blend focused R&D (“lab”) with broad enablement and engagement (“crowd”)—you need buy-in and participation beyond isolated pilots.
• Real momentum comes from intentionally building capacity, nurturing innovation, and sharing responsibility so that AI becomes part of everyday work, not just a side project—especially when starting with a small or single-person team.
• These practical insights equip leaders, engineers, and testers to systematically build and scale AI capabilities, avoiding common pitfalls and ensuring lasting organizational impact.

Modern software teams are under pressure to deliver secure, reliable features at unprecedented speed. Traditional testing approaches that happen late in the pipeline can no longer keep up. This session explores how shifting testing earlier powered by automation and AI-driven tooling can accelerate delivery, reduce defects, and improve developer experience. We’ll break down practical strategies for embedding testing into design, development, and CI/CD workflows, and highlight how intelligent test generation, predictive defect analysis, and self-healing tests are transforming DevOps. Attendees will learn frameworks, cultural changes, and team practices required to adopt shift-left testing across cloud-native, containerized, and distributed systems.

• Quality must start early not at the end
• Testing becomes a shared responsibility
• Automation is the foundation
• AI supercharges test effectiveness
• Shift-left is a journey, not a one-time adoption

Topic Details Coming Soon

As AI becomes embedded in test automation tools, many teams struggle to balance speed with trust, maintainability, and human accountability. This session focuses on how QA and engineering teams can apply AI in test automation without over-automating decisions or creating brittle, opaque test systems.

Based on real-world experience, the talk walks through practical, human-in-the-loop workflows for AI-assisted test design, API automation, failure triage, and test maintenance within modern CI/CD pipelines. Rather than promoting fully autonomous or self-healing testing, the session emphasizes clear guardrails, review points, and decision boundaries that keep humans responsible for quality outcomes.

Attendees will leave with concrete implementation patterns, checklists, and adoption strategies they can apply immediately to build sustainable, trustworthy, and AI-assisted test automation in real delivery environments.

How to apply AI in test automation while keeping human judgment and accountability

• Practical human-in-the-loop workflows for AI-assisted test design and maintenance
• Guardrails that prevent brittle, untrusted, or noisy AI-generated tests
• Techniques to reduce flaky automation and speed up failure triage using AI insights
• A responsible adoption model teams can implement without disrupting existing pipelines

As AI agents and LLMs make code generation widely accessible, the SDET role is shifting from how much we automate to how much we can trust AI output. Because AI optimizes for plausibility—not certainty—it introduces new quality risks.
In this hands-on workshop, test automation is reframed as Strategic Reliability Auditing. Participants will build a Guardian Layer that validates, constrains, and stabilizes AI output before it reaches production.

What You Will Learn

• Auditor Pattern – Detect hallucinations by reconciling AI output with authoritative engineering truth.
• Consistency Stress Testing – Use metamorphic testing to expose fragile reasoning under small input changes.
• Deterministic Guardrails – Implement Python-based logic to intercept and correct AI failures in real time.
• Strategic Risk Mapping – Translate audit signals into a Quality Risk Heatmap for AI adoption.

• From Scripting to Auditing – Why modern QA focuses on measuring and managing model stability.
• Defensive-by-Design AI – Patterns for resilient, self-healing AI output pipelines.
• Quantified Trust – Replace opinion with measurable trust scores and stability metrics.

Ravi Amarala is a seasoned Software Quality Assurance and Test Automation leader with over 16+ years of experience driving quality excellence across complex enterprise environments.

He brings a strong combination of technical depth, strategic thinking, and people leadership—consistently delivering high-impact quality engineering outcomes aligned with business objectives. Ravi has demonstrated exceptional leadership capabilities, driving transformation initiatives, fostering accountability, and enabling organizations to elevate their quality maturity.

A proven senior leader, Ravi has successfully built and scaled high-performing, multi-cultural teams across global geographies. He is known for cultivating collaborative environments that promote ownership, innovation, and measurable delivery excellence.

Adaptable and forward-looking, Ravi thrives in dynamic business and technology landscapes. His ability to embrace emerging technologies and operate effectively in challenging environments has helped organizations navigate change while maintaining a sharp focus on quality, speed, and efficiency.

With a career that started in software quality assurance, I’ve spent years leading global teams, refining QA strategies, and ensuring the delivery of high-performing digital experiences across complex products. My background spans hands-on testing, QA leadership, and client-facing delivery, giving me a deep appreciation for both the technical and human sides of software development. Now, as Director of Strategic Development at Testlio, I focus on building meaningful partnerships and aligning quality-driven insights with broader business goals, helping organizations scale confidently and deliver exceptional quality.

Visionary and results-driven, offering 15+ years of software test engineering, QA, and system engineering leadership experience. Versatile Senior Development Manager with expertise in managing test automation, DevOps, and Dev Engineering teams of up to 38 staff while enforcing standards/processes to automate the deployment of software products. Progressive and innovative, highly valued for interpreting IT vision and strategy, translating objectives into actionable plans, and providing decisive leadership to multi-functional technical and engineering staff. Articulate and organized with exceptional communication and management skills, able to effectively relate to everyone on any level. Revered by superiors, peers, and clientele for being highly collaborative and interpersonal.

I am an experienced Engineering Leader with deep expertise in reliability, observability, and infrastructure across startups and enterprise environments.

As the VP of Engineering at Defense Unicorns, I brings nearly two decades of experience building scalable systems and high-performing teams. My background spans building cloud providers, security, and data products having held senior roles at Statype, SS&C, Strava, DigitalOcean, FireEye, and more.

My goal is to always align engineering strategy with mission-driven outcomes.

Siva Prasad BV is an accomplished leader with strong expertise in Project Management, Program Management, and Client Relationship Management, delivering consistent business value across complex engagements.

He combines strategic oversight with operational excellence, bringing a solid foundation in financial management alongside deep technical understanding. His ability to align delivery execution with financial discipline ensures projects are completed efficiently, profitably, and with measurable impact