AI in the SDLC - Engineering Workflows in the Age of AI
Abstract
The first wave of AI in software engineering introduced assistive tools that helped developers generate code, tests, or documentation faster. Today, engineering teams are beginning to experience the next shift where AI systems participate directly in development workflows.
From proposing code changes and generating validation artifacts to triggering actions within build and release pipelines, AI is moving beyond code suggestions into execution across the Software Development Lifecycle (SDLC). This evolution is gradually transforming how requirements are translated into implementation, how validation is integrated into delivery pipelines, and how software changes flow from idea to production.
This panel brings together engineering leaders to explore how development and delivery workflows are evolving from AI-assisted practices towards models where AI becomes an active participant in build, test, and release processes.
Key Takeaways
1. Innovation creates noise, making obvious truths harder to see.
2. Question if a problem really needs GenAI or if existing tools suffice.
3. Understand GenAI’s true value beyond the hype.
4. Old and new solutions should complement, not replace, each other.
5. A real-world case study shows how GenAI can be used effectively.
6. Clarity comes from cutting through illusions and embracing simplicity.
About Speaker
Pankaj Bavishi is a transformative technology leader and currently serves as Vice President of Engineering – SaaS and Cloud Protection Services at Cohesity. With over 25 years of experience spanning enterprise software, multi-cloud platforms, and cyber resilience, Pankaj has led the design and delivery of highly scalable, secure systems adopted by enterprises worldwide, having held senior leadership roles at Dell EMC, IBM, and Computer Associates (now part of Broadcom).
Pankaj’s current focus is on applying AI to improve engineering productivity, software quality, operational resilience, and security in modern SaaS and cloud platforms. He is also involved in AI-led capabilities that introduce intelligent insights, automation, and decision support into engineering and operational workflows, helping teams manage complex systems more effectively. He is passionate about enabling engineering teams to adopt practical AI approaches that deliver real, measurable impact. Pankaj holds multiple patents and a Master’s degree in Computer Science from Northeastern University
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