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PostHeaderIcon [RivieraDev2025] Dhruv Kumar – Platform Engineering + AI: The Next-Gen DevOps

At Riviera DEV 2025, Dhruv Kumar delivered an engaging presentation on platform engineering, a discipline reshaping software delivery by addressing modern development challenges. Stepping in for Silva Devi, Dhruv, a senior product manager at CloudBees, explored how platform engineering, augmented by artificial intelligence, streamlines workflows, enhances developer productivity, and mitigates the complexities of cloud-native environments. His talk illuminated the transformative potential of internal developer platforms (IDPs) and AI-driven automation, offering a vision for a more efficient and secure software development lifecycle (SDLC).

The Challenges of Modern Software Development

Dhruv began by highlighting the evolving responsibilities of developers, who now spend only about 11% of their time coding, according to a survey by software.com. The remaining time is consumed by non-coding tasks such as testing, deployment, and managing security vulnerabilities. The shift-left movement, while intended to empower developers by integrating testing and deployment earlier in the process, often burdens them with tasks outside their core expertise. This is compounded by the transition to cloud environments, which introduces complex microservices architectures and distributed systems, creating navigation challenges and integration headaches.

Additionally, the rise of AI has accelerated software development, increasing code volume and tool proliferation, while supply chain attacks exploit these complexities, demanding constant vigilance from developers. Dhruv emphasized that these challenges—fragmented workflows, heightened security risks, and tool overload—necessitate a new approach to streamline processes and empower teams.

Platform Engineering: A Unified Approach

Platform engineering emerges as a solution to these issues, providing a cohesive framework for software delivery. Dhruv defined it as the discipline of designing toolchains and workflows that enable self-service capabilities for engineering teams in the cloud-native era. Central to this is the concept of an internal developer platform (IDP), which integrates tools and processes across the SDLC, from coding to deployment. By establishing a common SDLC model and vocabulary, platform engineering ensures that stakeholders—developers, QA, and security teams—share a unified understanding, reducing miscommunication and enhancing actionability.

Dhruv highlighted three pillars of effective platform engineering: a standardized SDLC model, secure best practices embedded in workflows, and the freedom for developers to use familiar tools. This last point, supported by a Forbes study from September 2023, underscores that happier developers, using tools they prefer, complete tasks 10% faster. By fostering collaboration and reducing context-switching, platform engineering creates an environment where developers can focus on innovation rather than operational overhead.

AI as a Catalyst for Optimization

Artificial intelligence plays a pivotal role in amplifying platform engineering’s impact. Dhruv explained that AI’s value lies not in generating code but in filtering noise and optimizing practices. By leveraging a robust SDLC data model, AI can provide actionable insights, provided it is fed high-quality data. For instance, AI-driven testing can prioritize time-intensive issues, streamline QA processes, and run only relevant tests based on code changes, reducing costs and feedback cycles. Dhruv cited examples like AI agents identifying vulnerabilities in code components or assessing risks in production ecosystems, automating fixes where appropriate.

He also introduced the Model Context Protocol (MCP), an open standard that enables applications to provide context to large language models, enhancing AI’s ability to deliver precise recommendations. From troubleshooting CI/CD pipelines to onboarding new developers, AI, when integrated with platform engineering, empowers teams to address bottlenecks and scale efficiently in a cloud-native world.

Empowering Developers and Securing the Future

Dhruv concluded by emphasizing that platform engineering, bolstered by AI, re-engages all actors in the software delivery process, from developers to leadership. By normalizing data across tools and providing metrics like DORA (DevOps Research and Assessment), IDPs offer visibility into bottlenecks and investment opportunities. This holistic approach not only secures the tech stack against supply chain attacks but also fosters a culture of productivity and developer satisfaction.

He encouraged attendees to explore CloudBees’ platform, which exemplifies these principles by breaking free from traditional platform limitations. Dhruv’s call to action urged developers to adopt platform engineering practices, leverage AI for optimization, and provide feedback to refine these evolving methodologies, ensuring a future where software delivery is both efficient and resilient.

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