Mojtaba Sarooghi, a Distinguished Product Architect at Queue-it, speaks with host Jeremy Jung about virtual waiting rooms for high-traffic events such as concerts and limited-quantity product releases. They explore using a virtual queue to prevent overloading systems, how most traffic is from bots, using edge workers to reduce requests to the customer's origin servers, and strategies for detecting bots in cooperation with vendors. Mojtaba discusses using AWS services like Elastic Load Balancing, DynamoDB, and Simple Notification Service, and explains why DynamoDB's eventual consistency is a good fit for their domain. To explain the approach, he walks us through how his team resolved an incident in which a traffic spike overloaded their services.

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In this episode, Benjamin Brial, CEO and co-founder of Cycloid, speaks with host Sriram Panyam about internal developer platforms (IDPs) and internal developer portals. The conversation explores how these platforms address the growing challenges of DevOps scalability, multi-cloud complexity, and cloud waste, all of which organizations face as they grow.

Benjamin begins by framing the core problems that IDPs solve: DevOps struggling to scale beyond small teams, the complexity of managing hybrid environments across on-premises, public cloud, and private cloud infrastructure, and the significant issue of cloud waste (averaging 35-45% according to major analysts). IDPs can serve as a bridge between DevOps teams and developers, providing access to tools, cloud resources, and automation for users who aren't DevOps or cloud experts. The technical discussion covers essential IDP components including service catalogs, versioning engines, platform orchestration, asset inventory, and FinOps/GreenOps modules. The episode concludes with Benjamin's practical advice: organizations should focus on understanding their specific pain points rather than following market trends, starting with simple use cases such as landing zones before building complex solutions, and adopt a GitOps-first approach as the foundation for any IDP implementation.

Brought to you by IEEE Computer Society and IEEE Software magazine.

In this episode of Software Engineering Radio, Srujana Merugu, an AI researcher with decades of experience, speaks with host Priyanka Raghavan about building LLM-based applications. The discussion begins by clarifying essential concepts like generative vs. predictive AI, pre-training vs. fine-tuning, and the transformer architecture that powers modern LLMs.

Srujana explains diffusion models and vision transformers, highlighting how multimodal AI is reshaping content creation. The conversation then moves to practical aspects—where LLMs make sense, where they don't, and a decision framework for evaluating use cases. They explore common application patterns such as retrieval-augmented generation (RAG) and agentic architectures, breaking down components like planners, orchestrators, memory, and tools. Key considerations for model selection, evaluation metrics, and safety guardrails are discussed in depth. The episode also touches on prompting strategies, automated prompt optimization, and emerging trends like multi-sensory AI and the "Internet of Senses." Finally, Srujana shares tips on staying current in a fast-moving AI landscape and emphasizes lifelong learning and curated knowledge sources.