PODCAST · technology
AI Engineering Podcast
by Tobias Macey
This show is your guidebook to building scalable and maintainable AI systems. You will learn how to architect AI applications, apply AI to your work, and the considerations involved in building or customizing new models. Everything that you need to know to deliver real impact and value with machine learning and artificial intelligence.
Episodes
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What Do Humans Do Now? Rethinking Software Engineering in the Age of AI Agents
Summary In this episode, I spoke with Jonathan Ellis about how AI agents are changing the economics of software development and forcing teams to rethink where human time is best spent. We explored his argument that, now that code generation is dramatically faster, traditional human-centered code...
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How to Evaluate RAG Systems When Ground Truth Keeps Changing
Summary In this episode Ofer Mendelevitch shares what it really takes to evaluate RAG systems in production when your source data is incomplete, constantly changing, or difficult to validate against a clean ground truth. He explores how RAG has evolved from simple “chat with your PDF” demos into...
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Harness Engineering for Reliable, Governed AI Agents
Summary In this episode Nikunj Bajaj, co-founder and CEO of TrueFoundry, talks about the challenge of building reliable agents on top of inherently variable foundation models. He explores the idea of the agent harness as everything around the model engine: memory and context management, tool and...
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Kubernetes, Compliance, and Control: The Operational Backbone of AI Sovereignty
Summary In this episode of the AI Engineering Podcast, Steven Watt, leader of the Office of the CTO at Red Hat, discusses practical paths to achieving AI sovereignty for organizations. He shares his two-decade experience in AI, highlighting how governments are building GPU platforms and protected...
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From Blind Spots to Observability: Operationalizing LLM Apps with OpenLit
Summary In this episode of the AI Engineering Podcast, Aman Agarwal, creator of OpenLit, discusses the operational foundations required to run LLM-powered applications in production. He highlights common early blind spots teams face, including opaque model behavior, runaway token costs, and…
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Taming Voice Complexity with Dynamic Ensembles at Modulate
Summary In this episode of the AI Engineering Podcast, Carter Huffman, co-founder and CTO of Modulate, discusses the engineering behind low-latency, high-accuracy Voice AI. He explains why voice is a uniquely challenging modality due to its rich non-textual signals like tone, emotion, and…
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GPU Clouds, Aggregators, and the New Economics of AI Compute
Summary In this episode I sit down with Hugo Shi, co-founder and CTO of Saturn Cloud, to map the strategic realities of sourcing and operating GPUs across clouds. Hugo breaks down today’s provider landscape—from hyperscalers to full-service GPU clouds, bare metal/concierge providers, and emerging...
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The Future of Dev Experience: Spotify’s Playbook for Organization‑Scale AI
Summary In this episode of the AI Engineering Podcast Niklas Gustavsson, Chief Architect at Spotify, talks about scaling AI across engineering and product. He explores how Spotify's highly distributed architecture was built to support rapid adoption of coding agents like Copilot, Cursor, and…
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Generative AI Meets Accessibility: Benchmarks, Breakthroughs, and Blind Spots with Joe Devon
Summary In this episode Joe Devon, co-founder of Global Accessibility Awareness Day (GAAD), talks about how generative AI can both help and harm digital accessibility — and what it will take to tilt the balance toward inclusion. Joe shares his personal motivation for the work, real-world stakes…
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Beyond the Chatbot: Practical Frameworks for Agentic Capabilities in SaaS
Summary In this episode product and engineering leader Preeti Shukla explores how and when to add agentic capabilities to SaaS platforms. She digs into the operational realities that AI agents must meet inside multi-tenant software: latency, cost control, data privacy, tenant isolation, RBAC, and...
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MCP as the API for AI‑Native Systems: Security, Orchestration, and Scale
Summary In this episode Craig McLuckie, co-creator of Kubernetes and founder/CEO of Stacklok, talks about how to improve security and reliability for AI agents using curated, optimized deployments of the Model Context Protocol (MCP). Craig explains why MCP is emerging as the API layer for…
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Context as Code, DevX as Leverage: Accelerating Software with Multi‑Agent Workflows
Summary In this episode Max Beauchemin explores how multiplayer, multi‑agent engineering is reshaping individual and team velocity for building data and AI systems. Max shares his journey from Airflow and Superset to going all‑in on AI coding agents, describing a pragmatic “AI‑first reflex” for...
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Inside the Black Box: Neuron-Level Control and Safer LLMs
Summary In this episode of the AI Engineering Podcast Vinay Kumar, founder and CEO of Arya.ai and head of Lexsi Labs, talks about practical strategies for understanding and steering AI systems. He discusses the differences between interpretability and explainability, and why post-hoc methods can…
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Building the Internet of Agents: Identity, Observability, and Open Protocols
Summary In this episode Guillaume de Saint Marc, VP of Engineering at Cisco Outshift, talks about the complexities and opportunities of scaling multi‑agent systems. Guillaume explains why specialized agents collaborating as a team inspire trust in enterprise settings, and contrasts rigid,...
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Agents, IDEs, and the Blast Radius: Practical AI for Software Engineers
Summary In this episode of the AI Engineering Podcast Will Vincent, Python developer advocate at JetBrains (PyCharm), talks about how AI utilities are revolutionizing software engineering beyond basic code completion. He discusses the shift from "vibe coding" to "vibe engineering," where…
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From MRI to World Models: How AI Is Changing What We See
Summary In this episode of the AI Engineering Podcast Daniel Sodickson, Chief of Innovation in Radiology at NYU Grossman School of Medicine, talks about harnessing AI systems to truly understand images and revolutionize science and healthcare. Dan shares his journey from linear reconstruction to...
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Specs, Tests, and Self‑Verification: The Playbook for Agentic Engineering Teams
Summary In this episode Andrew Filev, CEO and founder of ZenCoder, takes a deep dive into the system design, workflows, and organizational changes behind building agentic coding systems. He traces the evolution from autocomplete to truly agentic models, discusses why context engineering and...
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From Probabilistic to Trustworthy: Building Orion, an Agentic Analytics Platform
Summary In this episode of the AI Engineering Podcast Lucas Thelosen and Drew Gillson talk about Orion, their agentic analytics platform that delivers proactive, push-based insights to business users through asynchronous thinking with rich organizational context. Lucas and Drew share their…
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Building Production-Ready AI Agents with Pydantic AI
Summary In this episode of the AI Engineering Podcast Samuel Colvin, creator of Pydantic and founder of Pydantic Inc, talks about Pydantic AI - a type-safe framework for building structured AI agents in Python. Samuel explains why he built Pydantic AI to bring FastAPI-like ergonomics and...
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From GPUs to Workloads: Flex AI’s Blueprint for Fast, Cost‑Efficient AI
Summary In this episode of the AI Engineering Podcast Brijesh Tripathi, CEO of Flex AI, talks about revolutionizing AI engineering by removing DevOps burdens through "workload as a service". Brijesh shares his expertise from leading AI/HPC architecture at Intel and deploying supercomputers like...
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Right-Sizing AI: Small Language Models for Real-World Production
Summary In this episode of the AI Engineering Podcast Steven Huels, Vice President of AI Engineering & Product Strategy at Red Hat, talks about the practical applications of small language models (SLMs) for production workloads. He discusses how SLMs offer a pragmatic choice due to their ability…
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AI Agents and Identity Management
Summary In this episode of the AI Engineering Podcast Julianna Lamb, co-founder and CTO of Stytch, talks about the complexities of managing identity and authentication in agentic workflows. She explores the evolving landscape of identity management in the context of machine learning and AI,...
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Revolutionizing Production Systems: The Resolve AI Approach
Summary In this episode of the AI Engineering Podcast, CEO of Resolve AI Spiros Xanthos shares his insights on building agentic capabilities for operational systems. He discusses the limitations of traditional observability tools and the need for AI agents that can reason through complex systems…
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Designing Scalable AI Systems with FastMCP: Challenges and Innovations
Summary In this episode of the AI Engineering Podcast Jeremiah Lowin, founder and CEO of Prefect Technologies, talks about the FastMCP framework and the design of MCP servers. Jeremiah explains the evolution of FastMCP, from its initial creation as a simpler alternative to the MCP SDK to its...
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Proactive Monitoring in Heavy Industry: The Role of AI and Human Curiosity
Summary In this episode of the AI Engineering Podcast Dr. Tara Javidi, CTO of KavAI, talks about developing AI systems for proactive monitoring in heavy industry. Dr. Javidi shares her background in mathematics and information theory, influenced by Claude Shannon's work, and discusses her…
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Navigating the AI Landscape: Challenges and Innovations in Retail
Summary In this episode of the AI Engineering Podcast machine learning engineer Shashank Kapadia explores the transformative role of generative AI in retail. Shashank shares his journey from an engineering background to becoming a key player in ML, highlighting the excitement of understanding…
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The Anti-CRM CRM: How Spiro Uses AI to Transform Sales
Summary In this episode of the AI Engineering podcast Adam Honig, founder of Spiro AI, about using AI to automate CRM systems, particularly in the manufacturing sector. Adam shares his journey from running a consulting company focused on Salesforce to founding Spiro, and discusses the challenges…
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Unlocking AI Potential with AMD's ROCm Stack
Summary In this episode of the AI Engineering podcast Anush Elangovan, VP of AI software at AMD, discusses the strategic integration of software and hardware at AMD. He emphasizes the open-source nature of their software, fostering innovation and collaboration in the AI ecosystem, and highlights...
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Applying AI To The Construction Industry At Buildots
Summary In this episode of the Machine Learning Podcast Ori Silberberg, VP of Engineering at Buildots, talks about transforming the construction industry with AI. Ori shares how Buildots uses computer vision and AI to optimize construction projects by providing real-time feedback, reducing…
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The Future of AI Systems: Open Models and Infrastructure Challenges
Summary In this episode of the AI Engineering Podcast Jamie De Guerre, founding SVP of product at Together.ai, explores the role of open models in the AI economy. As a veteran of the AI industry, including his time leading product marketing for AI and machine learning at Apple, Jamie shares...
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The Rise of Agentic AI: Transforming Business Operations
Summary In this episode of the AI Engineering Podcast, host Tobias Macey sits down with Ben Wilde, Head of Innovation at Georgian, to explore the transformative impact of agentic AI on business operations and the SaaS industry. From his early days working with vintage AI systems to his current...
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Protecting AI Systems: Understanding Vulnerabilities and Attack Surfaces
Summary In this episode of the AI Engineering Podcast Kasimir Schulz, Director of Security Research at HiddenLayer, talks about the complexities and security challenges in AI and machine learning models. Kasimir explains the concept of shadow genes and shadow logic, which involve identifying…
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Understanding The Operational And Organizational Challenges Of Agentic AI
Summary In this episode of the AI Engineering podcast Julian LaNeve, CTO of Astronomer, talks about transitioning from simple LLM applications to more complex agentic AI systems. Julian shares insights into the challenges and considerations of this evolution, emphasizing the importance of…
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The Power of Community in AI Development with Oumi
Summary In this episode of the AI Engineering Podcast Emmanouil (Manos) Koukoumidis, CEO of Oumi, about his vision for an open platform for building, evaluating, and deploying AI foundation models. Manos shares his journey from working on natural language AI services at Google Cloud to founding...
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Arch Gateway: Add AI To Your Apps Without Custom Development
Summary In this episode of the AI Engineering Podcast Adil Hafiz talks about the Arch project, a gateway designed to simplify the integration of AI agents into business systems. He discusses how the gateway uses Rust and Envoy to provide a unified interface for handling prompts and integrating...
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The Role Of Synthetic Data In Building Better AI Applications
Summary In this episode of the AI Engineering Podcast Ali Golshan, co-founder and CEO of Gretel.ai, talks about the transformative role of synthetic data in AI systems. Ali explains how synthetic data can be purpose-built for AI use cases, emphasizing privacy, quality, and structural stability.…
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Optimize Your AI Applications Automatically With The TensorZero LLM Gateway
Summary In this episode of the AI Engineering podcast Viraj Mehta, CTO and co-founder of TensorZero, talks about the use of LLM gateways for managing interactions between client-side applications and various AI models. He highlights the benefits of using such a gateway, including standardized...
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Harnessing The Engine Of AI
Summary In this episode of the AI Engineering Podcast Ron Green, co-founder and CTO of KungFu AI, talks about the evolving landscape of AI systems and the challenges of harnessing generative AI engines. Ron shares his insights on the limitations of large language models (LLMs) as standalone...
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The Complex World of Generative AI Governance
Summary In this episode of the AI Engineering Podcast Jim Olsen, CTO of ModelOp, talks about the governance of generative AI models and applications. Jim shares his extensive experience in software engineering and machine learning, highlighting the importance of governance in high-risk…
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Building Semantic Memory for AI With Cognee
Summary In this episode of the AI Engineering Podcast, Vasilije Markovich talks about enhancing Large Language Models (LLMs) with memory to improve their accuracy. He discusses the concept of memory in LLMs, which involves managing context windows to enhance reasoning without the high costs of...
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The Impact of Generative AI on Software Development
Summary In this episode of the AI Engineering Podcast, Tanner Burson, VP of Engineering at Prismatic, talks about the evolving impact of generative AI on software developers. Tanner shares his insights from engineering leadership and data engineering initiatives, discussing how AI is blurring the...
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ML Infrastructure Without The Ops: Simplifying The ML Developer Experience With Runhouse
Summary Machine learning workflows have long been complex and difficult to operationalize. They are often characterized by a period of research, resulting in an artifact that gets passed to another engineer or team to prepare for running in production. The MLOps category of tools have tried to...
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Building AI Systems on Postgres: An Inside Look at pgai Vectorizer
Summary With the growth of vector data as a core element of any AI application comes the need to keep those vectors up to date. When you go beyond prototypes and into production you will need a way to continue experimenting with new embedding models, chunking strategies, etc. You will also need a...
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Running Generative AI Models In Production
Summary In this episode Philip Kiely from BaseTen talks about the intricacies of running open models in production. Philip shares his journey into AI and ML engineering, highlighting the importance of understanding product-level requirements and selecting the right model for deployment. The...
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Enhancing AI Retrieval with Knowledge Graphs: A Deep Dive into GraphRAG
Summary In this episode of the AI Engineering podcast, Philip Rathle, CTO of Neo4J, talks about the intersection of knowledge graphs and AI retrieval systems, specifically Retrieval Augmented Generation (RAG). He delves into GraphRAG, a novel approach that combines knowledge graphs with...
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Harnessing Generative AI for Effective Digital Advertising Campaigns
Summary In this episode of the AI Engineering podcast Praveen Gujar, Director of Product at LinkedIn, talks about the applications of generative AI in digital advertising. He highlights the key areas of digital advertising, including audience targeting, content creation, and ROI measurement, and...
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Building Scalable ML Systems on Kubernetes
Summary In this episode of the AI Engineering podcast, host Tobias Macy interviews Tammer Saleh, founder of SuperOrbital, about the potentials and pitfalls of using Kubernetes for machine learning workloads. The conversation delves into the specific needs of machine learning workflows, such as...
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Expert Insights On Retrieval Augmented Generation And How To Build It
Summary In this episode we're joined by Matt Zeiler, founder and CEO of Clarifai, as he dives into the technical aspects of retrieval augmented generation (RAG). From his journey into AI at the University of Toronto to founding one of the first deep learning AI companies, Matt shares his insights...
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Barking Up The Wrong GPTree: Building Better AI With A Cognitive Approach
Summary Artificial intelligence has dominated the headlines for several months due to the successes of large language models. This has prompted numerous debates about the possibility of, and timeline for, artificial general intelligence (AGI). Peter Voss has dedicated decades of his life to the...
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Build Your Second Brain One Piece At A Time
Summary Generative AI promises to accelerate the productivity of human collaborators. Currently the primary way of working with these tools is through a conversational prompt, which is often cumbersome and unwieldy. In order to simplify the integration of AI capabilities into developer workflows...
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ABOUT THIS SHOW
This show is your guidebook to building scalable and maintainable AI systems. You will learn how to architect AI applications, apply AI to your work, and the considerations involved in building or customizing new models. Everything that you need to know to deliver real impact and value with machine learning and artificial intelligence.
HOSTED BY
Tobias Macey
CATEGORIES
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Frequently Asked Questions
How many episodes does AI Engineering Podcast have?
AI Engineering Podcast currently has 81 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.
What is AI Engineering Podcast about?
This show is your guidebook to building scalable and maintainable AI systems. You will learn how to architect AI applications, apply AI to your work, and the considerations involved in building or customizing new models. Everything that you need to know to deliver real impact and value with machine...
How often does AI Engineering Podcast release new episodes?
AI Engineering Podcast has 81 episodes. Check the episode list to see recent publication dates and frequency.
Where can I listen to AI Engineering Podcast?
You can listen to AI Engineering Podcast on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.
Who hosts AI Engineering Podcast?
AI Engineering Podcast is created and hosted by Tobias Macey.
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