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PODCAST

AI Engineering Podcast

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.

technology

All Episodes

00:59:49

Context as Code, DevX as Leverage: Accelerating...

AI Engineering Podcast ·

2025/11/24

SummaryIn 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 nearly every task and the emerging role of humans as orchestrators of agents. He digs into shifting bottlenecks — code review, QA, async coordination — and how better DevX/AIX, just‑in‑time context via tools,

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01:00:52

Inside the Black Box: Neuron-Level Control and Safer...

AI Engineering Podcast ·

2025/11/16

SummaryIn 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 be misleading. Vinay shares his approach to tracing relevance through deep networks and LLMs using DL Backtrace, and how interpretability is evolving from an audit tool into a lever for alignment, enabling

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01:07:14

Building the Internet of Agents: Identity,...

AI Engineering Podcast ·

2025/11/10

SummaryIn 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, “lift-and-shift” agentic workflows with fully self-forming systems. We explore the emerging Internet of Agents, the need for open, interoperable protocols (A2A for peer collaboration and MCP for tool calling), and

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00:59:18

Agents, IDEs, and the Blast Radius: Practical AI for...

AI Engineering Podcast ·

2025/11/02

SummaryIn 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 engineers collaborate with AI agents through clear guidelines, iterative specs, and tight guardrails. Will shares practical techniques for getting real value from these tools, including loading the whole codebase for

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00:48:51

From MRI to World Models: How AI Is Changing What We See

AI Engineering Podcast ·

2025/10/27

SummaryIn 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 early deep learning for accelerated MRI, highlighting the importance of domain expertise when adapting models to specialized modalities. He explores "upstream" AI that changes what and how we measure, using

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01:06:28

Specs, Tests, and Self‑Verification: The Playbook for...

AI Engineering Podcast ·

2025/10/19

SummaryIn 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 verification are the real unlocks for reliability, and outlines a pragmatic path from “vibe coding” to AI‑first engineering. Andrew shares ZenCoder’s internal playbook: PRD and tech spec co‑creation with AI,

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01:12:19

From Probabilistic to Trustworthy: Building Orion, an...

AI Engineering Podcast ·

2025/10/11

SummaryIn 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 approach to building trustworthy analysis by grounding in semantic layers, fact tables, and quality-assurance loops, as well as their focus on accuracy through parallel test-time compute and evolving from

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00:50:53

Building Production-Ready AI Agents with Pydantic AI

AI Engineering Podcast ·

2025/10/07

SummaryIn 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 production-grade engineering to agents, focusing on strong typing, minimal abstractions, and reliability, observability, and stability. He explores the evolving agent ecosystem, patterns for single vs. many agents,

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00:55:19

From GPUs to Workloads: Flex AI’s Blueprint for Fast,...

AI Engineering Podcast ·

2025/09/28

SummaryIn 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 Aurora, highlighting how access friction and idle infrastructure slow progress. He discusses Flex AI's innovative approach to simplifying heterogeneous compute, standardizing on consistent Kubernetes layers,

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00:50:58

Right-Sizing AI: Small Language Models for Real-World...

AI Engineering Podcast ·

2025/09/20

SummaryIn this episode of the AI Engineering Podcast Steven Huels, VP of AI Engineering 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 to fit on single enterprise GPUs and provide model selection trade-offs. The conversation covers self-hosting vs using API providers, organizational capabilities needed for running production-grade LLMs, and the importance of guardrails

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00:53:32

AI Agents and Identity Management

AI Engineering Podcast ·

2025/09/13

SummaryIn 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, highlighting the importance of flexible compute environments and seamless data exchange. The conversation covers implications of AI agents on identity management, including granular permissions, OAuth protocol,

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00:51:01

Revolutionizing Production Systems: The Resolve AI...

AI Engineering Podcast ·

2025/09/04

SummaryIn 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 to provide actionable insights and solutions. The conversation highlights the architecture of Resolve AI, which integrates with existing tools to build a comprehensive understanding of production

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01:13:57

Designing Scalable AI Systems with FastMCP:...

AI Engineering Podcast ·

2025/08/26

SummaryIn 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 current role in facilitating the deployment of AI tools. The discussion covers the complexities of designing MCP servers, the importance of context engineering, and the potential pitfalls of overwhelming AI

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00:40:57

Proactive Monitoring in Heavy Industry: The Role of...

AI Engineering Podcast ·

2025/08/23

SummaryIn 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 approach to curiosity-driven AI that mimics human curiosity to improve data collection and predictive analytics. She explains how KavAI's platform uses generative AI models to enhance industrial monitoring by

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00:52:09

Navigating the AI Landscape: Challenges and...

AI Engineering Podcast ·

2025/08/07

SummaryIn 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 human behavior at scale through AI. He discusses the challenges and opportunities presented by generative AI in retail, where it complements traditional ML by enhancing explainability and personalization,

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00:46:48

The Anti-CRM CRM: How Spiro Uses AI to Transform Sales

AI Engineering Podcast ·

2025/07/21

SummaryIn 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 of traditional CRM systems where data entry is often neglected. He explains how Spiro addresses this issue by automating data collection from emails, phone calls, and other communications, providing a rich

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00:42:18

Unlocking AI Potential with AMD's ROCm Stack

AI Engineering Podcast ·

2025/06/23

SummaryIn 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 AMD's performance and capability advantages over competitors like NVIDIA. Anush addresses challenges and opportunities in AI development, including quantization, model efficiency, and future deployment across

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00:49:29

Applying AI To The Construction Industry At Buildots

AI Engineering Podcast ·

2025/06/14

SummaryIn 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 delays, and improving efficiency. Learn about the complexities of digitizing the construction industry, the technical architecture of Buildoz, and how its AI-driven solutions create a digital twin of construction

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00:51:01

The Future of AI Systems: Open Models and...

AI Engineering Podcast ·

2025/06/01

SummaryIn 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 insights on the challenges and opportunities of operating open models at speed and scale. He delves into the importance of open source in AI, the evolution of the open model ecosystem, and how Together.ai's AI

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01:01:57

The Rise of Agentic AI: Transforming Business Operations

AI Engineering Podcast ·

2025/05/21

SummaryIn 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 focus on product strategy and innovation in AI, Ben shares his expertise on what he calls the "continuum" of agentic AI - from simple function calls to complex autonomous systems. Join them as they discuss the

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67 results

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