AI Engineering Podcast

Mar 16 2025 49 ep. 52 mins 256
AI Engineering Podcast artwork

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  Education
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The Power of Community in AI Development with Oumi

Mar 16 2025 56 mins  
SummaryIn 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 Oumi with a mission to advance open-source AI, emphasizing the importance of community co

Arch Gateway: Add AI To Your Apps Without Custom Development

Feb 25 2025 31 mins  
SummaryIn 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 large language models (LLMs), allowing developers to focus on core business logic rather t

The Role Of Synthetic Data In Building Better AI Applications

Feb 16 2025 54 mins  
SummaryIn 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. He highlights the shift from traditional methods to using language models, which offer en

Optimize Your AI Applications Automatically With The TensorZero LLM Gateway

Jan 22 2025 63 mins  
SummaryIn 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 communication, credential management, and potential features like request-response caching

Harnessing The Engine Of AI

Dec 15 2024 55 mins  
SummaryIn 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 solutions and emphasizes the need for human oversight, multi-agent systems, and robust data m

The Complex World of Generative AI Governance

Dec 01 2024 54 mins  
SummaryIn 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 applications like healthcare. He explains that governance is more about the use cases of AI models

Building Semantic Memory for AI With Cognee

Nov 24 2024 55 mins  
SummaryIn 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 traditional training methods. He explains the challenges of forgetting in LLMs due to cont

The Impact of Generative AI on Software Development

Nov 22 2024 52 mins  
SummaryIn 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 lines of developer roles and the strategic value of AI in software development. He expl

ML Infrastructure Without The Ops: Simplifying The ML Developer Experience With Runhouse

Nov 10 2024 76 mins  
SummaryMachine 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 build a new set of utilities to reduce that friction, but have instead introduced a new ba

Building AI Systems on Postgres: An Inside Look at pgai Vectorizer

Nov 10 2024 53 mins  
SummaryWith 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 way to keep the embeddings up to date as your data changes. The team at Timescale creat