Interview based show around AI Engineering. Episodes are also available as video on Youtube. Show notes have a summary and full transcript.
Episodes
17 Mar 2026
Cowork is a cloud-native tool simplifying Cloud Code access for non-technical users through a balance of simplicity and flexibility, integrating with cloud services and Chrome while supporting diverse workflows via a lightweight virtual machine, developed in 10 days with a focus on modular components and ethical trade-offs in AI infrastructure.
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12 Mar 2026
TurboPuffer is a next-gen database platform focusing on AI-powered vector search, full-text search, and scalability, with a strong emphasis on hiring top talent and customer-driven innovation.
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10 Mar 2026
Advancements in AI agents focus on automating complex tasks, optimizing resource management, and addressing efficiency and scalability challenges.
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6 Mar 2026
Software development is evolving with the integration of AI and agentic systems, requiring a balance between automation and human expertise to optimize workflows.
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5 Mar 2026
The integration of AI in enterprise software and its cultural impact on film, media, and software engineering are explored in this podcast.
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27 Feb 2026
The podcast explores the intersection of AI capabilities and societal risks, discussing challenges in evaluating and deploying AI systems.
Open episode![[LIVE] Anthropic Distillation & How Models Cheat (SWE-Bench Dead) | Nathan Lambert & Sebastian Raschka thumbnail](https://substackcdn.com/feed/podcast/1084089/post/189277598/ca7468da5614a246d2906ee8926f6de7.jpg)
26 Feb 2026
A podcast discusses the application of distillation in machine learning, particularly in training smaller language models, and raises concerns about the potential for malicious use and the need for improved detection and regulation.
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25 Feb 2026
Physicists, machine learning experts, and materials scientists explore the intersection of their fields to accelerate material discovery and tackle challenges like climate change.
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24 Feb 2026
The limitations of AI's current capabilities are discussed, highlighting the need for meta-learning to improve it and achieve true effectiveness.
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23 Feb 2026
C-bench Verified, a coding benchmark, has faced challenges such as task saturation, biased tasks, and overlapping training data, prompting the need for more advanced alternatives and a reevaluation of broader issues in AI coding evaluation.
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