Loïc Houssier, Head of Engineering at Superhuman, joins us to discuss how AI and LLMs are reshaping the email experience. He highlights challenges related to the variability of user prompts and infrastructure optimization. Loïc emphasizes that a deep focus on user experience and real human workflows is key to building AI tools people actually love to use.

Featuring:

• Loïc Houssier – LinkedIn
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Links:

• Superhuman
• Referral Code for a Free month

Sponsors:

• Outshift by Cisco – AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.

In this episode, Daniel and Chris unpack the Model Context Protocol (MCP), a rising standard for enabling agentic AI interactions with external systems, APIs, and data sources. They explore how MCP supports interoperability, community contributions, and a rapidly developing ecosystem of AI integrations. The conversation also highlights some real-world tooling such as FastAPI-MCP.

Featuring:

• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Links:

• Protocol website
• Anthropic blog post
• Blog post - Model Context Protocol (MCP) an overview
• FastAPI-MCP
• How to Use FastAPI MCP Server: A Complete Guide
• Candle (Rust framework)

In this episode, we explore the intersection of AI, machine learning, and healthcare through the lens of neuroimaging and epilepsy diagnosis. Dr. Gavin Winston shares insights from his work using MRI data and machine learning to uncover subtle abnormalities in brain function. We discuss the cultural and ethical barriers to AI adoption in medicine, how predictive data analysis could transform the diagnostic workflow, and what the future holds for medical imaging in a world increasingly shaped by intelligent systems.

Featuring:

• Gavin Winston – LinkedIn, Website
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Links:

• Detection of Epileptogenic Focal Cortical Dysplasia Using Graph Neural Networks: A MELD Study
• Machine Learning in Neuroimaging across Disciplines
• Automated and Interpretable Detection of Hippocampal Sclerosis in Temporal Lobe Epilepsy: AID-HS
• Literature review and protocol for a prospective multicentre cohort study on multimodal prediction of seizure recurrence after unprovoked first seizure
• Deep learning in neuroimaging of epilepsy
• Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy
• Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data