Hugo Bowne-Anderson

3 weeks ago | vanishinggradients.fireside.fm | Hugo Bowne-Anderson

What if building software felt more like composing than coding? In this episode, Hugo and Greg explore how LLMs are reshaping the way we think about software development—from deterministic programming to a more flexible, prompt-driven, and collaborative style of building. It’s not just hype or grift—it’s a real shift in how we express intent, reason about systems, and collaborate across roles.

2 months ago | vanishinggradients.fireside.fm | Hugo Bowne-Anderson

Vanishing Gradients Your browser does not support the audio tag. 00:00:00 / 01:17:30 Share Page Embed Code Subscribe & Share RSS Feed Download (71 MB) February 21st, 2025 Too many teams are building AI applications without truly understanding why their models fail. Instead of jumping straight to LLM evaluations, dashboards, or vibe checks, how do you actually fix a broken AI app?

2 months ago | vanishinggradients.fireside.fm | Hugo Bowne-Anderson

AI coding assistants are reshaping how developers write, debug, and maintain code—but who’s really in control? In this episode, Hugo speaks with Tyler Dunn, CEO and co-founder of Continue, an open-source AI-powered code assistant that gives developers more customization and flexibility in their workflows. In this episode, we dive into:• The trade-offs between proprietary vs. open-source AI coding assistants—why open-source might be the future.

Jan 21, 2025 | oreilly.com | Hugo Bowne-Anderson |Alan Nichol

Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) don’t deliver the reliability needed for production systems. The prompt-and-pray model—where business logic lives entirely in prompts—creates systems that are unreliable, inefficient, and impossible to maintain at scale. A shift toward structured automation, which separates conversational ability from business logic execution, is needed for enterprise-grade reliability.

Nov 5, 2024 | vanishinggradients.fireside.fm | Byung-Chul Han |Hugo Bowne-Anderson

Hugo speaks with Jason Liu, an independent AI consultant with experience at Meta and Stitch Fix. At Stitch Fix, Jason developed impactful AI systems, like a $50 million product similarity search and the widely adopted Flight recommendation framework. Now, he helps startups and enterprises design and deploy production-level AI applications, with a focus on retrieval-augmented generation (RAG) and scalable solutions. This episode is a bit of an experiment.