Episode
GN 70: AI - The Enemy that we Love
- Podcast
- Goldcasting Podcast
- Published
- Apr 30, 2026
- Duration seconds
- 2338
- Processing state
not_requested
Actions
POST https://stenobird.com/v1/public/podcasts/goldcasting-podcast-6612990/episodes/gn-70-ai-the-enemy-that-we-love/transcription-requests
Idempotently request low-priority transcript generation for this episode.GET https://stenobird.com/podcast/goldcasting-podcast-6612990/gn-70-ai-the-enemy-that-we-love.md
Read the agent-friendly Markdown representation of this episode resource.
Summary
AI is no longer something the foundry industry can laugh off as a distant software trend. Large language models are already being used by engineers, buyers, designers, and decision-makers to explore manufacturing options, compare processes, prepare for meetings, and form first impressions of suppliers. In this episode, Fabian Niklas and Staffan Zetterström look at AI from the perspective of foundry guys, not AI experts. The central concern is not that LLMs (Large Language Models) exist. The real problem is that LLMs often provide poor or outdated answers about casting because the foundry industry has not produced enough accessible, up-to-date, publicly available information for these systems to learn from. That has direct commercial consequences. If an engineer, product designer, or purchasing team asks an LLM whether a part should be cast, the answer may be shaped by outdated textbook assumptions rather than by modern high-pressure die-casting practices. In the worst case, AI does not just misunderstand casting, it quietly sends potential customers somewhere else. The episode is a grounded conversation about what AI can do, where it fails, and why foundries should start testing it from the perspective of their target customers. Key Topics * Why AI drives customers away from casting When an engineer asks an LLM for manufacturing advice, the answer depends on the information available online. If current casting knowledge and marketing material are missing, the model may recommend against casting based on outdated assumptions. * The foundry industry has a visibility problem AI often fails to distinguish between older textbook descriptions and modern die-casting processes. The issue is not only technical accuracy but also the lack of publicly searchable material showing w…