AI model

also referred to as: ai models

9 statements across 5 episodes · 5 bullish · 1 bearish · 5 people on the record · first statement Nov 9, 2023 by Anastasis Germanidis · across every show →

Everything said about AI model, oldest first

Nov 9, 2023 positive
Insight
Germanidis: AI tools succeed by translating raw models into design vocabulary
“Once artists understood how to use those tools, it would make amazing things with those tools, but it was the barrier to entry was really high. So just providing that like translation layer between creating this technology and AI models and the more vocabulary…”
Anastasis Germanidis Nov 9, 2023 ▶ 8:03 How goal-setting and planning is different for AI products | Anastasis Germanidis (Runway)
Nov 9, 2023 bullish
Prediction Not checkable as stated
AI industry focus will shift from foundation models to workflows and UIs
“I think we're going to move from focusing a lot on the models and the foundations to focusing on the workflows and the tools and the UIs and the specific products that we built around AI models. And that's going to be, I think, a lot of the focus for kind of t…”
Anastasis Germanidis Nov 9, 2023 ▶ 52:50 How goal-setting and planning is different for AI products | Anastasis Germanidis (Runway)
Jun 6, 2024 neutral
Disclosure
Schillace: Microsoft's experimental AI team explores agent mechanics instead of shipping products
“I've got a team right now at Microsoft that's This sort of experimental prototyping team. It's just the whole thing is like a jazz ensemble. It's really wild. We don't really ship products. We're trying to explore the space and understand some deep things abou…”
Sam Schillace Jun 6, 2024 ▶ 12:33 Developing technical taste: A guide for next-gen engineers | Sam Schillace (Microsoft, Google Docs)
Jun 6, 2024
Insight
Schillace: Engineers should think with AI models but plan with code
“The easy way to understand this is when I say you should think with the model, but plan with code because the models are, they're stochastic and fuzzy. And so if you want something reliable, you should build kind of a scaffold around it in code, something exec…”
Sam Schillace Jun 6, 2024 ▶ 37:20 Developing technical taste: A guide for next-gen engineers | Sam Schillace (Microsoft, Google Docs)
Oct 22, 2025 bullish
Prediction Not checkable as stated
Model commoditization will drive fragmentation, favoring multi-model platforms like fal
“So it looks like it's going to be really hard for someone to differentiate with the quality of the model. And we believe this is going to lead to even, even more fragmentation. So a company like Fall where you get to access many different models at the same ti…”
Gorkem Yurtseven Oct 22, 2025 ▶ 29:48 The pivot that paid off: How fal found explosive growth | Gorkem Yurtseven (Co-founder and CTO)
Oct 22, 2025 bullish
Insight
Off-the-shelf models eliminate data prep for all but the largest enterprises
“If there's a ready-made model that changes everything, this whole like data preparation stage. Can be skipped and only like the biggest of the companies are going to do that. Everyone else, they'll just use something off the shelf.”
Gorkem Yurtseven Oct 22, 2025 ▶ 6:44 The pivot that paid off: How fal found explosive growth | Gorkem Yurtseven (Co-founder and CTO)
Oct 23, 2025 bearish
Opinion
Stauch: Future AI could allow startups to rapidly copy software
“The competitor I'm most worried about is the one that doesn't exist yet. The one that comes along a couple of years from now. And maybe these tools have unlocked so many crazy capabilities that they're able to move very quickly and build so much of what we bui…”
Jake Stauch Oct 23, 2025 ▶ 45:11 Go hard early: How lessons from Verkada shaped this AI-native IT platform | Jake Stauch (Serval)
Jul 24, 2026 positive
Insight
Noronha: Building smaller product surface areas lets AI fill white space
“Particularly in this world of rapidly advancing AI models, it's actually a really healthy instinct, because the less you build as product surface area, the more that the AI can actually fill in, in actually the white space.”
Jon Noronha Jul 24, 2026 ▶ 28:56 How Gamma pulled off their AI pivot | Jon Noronha (Co-founder and CPO of Gamma)
Jul 24, 2026 neutral
Insight
AI products require disposable engineering systems lasting only six to twelve months
“The classic design mindset is make a quick prototype and throw it away. The classic engineering mindset is build durable systems that can last for 10 years. We find ourselves in this in-between, where we have to build systems that last for six to 12 months. At…”
Jon Noronha Jul 24, 2026 ▶ 35:24 How Gamma pulled off their AI pivot | Jon Noronha (Co-founder and CPO of Gamma)
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