Amjad Masad

Future AI products will not be built on a single model but on an orchestrated ecosystem of specialized models.

"I actually wrote about it back in '22. I said it's going to be society of models, like products will be made of a lot of different models, and it's quite a heavy engineering project."

AI enables a future of 'hyper-efficient' companies where core functions like support and development are fully automated, allowing founders to focus purely on value creation.

"I could imagine whatever, five years from now, someone running a billion dollar company with zero employees where it's like the support is handled by AI, the development is handled by AI, and you're j..."

Advanced AI applications rely on a 'society of models' where different LLMs are assigned specialized roles like coding, critiquing, or managing.

"The most important model that we use is the Sonnet model from Claude, from Anthropic, and it is the best model at coding. So that's the model we use for coding, but we use models from OpenAI as well b..."

The ROI on learning to code is doubling every six months because AI amplifies the power of even basic technical literacy.

"Learning a bit of skill about how to prompt AI, how to read code, and be able to debug it. Every six months, that's netting you more and more power because you're going to be able to create a lot more..."

Code and working prototypes are becoming the 'universal language' that breaks down silos between design, product, and engineering.

"One of the things that I think is sort of hard about tech companies is these silos between designers, product managers, and engineers... the common language that everyone shares is code. Ultimately in..."

The rise of 'hybrid' roles (designers who code, engineers who design) requires a more fluid, less structured organizational culture.

"You got to be fluid because again, when designers can code and engineers can design, I mean it really becomes, you can't have a lot of structure around that. So you want to build a culture and you wan..."

In the AI era, rigid roadmaps are a liability; teams must be able to pivot instantly when new model capabilities are released.

"Being agile, not being stuck with roadmaps, being able to just say, oh, we're just going to switch priorities right away, is going to be super important... there's going to be capabilities that are go..."

Effective problem definition in the AI era involves crafting highly descriptive prompts that outline specific user roles, features, and desired outcomes.

"I asked RPM at Replit, Aman Mathur who's a fan of the show to tell me what PMs like to build. And so he came up with a prompt. He kind of really crafted a great prompt... basically, what we're asking..."

AI tools allow PMs to bypass engineering bottlenecks to create functional prototypes for real-world user testing.

"We've seen product managers build, like I said, like a v1 of an app and actually go out and test it with users. I can't name the company, but there's a public company that have used Replit to test a v..."

Modern platforms are abstracting the complexity of cloud infrastructure, allowing non-technical builders to deploy production-ready applications instantly.

"Let's actually just deploy it really quickly to show people how you can deploy... We use Google Cloud. So we abstract all of that away from you, but we use Google Cloud behind the scenes."