@omarsar0: Own your intelligence stack, folks. You can't scale a company to the frontier by renting intelligence. Custom models, h…
Summary
The tweet emphasizes the need for companies to own their AI intelligence stack, including custom models, harnesses, and evaluations, rather than renting, with a quote from Gabe Pereyra discussing challenges at Harvey.
View Cached Full Text
Cached at: 09/22/26, 07:57 PM
Own your intelligence stack, folks.
You can’t scale a company to the frontier by renting intelligence.
Custom models, harnesses, and evals are becoming huge assets. And if you’re building something new, you might want to consider working on any one of these, or a combination of them.
Gabe Pereyra (@gabepereyra): The hardest thing about building @harvey is doing what’s best for our customers despite immense pressure to do what’s easy.
The easy thing would have been to force our customers onto consumption pricing before they were ready and serve them worse models to protect our margins.
Similar Articles
@omarsar0: Own your intelligence. How? Start by building specialized models using agents. @oumi_ai does this well. It creates the …
Tweet highlighting Oumi AI as a platform that lets you build specialized models using agents, including data generation, recipe creation, model weights, evaluators, and deployment.
@jianxliao: That's why OSS models are so important, along with the stack to adopt those OSS models for domain-specific tasks, run t…
Emphasizes the importance of open-source AI models for domain-specific tasks, local deployment, and continuous improvement, advocating for owning intelligence rather than renting it.
Own Your Intelligence: A How-To Guide (7 minute read)
AI companies should selectively own their intelligence to address cost, latency, and data privacy constraints by using post-training and online learning to build continuously improving domain-specific models.
@GokuMohandas: https://x.com/GokuMohandas/status/2066853420326384055
This technical guide explains why organizations should build their own learning loops on open-source AI models rather than renting intelligence from frontier labs, drawing on case studies from finance, robotics, and biotech.
@omarsar0: Highly recommended read. While it looks more catered towards enterprise, it applies to every one of us (independent AI …
A recommendation to read about owning as much of the intelligence stack as possible, applicable to enterprise, independent AI developers, researchers, and startups.