The landscape of vibe coding — creating software through natural language interactions — is shifting toward vertical integration. Base44, the Bay Area startup acquired by Wix for $80 million last year, has begun rolling out Base1, its own proprietary large language model (LLM) designed to empower users in building applications.

Moving Beyond General-Purpose AI

By developing its own model, Base44 aims to solve the inherent limitations of relying on frontier models. Founder Maor Shlomo argues that owning the full technology stack enables significant optimizations in latency, cost, and overall efficiency.

Base1 was trained on a massive dataset comprising tens of millions of real user interactions within the platform. This specialization is intended to outperform general-purpose models in specific app-creation tasks, as Shlomo believes that while frontier models will continue to evolve, they will remain fundamentally generalist.

The Quest for Defensibility

This strategic pivot highlights a broader trend among AI startups seeking defensibility. Building on top of third-party APIs often leaves companies vulnerable to being commoditized. Jonathan Userovici, a general partner at Headline, notes that proprietary data, distribution networks, and the tech stack are the three pillars of a sustainable AI business.

While this move gives Base44 an edge over rivals like the Swedish unicorn Lovable, which relies on external LLMs, the company still faces competition from AI giants. Tools like Claude Code and integrations within Cursor are bringing frontier-level capabilities directly into the vibe coding space, creating a high-stakes race for developer mindshare.

The Inference Cost Equation

Economic pressure is a primary catalyst for this shift. As inference costs become a significant part of the operational budget, companies are seeking ways to decouple their growth from expensive API calls. Userovici points out that enterprise customers are increasingly questioning the ROI of using the most powerful models for every task, making specialized, cost-effective internal models a strategic necessity.