Jason's Team Achieves 10x Efficiency with Lovable for Internal Tools
Jason revealed that his team has built multiple internal tools using Lovable over the past month, completing projects that previously required over $100,000 in outsourced development in just 4-16 hours.
The team has productized the "whisper network," allowing founders to upload materials through a portal, which are then automatically forwarded as customized emails by 10 investment team members without the need for manual email checking.
In terms of market mechanisms, incubators are accelerating the adoption of AI-native tools to replace traditional development and manual processes, shifting funds and time from high-cost outsourcing to internal productivity leverage. Lovable and similar AI development platforms benefit from this trend, while traditional development service providers face pressure.
Source: Public Information
ABAB AI Insight
Jason Calacanis, a well-known angel investor and founder of the LAUNCH incubator, has long relied on manual networks for VC matching. This rapid productization continues his previous approach of iterating operational processes using tools like Notion and Airtable, focusing on transforming personal relationship capital into scalable systems.
In terms of capital pathways, Jason's team directly uses Lovable in the core funnel of the incubator, automating the connection between founders' pitch materials and investors' emails. This effectively shifts limited partner time from repetitive administrative tasks to high-value meeting selection, motivated by the goal of using AI to amplify a single incubator's capacity to handle quality projects, leading to more deals and follow-ups.
Similar cases include a16z's early use of internal tools to enhance due diligence efficiency and Y Combinator's batch application system. The incubation and early investment industry is currently transitioning from a manual network dominance to AI infrastructure control, with top incubators simultaneously deploying accelerated stratification.
Essentially, this represents a technological substitution: traditional high-cost manual and outsourced development is rapidly replaced by AI-generated tools. The fundamental mechanism is that platforms like Lovable lower the programming barrier to the level of natural language, enabling non-technical teams to build productivity tools in a very short time frame, thus achieving a structural leap in capital allocation efficiency.
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