LLMs have hit a wall by scraping nearly all available public data. The next phase of AI development and competitive differentiation will come from training models on high-quality, proprietary data generated by human experts. This creates a booming "data as a service" industry for companies like Micro One that recruit and manage these experts.

The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.

With a majority of internet content now AI-generated, publishing more of the same is a losing strategy. The competitive advantage lies in creating net-new information through original research, proprietary data, and genuine expert insights. Use AI to distribute this unique content, not just to create it.

Since LLMs are commodities, sustainable competitive advantage in AI comes from leveraging proprietary data and unique business processes that competitors cannot replicate. Companies must focus on building AI that understands their specific "secret sauce."

M&A Science's "intelligence hub" differentiates from generalist AI like ChatGPT by grounding answers in a closed ecosystem of 400+ expert interviews. It provides sourced, experiential intelligence rather than generic internet-scraped guesses, making it a reliable tool for high-stakes professional work.

For entrepreneurs building on top of large language models, the key differentiator is not creating general platforms but achieving deep domain specialization. The call to arms is to know a vertical better than anyone and imbue that unique knowledge into AI agents, creating a defensible moat against more generalized tools.

As AI capabilities become commoditized, the key to superior output is the user's domain expertise. An expert with precise vocabulary can guide an AI to produce better results in one attempt than a novice can in many, because they can articulate the desired outcome more effectively.

The next frontier of competitive advantage in AI may not be public models, but proprietary 'bootleg skills'—custom markdown files—shared within trusted circles. Gatekeeping these unique, highly effective prompts and workflows could become a significant personal or corporate moat in a world of commoditized AI.

Treat AI skills not just as prompts, but as instruction manuals embodying deep domain expertise. An expert can 'download their brain' into a skill, providing the final 10-20% of nuance that generic AI outputs lack, leading to superior results.