Nick Turley

Credit where credit is due I think NotebookLM is awesome and differentiated and helps me learn new stuff. I think it's great. When a leading product executive at OpenAI explicitly praises a competitor's product as awesome and differentiated, it signals that Alphabet is successfully innovating at the application layer. Google's ability to leverage its massive data ecosystem into unique, sticky AI tools proves it is not being entirely disrupted by OpenAI and remains a formidable builder. LONG. Alphabet retains massive distribution and is proving capable of building highly differentiated AI applications that even industry rivals admire. Cannibalization of traditional high-margin search ad revenue by higher-compute, direct-answer AI queries.

I'm really excited about these companies that are going into companies and getting extremely hands-on and doing effectively professional services with AI because we've saturated all the emails and you need to get proximate to the problems. The initial wave of AI adoption was horizontal (basic chatbots and email drafting). The next wave of massive value creation is vertical and outcome-based. Companies like Palantir and ServiceNow that embed AI directly into complex corporate workflows to act as automated professional services will capture this next enterprise TAM. LONG. Enterprise AI integration is moving from basic API calls to deep, hands-on operational execution, heavily favoring established platforms with deep enterprise access. Enterprise sales cycles are notoriously long, and internal IT departments may attempt to build these integrations in-house using open-source models.

GPUs are zero sum and if you don't have more GPUs you really have to figure out how do you make very very hard trades... demand keeps going up even as prices go down. When you just look at token consumption per user... you see a lot of very GPU hungry workflows. As AI models evolve from simple text generation to reasoning (test-time compute) and autonomous agents, the compute required per user query scales exponentially. This guarantees sustained, insatiable demand for the underlying silicon provided by Nvidia and manufactured by TSMC, regardless of which software layer ultimately wins the consumer war. LONG. Compute remains the fundamental bottleneck and the most valuable, zero-sum resource in the AI economy. Geopolitical tensions affecting Taiwan (TSMC) or a sudden breakthrough in algorithmic efficiency that drastically reduces hardware compute requirements.

I'm really excited about these companies that are going into companies and getting extremely hands-on and doing effectively professional services with AI because we've saturated all the emails and you need to get proximate to the problems. The initial wave of AI adoption was horizontal (basic chatbots and email drafting). The next wave of massive value creation is vertical and outcome-based. Companies like Palantir and ServiceNow that embed AI directly into complex corporate workflows to act as automated professional services will capture this next enterprise TAM. LONG. Enterprise AI integration is moving from basic API calls to deep, hands-on operational execution, heavily favoring established platforms with deep enterprise access. Enterprise sales cycles are notoriously long, and internal IT departments may attempt to build these integrations in-house using open-source models.

GPUs are zero sum and if you don't have more GPUs you really have to figure out how do you make very very hard trades... demand keeps going up even as prices go down. When you just look at token consumption per user... you see a lot of very GPU hungry workflows. As AI models evolve from simple text generation to reasoning (test-time compute) and autonomous agents, the compute required per user query scales exponentially. This guarantees sustained, insatiable demand for the underlying silicon provided by Nvidia and manufactured by TSMC, regardless of which software layer ultimately wins the consumer war. LONG. Compute remains the fundamental bottleneck and the most valuable, zero-sum resource in the AI economy. Geopolitical tensions affecting Taiwan (TSMC) or a sudden breakthrough in algorithmic efficiency that drastically reduces hardware compute requirements.