The great commoditization wave
Inspiration: Christian Garrett - 137 Ventures (TBPN)
Front-end products are hitting a wall. AI is enabling developers to produce high-quality software at an alarming rate. Without first mover advantage, software companies will struggle to convert both consumers and capital investment. The reality: consumer-facing products are becoming too easy to replicate, making it harder to build lasting competitive advantages.
So how do you build a (…cue industry term) defensible moat? This is a question I ask myself daily while planning my next steps. Christian Garrett supplied one possibility: withhold data. Restrict API access and force outside companies to use internal infrastructure (e.g., internal AI agents instead of building their own). It seems the ‘you own your data’ wave of the early 2000s was a cold lie. But this is a difficult strategy for aspiring founders with no data (like me).
Backend AI revolution in professional services
Inspiration: Aaron Frank - Lightspeed + Ryan Daniels - Crosby (TBPN)
The age-old EY model of throw bodies at the problem will quickly die. There are many use cases for AI to make immediate impact, but few better than low-level backend process automation. The real boring stuff that serves as the backbone to many of our industries. How quickly can we replace expensive professional labor with AI at scale? What level of human-involvement will be necessary? This is where my focus is, but it’s also inherently tied to the section above, “The great commoditization wave.”
I thought Ryan Daniels segment on TBPN was fascinating. His team is creating Crosby, an agentic law firm that owns the full life cycle of project workflows. They started with questions like: (1) Which work requires resumé credibility vs. which just needs to get done? (2) Which workflows are easiest to automate, but maintain critical impact? The applied AI framework is truly every VC’s wet-dream. It's scalable, addresses massive market pain points, and doesn't require a defensible moat.
Other commentary
VCs are pricing themselves out of early-stage deals. Funds are growing too large to justify smaller acquisitions. I think this is up to the founders to say no to high valuations as well. (Source: TBPN crew)
AI winners won’t be pure tech. Companies like Crosby will have unique advantages and many player’s can operate in the same space. What does this structure mean for the traditional venture model?
The data wars sound like a nightmare.