Investment and Innovation in the Age of AI

Jess Schram
Remedy Product Studio
5 min readApr 26, 2024


Key Takeaways from the Startup Grind Conference

I just wrapped up a whirlwind week at the Startup Grind conference in San Francisco. Of course, AI dominated the majority of the conversation, so I wanted to recap a few of my favorite insights and contrarian takes about how the new technology is changing the startup landscape. Let’s dive in.

Left to right: Elsa Hyland (Angel Investor), Ashley Huang of Scrum Ventures, Jess Schram (me) of Remedy Product Studio, and Katie Swanson of SAIC’s CVC

CaaS (Cognition as a Service) vs. SaaS (Software as a Service)

One of my favorite takeaways at the conference came from Vanessa Larco of NEA during a Q&A session about Investing in AI. Larco proposed a transformative view on the future of SaaS companies and, specifically, how to think about pricing models in the age of artificial intelligence.

Traditionally, SaaS companies monetize on a per-user basis or a price-per-seat model. However, as AI helps companies operate faster and more efficiently, many businesses will choose to reduce their workforce. This reduction in human capital can cannibalize the business model if the SaaS tool/solution adds value to the point where the companies employing it require fewer human resources to do the job.

As a response to this shift in org dynamics, Larco suggests a future where SaaS companies will employ a value-based pricing model akin to VBC compensation in healthcare. With this approach, pricing would be directly tied to the value generated by the software instead of the number of people using it.

For example, if an AI marketing tool claims to optimize revenue for eComm businesses, a value-based pricing model may employ a take rate on the incremental lift in sales achieved through the CaaS tool’s performance. This shift in value could redefine how we assess and pay for digital tools, focusing more on outcomes rather than output.

My thoughts:

  • How will this shift impact the B2B SaaS landscape? Will companies that adopt a value-based pricing model have a competitive advantage over those that stick with traditional pricing models?
  • How will this new pricing model impact the revenue potential for SaaS companies? Will it lead to higher revenue per customer, or will it result in fewer customers due to higher pricing?
  • How can investors mitigate the risks associated with this shift in pricing models? Are there ways to hedge against potential downsides?
Left to right: James Joaquin of Obvious Ventures, Vanessa Larco of NEA, and Kobie Fuller of Upfront Ventures

Generative Science vs. Generative Pre-trained Transformers (GPTs)

While the buzz around AI was deafening at Startup Grind, 90% of the businesses I saw were glorified wrappers around ChatGPT.

As many know, GPT models are trained on internet text data, which allows them to produce coherent responses relevant to the context at hand. This makes them useful for a variety of applications, including content creation, translation, and answering questions.

The use of text data doesn’t make these startups any less compelling or potentially lucrative, but it does create a repeatable pattern of “sameness.” And while many investors are throwing their weight behind large language models (LLMs) and similar technologies, it was refreshing to hear James Joaquin of Obvious Ventures talk about a contrarian strategy — investing in Generative Science.

Instead of being trained on text data, Generative Science companies are trained on databases of genes, proteins, and biomarkers. These companies aim to harness AI’s potential to revolutionize our approach to curing diseases and tackling previously insurmountable science problems.

My thoughts:

  • Will AI one day be smart enough to derive solutions based on combinations of scientific theories, principles, and elements for problems that have never been solved before?
  • Will AI one day be smart enough to train itself?
  • At what point does AI become the founder vs. the invention, and where does the concept of “idea ownership” start and stop?
  • What new legal ramifications will come to fruition as humans grow increasingly unable to fact-check AI because it is producing net-new information? How will humans accept/adopt this?
Left to right: Garry Tan of Y Combinator, Derek Andersen of Bevy & Startup Grind

The Diminishing Moat vs. The New Moat

A recurring theme at the conference — and a personal takeaway — is the evolving concept of a company’s moat in the software industry. It’s becoming evident that as technology becomes more accessible and easier to develop and deploy, the traditional barriers to entry, such as technological uniqueness and defensibility, are eroding.

Instead, I believe businesses’ real competitive advantage today lies in their execution, distribution, and understanding of their customers’ needs. In other words, back to basics.

Companies need to ask themselves: Are we addressing a significant problem for a large enough audience? How robust is our distribution network and why are we (or am I, as a founder) uniquely qualified to sell to this audience? Can we outpace our competitors in execution? And, crucially, how do we ensure our solution remains indispensable?

Novelty vs. Execution and Customer Obsession

Achieving a “sticky” product that customers cannot live without isn’t about launching a perfect solution on day one — it’s about speed to market, agility in product development, and a relentless focus on aligning with customer feedback.

This new moat isn’t about having the best or most novel idea, but rather about continuously refining it, staying ahead of user demands, and executing flawlessly so customers have no reason to churn. This product-first approach will foster not only better retention but also advocacy, driving both near-term growth and long-term success.

As I return to New York, my mind is overflowing with ideas and questions for our team and partners at Remedy Product Studio.

  • How can we integrate these insights into our investment strategy and incubation processes?
  • How do we adapt to a rapidly changing landscape where value, data, and execution become the pillars of success?
  • How can we help our partners think about unique business models to stay ahead of the curve to maximize their revenue potential?
  • How do we deliver on our promise of building best-in-class technology that functions so well it can command value-based pricing?

The path forward is as exciting as it is daunting, and I look forward to exploring these themes more deeply with our community.

Fun times at Startup Grind!

If you want to nerd out further or are building something awesome, please don’t hesitate to reach out!



Jess Schram
Remedy Product Studio

Director of Investments & Incubations @Remedy Product Studio. Formerly at 14W, Lerer Hippeau, and Swiftarc Ventures. All thoughts are my own.