A hole in the wall
David Peterson

Our friend Christoph from Point Nine made a prediction last week that got me thinking:

It’s a useful thought experiment for entrepreneurs and early stage investors alike. In a world where AI can do a lot of what humans can do, how will software evolve?

To help think through what products might look like in our AI-powered future, it’s worth recalling what is one of the most powerful and ubiquitous AI-powered products of our past: Google’s conversion optimizer.

Back in the early 2000s, paid marketing was an entirely different beast than it is today. Marketing teams spent a lot of their time figuring out what amount to bid. Go far enough back in Search Engine Land and you’ll see what life was like.

Then, in late 2007, Google’s conversion optimizer launched. And in what may have been the first job that artificial intelligence replaced, all of a sudden, paid marketers didn’t really need to bid anymore. Instead, they refocused their efforts on two things:

First, data. The more relevant data marketers could pipe back into Google, the better the conversion optimization worked. At the beginning, this meant sending back conversion data. Eventually, this started to include product usage data as well (and anything else that was seen to improve performance).

Second, creative. The more creative iterations marketers could provide to the system, the more likely they were to find a new winner and boost performance. Top performing marketing teams were creative-production machines, testing new iterations on a weekly or daily basis.

Yes, the conversion algorithm itself was a black box, but that didn’t stop paid marketers from reorienting themselves to do whatever they could to improve its performance at the margins.

So, let’s say you’re building a product with AI at its core. What does the example of Google’s conversion optimizer teach us about how you might design it?

First, build a proprietary data advantage. If you recall, Google launched conversion tracking long before launching conversion optimizer, so Google had all the conversion data they needed to build the initial model. Like Google, you need some sort of internal data to bootstrap the model at the start. It may be the case that an out-of-the-box LLM is good enough to get you started, but some sort of proprietary data will likely be key to long-term differentiation.

Second, enable your users to proactively improve the model. Like Google enabling marketers to pipe back every type of “conversion” they wanted, you need to empower your users to improve the model with external performance data as well. This has the additional benefit of making your product stickier. Not only will the model’s performance improve, it will be a user’s job to improve the model’s performance!

Third, give your users additional levers to pull. Like how marketers pivoted to extreme creative experimentation as a means of improving the model’s performance, think about what additional variables your users can iterate through. By giving your users tools to improve the model’s performance through experimentation, you’re creating users who will define themselves by how good they are at extracting the best performance from your system, improving stickiness even further (as we’ve learned in the past, customer-built products create power users and evangelists.)

Given how versatile LLMs are, it’s tempting to imagine a world where these models replace humans entirely…where they’re able to simply produce a “hole in the wall.” But, just as with Google’s conversion optimizer, I think the reality will be much more nuanced than that.

Until next time,
David

EVENTS

Mar 8 / The Evolution of Collibra’s Product Positioning & How They Created a Category
Stan Christiaens, Co-Founder & Chief Data Citizen, Collibra

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EUROPE & ISRAEL FUNDING NEWS

Israel/OEM Semiconductors. Chain Reaction raised $70M to produce chips used to compute encrypted data.
UK/Data Tooling Metomic raised $20M for its data security solution for protecting sensitive data in the new era of collaborative SaaS.
UK/SME Security. Cyber Smart raised $15M for its all-in-one cybersecurity and insurance solution for SMBs.

WORTH READING

ENTERPRISE/TECH NEWS

Wiz funding. Cloud cybersecurity startup Wiz has raised $300M at a whopping $10B valuation. There are three aspects of this raise which are interesting. 1) A late stage raise and valuation of this magnitude in 2023 is impressive. 2) Wiz was only founded in March 2020 — making it the fastest SaaS company to reach $10B. 3) Wiz’s CEO, Assaf Rappaport, has stated that the funds will remain in the US and not be invested in Israel, given the uncertainty around the country’s judiciary system.

Foundational models. Frontline’s Ruth Sheridan shares a terrific primer on foundational models like GPT-3, where she breaksdown how these models work under the hood.

Stripe & Adyen. After years as Silicon Valley’s darling, Stripe may be losing its shine. Stripe shares are trading at a huge discount to Adyen. The All In podcast dives deeper comparing the two companies and Stripe’s precarious situation, where it seems to have missed its window to go public.

HOW TO STARTUP

What’s in a name? Selecting a company name is one of the most important decision founders must grapple with. Startup name trends come and go. For a time there was mashing two words together, creatively misspelled words, dropping vowels, etc. What is the current startup naming trend? According to Crunchbase, “simple names composed of recognizable words have gotten super popular. Increasingly, founders appear to be prioritizing recognizability over uniqueness.” While short simple names are easily remembered, a downside is that these names are often shared by a number of companies. Another unsurprising name trend given the enthusiasm around generative AI, has been the addition of “AI” to company names. However, according to naming expert Michael Carr, ““that to me is a very short sighted strategy,” said Carr, regarding companies adding AI to their names. He compares it to the dot-com bubble, when companies routinely put .com in their names, only to remove the suffix later on.”

HOW TO VENTURE

The hard conversations. In last week’s newsletter, Gil wrote about having tough conversations with founders. Conveying difficult messages, like the need to cut burn, is one that many VCs are sharing with their founders. Y Combinator partners, Michael Seibel and Dalton Caldwell, expand on the topic. While having hard conversations can be uncomfortable, they argue that this transparency is essential. However, in a recent Angular Insights podcast, Jason Green from Emergence astutely reminds investors to have empathy for founders during these tough conversations: “I think it’s super important to have a lot of empathy and compassion as an investor for what emotionally an entrepreneur is going through in this situation. And remember that, we have a portfolio of companies, but this is everything to them. And it’s not just numbers we’re talking about.”

The VC customer. Following a tweet made by Dan Primack, where he stated that VC funds work “for their limited partners, not their portfolio companies”, USV’s Fred Wilson resurfaced his 2005 blog post on the topic of who actually is the VC’s customer. Fundamentally he states, “the entrepreneur is the customer and the LP is the shareholder. That’s the only way to think about the venture capital business that makes sense to me.” He concludes with a timeless and pertinent message on difficult conversations: “If you really view the entrepreneur as your customer, when you walk into their office with the hard news that you aren’t going to keep funding their company if it continues on its current path, or that you want them to step aside and bring in someone better suited to run the company, or that they need to get a coach and start behaving differently if they want to keep their job, you will deliver that news as a friend, a person who honestly cares about them and their dreams, and with compassion and understanding. And that is the only way to get through those really hard discussions with a chance of coming out the other side with a relationship.”

PORTFOLIO NEWS

Aquant was awarded as one of Built In’s 2023 Best Places To Work.

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