Early stage equity data & chatbots solve loneliness | Intent, 0013

We’re back after a hiatus! The last issue of Intent was August of 2023, so as a reminder: Intent is all about helping talent in tech become more intentional with their career by becoming more informed, more fluent, and more aware about the goings-on within tech and adjacent industries. We welcome your feedback!

• The agenda ahead:

  • A quick look at the latest equity compensation data coming out of Carta

  • Early evidence that large language models might curtail our loneliness epidemic

  • Three things worth reading/watching/listening to

  • Three interesting startups to watch (with jobs!)

Early stage equity compensation is complicated.

Carta’s Insights team released their latest first-5-employee equity data sourced from ~5,000 hires made in 2023. And the results are as unsatisfying as they are interesting: it’s all over the place!

When it comes to the compensation awarded to the first few team members at any given startup, it’s always been a bit random. So much is driven by the compensation philosophy of the founder(s) and how they view those team members. In some cases, a newly-minted startup CEO will see their first few hires as “founding team members,” giving them anywhere from 1 to 3 points of equity. In other cases, a CEO that has just done the tough work of raising their first round will consider their company somewhat de-risked, and offer those first few hires a percent of a percent (ex. 0.1% to 0.5%).

It’s a hard topic because so much of it is indeed contextual to a particular company. There might be two companies started on the same day that go through very different pre-hiring journeys – one might raise $500k, whereas the other raises $2M. One’s founder might be capable of contributing code, whereas the other might be dependent on the team they hire.

Depending on a matrix of factors, it’s easy to justify both sides of the equation – whether it’s “as a founder, I’ve moved this beyond idea stage, and so I will treat my hires as normal employees,” or “we’re still early, and so I want to recognize the risk and burden on each team member to get us toward the next phase.”

An interesting long tweet from equity expert Hari Raghavan argues that founders can and should do more in the current era of tech to reward the first few hires.

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Good news about LLMs and loneliness?

America is more lonely and depressed than ever [1] [2]. In the absence of society-wide interventions, there may be a strong case for research and development into AI-enabled solutions to fill the void. An academic survey released out of Stanford earlier this year zeroed in on the loneliness impact of Replika, a generative AI chatbot focused on offering users a more personal “AI companion.”

Users of the app were far more likely to have recently “experienced loneliness” in the recent past (90% compared to just 53% of the general population). But many of those individuals reported positive effects, including a greater likelihood to seek coaching and guidance from human counselors, more engagement in their interpersonal relationships with humans, and “approximately three times more participants reported their Replika experiences stimulated rather than displaced their human interactions”

Incredibly, 30 users (3% of their n) reported that “Replika helped them avoid suicide.”

Related —

• Today, OpenAI announced GPT-4o, their latest flagship model with reasoning capabilities across audio, vision, and text, alongside updates to their voice assistant to make it more real-time and human than ever before.

• In a reddit AMA on Sunday, OpenAI CEO Sam Altman mentioned that the company is striving toward enabling more personal, even NSFW use cases than they have in the past (though he explicitly mentions that they do not want to enable deepfakes).

• Replika has come into and out of fire over the past year for being the most popular AI companion of choice for those seeking a romantic or even erotic relationship. In 2023, when the company turned off sexual conversations and intimacy, users were livid – reporting that they relied on their AI companions and had even fallen in love with them.

Three pieces of content to digest:

1. Andrew Chen, partner at a16z and a prolific author of blogs + essays related to startup growth, wrote an intriguing piece about “Dopamine Culture” and its impact on things like spikey product growth and app retention.

2. Journalist-turned-investor (Google Ventures) MG Siegler dove into the madness of different streaming bundles, discounts, and offers, finding at least 20 different bundles offered by Disney — and proposing that we’re in a case of “We got what we wished for. And now we wish we hadn’t gotten [it].”

3. Google announced AlphaFold 3, their latest AI model capable of predicting the structure of proteins – read more about its potential to impact biological + drug discovery.

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Three interesting startups to watch, that are hiring!

1. Mammoth has raised just over $2M to solve supply chain productivity using AI – if you’ve ever worked in manufacturing, retail, etc., then you know just how much optimization is still up for grabs, and how genAI could be the solution for this data-wrangled problem. They’re hiring for a Founding Senior Backend Engineer and a Head of Customer Operations in NYC.

2. YC-backed Pylon is bringing workflow automation to customer issues – they integrate with a companies’ relevant comms tools to identify and track issues (like bugs and customer requests), then help build AI-enabled workflows for automated alerts, linking, and response. They’re hiring for a Founding Designer in SF, plus a few other roles.

3. If you’re interested in the startup studio model, Expa (started by Uber co-founder Garrett Camp) is hiring a Product Manager (LA or SF) to work with a new incubated company – very rarely do PMs get to dig in this early in a company’s lifespan.

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