“Admirer from outside of the cap table” is how I approached Kieran Snyder, Cofounder of Textio. That is to say, I DMed her on Twitter in 2016, impressed by the work she was doing but without a preexisting relationship. Thankfully the interest was mutual and we’ve had the chance to exchange thoughts here and there in the time since. When Kieran announced earlier this year she was stepping back from the CEO role at her company it seemed like a great time to (a) learn from her tenure and (b) promote her awesome weekly newsletter.

Hunter Walk: Textio, the startup you founded and CEO’ed until a few months ago, is almost 10 years old. When you think back to the founding vision/mission, what played out the way you expected and what was most different?

Kieran Snyder: We started off with a premise about AI and writing. Specifically, we thought that if you could use piles and piles of data to figure out which phrases, structures, and other linguistic characteristics performed the best with real audiences, then you could expose that data to help people write stuff that performed better. That premise turned out to be true, as we’re all seeing play out today with the rise of AI APIs that many applications are rushing to adopt.

Textio brought this vision to market with our first product, designed to help people write job posts that attracted diverse and qualified candidates. We had initially wanted to begin with a performance review product or a more conventional marketing product, but we started off in recruiting for very practical reasons: 1) We cared about the problem and 2) We were pretty sure we were going to win. We had some unfair competitive advantages in serving HR buyers: we knew them all. I was publishing quite a bit of original research about bias in workplace documents like performance reviews and job posts, a bunch of it went viral, and I got to know a lot of people who eventually became Textio customers.

However, we thought our initial focus on recruiting was a wedge – an important but small part of the enterprise communication market that we were going after. We way underestimated Textio’s stickiness within HR and how deeply HR execs would invest in Textio. We also underestimated how little we would want to fracture our go-to-market to explore other business writing use cases as the company grew. Today, you’d look at Textio and say it’s an HR Tech company. But that’s not really how we saw ourselves when we started.

HW: This was your first CEO run after a successful product management career. If 2024 Kieran could whisper something into the ear of 2014 Kieran, what would you have told her about the difference between leading a team vs leading a company?

KS: Being a CEO has a lot in common with being a product manager, except that the product you’re responsible for is the company itself. Because there are so many similarities, I often underestimated the differences, especially early on.

As a leader of teams within larger organizations, I was able to build phenomenal teams in terms of both delivery and culture. I did this in part by defining my team’s culture as being outside-the-norm; I worked hard to make sure that my team felt special in the context of the larger organization. My teams always had a recognizable identity and subculture. But when your team is the larger organization, you can’t use this strategy.

That being said, I’ve always been at my best as a leader when I embrace my passion for teaching and nurturing. It’s not an accident that I started out in academia or that I have coached kids’ sports for so many years. It’s also not an accident that, upon stepping back from being Textio’s CEO, I’ve built a sizable exec coaching practice working largely with early stage founders. I find it tremendously personally fulfilling to work with people to achieve their visions and see them grow.

As a CEO, I was at my best when I embraced this side of myself fully. I love leading workshops for the team on how to tell effective stories with data. I love working with customers to support them in meeting their goals. I even love leading a really meaningful performance feedback conversation. 

This work is my zone of excellence. If I could give 2014 Kieran one piece of advice from 2024 Kieran, it would be to center this much more explicitly in how I approached my job as CEO.

HW: nerd processor, your weekly newsletter, is great! A recent essay covered the ‘AI gold rush’ and as it related to startups operating in this area, very much ‘caution ahead’ in terms of building a sustainable, differentiated business. Are there specific paths/opportunities in AI that you believe startups are actually better qualified to take advantage of than incumbents?

KS: Isn’t this the trillion-dollar question? When it comes to AI applications, big companies have more competitive advantages than they ever have before, because they already own the workflows and data that can make AI features stickiest. Big companies are also rich with much more cash to fund AI investments and compute costs.

As I see it, startups have two major advantages. The first one is simply focus. Startups can build habits with customers in narrow wedge markets that might at first look too small for a big company to care about. However, the startups that will make this strategy work are not just building undifferentiated offerings by wrapping the same OpenAI APIs as everyone else. They are either building on some differentiated technology or more likely a differentiated data source – ideally a data source that is generated from within their own application, where the data is collected by default as people use their product. 

That leads me to the second advantage that startups have. They can design their products to be AI-native from the start, rather than having to bolt AI capabilities on as a layer on top of a foundation that was not designed for it. From the very start, they can design experiences and choose privacy policies that automatically collect proprietary data. Customers know what they’re getting when they first use the product and can make an informed choice.

Textio relied on both of these strategies for a few years before launching our first truly generative AI capabilities back in 2019.

HW: Textio is open to remote hires from a specific set of states which I found interesting. Is that administrative (those are places you already have to deal with taxes, payroll, etc) or was there another reason? How did Textio get smarter about remote teams over time?

KS: For the first several years of Textio’s life, our team was entirely co-located in Seattle. Jensen and I had colocation as religion, and our team was incredibly tight-knit. To this day, if you ask people who worked at Textio in 2018 what they most valued about their experience at the company, they will talk about the caliber of their coworkers and the energy they felt building alongside teammates in the office.

By the time the pandemic started, we had brought on a couple of sales people in New York and San Francisco, but we were still 95% colocated in Seattle. Like everyone else, we went distributed overnight in March 2020. When it became clear that we weren’t heading back to the office right away, lots of our team members wanted to relocate to be closer to loved ones. Most people wanted to go to a specific handful of other states, so we opened those states.

Since we were already doing business in those states, it made sense to start hiring new people there too. In the medium term, we ended up prioritizing a combination of places where current employees wanted to live and those where we could tap into a great local talent pool. And that’s still where Textio is today. We’ve talked about using a PEO to open up even broader geography at scale, but the work to do this hasn’t made the prioritization cut because we can already find so many qualified, diverse team members within our existing locations.

HW: I think of you first and foremost as a founder, not a ‘female founder.’ That said, as a woman you have a perspective on the ecosystem which I lack. Set aside the people who think our community is already a meritocracy – we’re not going to convince them – but is there something that even well-intentioned VCs do with female founded/led startups that is harmful or could be improved?

KS: The reason I have always liked using quantitative data to talk about industry bias is that data is a language that technologists already speak. 

Right or wrong, it’s easy for people to discount individual stories about bias in the industry. But if you can look at hundreds of thousands of written performance reviews across the Fortune 500 and see that Black people get 25% less written feedback at work than white people, or that women are 20 times more likely to be described as abrasive, or that the word ambitious is used to compliment men but punish women – well, that’s a lot harder to argue with. I love quantitative data based on real workplace documents because you don’t have to stretch to show what’s going on.

The best VCs are outstanding at analyzing data to find patterns and using those patterns to make decisions. But investors rarely use their analytical skills in the context of understanding their own interactions with founders. 

One example: As I’ve ramped up my coaching and advising work with founders, it’s striking how much more often the female CEOs I work with are pushed to sign away major decision rights compared to the male CEOs. Why does this happen? I doubt it’s because investors consciously trust the women less. It’s more likely because the women on average get fewer term sheets overall. When a founder has fewer options, investors typically push them to make more concessions on terms.

This is just one example of many that compounds over time, and could be studied with real data. Huh, maybe I’ll do that for a future nerd processor!

Thanks Kieran! Everyone should subscribe to her free newsletter.