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BIG NEWS: We launched an AI jobs board at Athyna. If you are looking for jobs in AI, whether that’s typical tech jobs inside of the leading AI firm, or AI/ML, and post-training roles, we have you covered. Find roles at Anthropic, OpenAI, Mistral, ElevenLabs, Perplexity, Midjourney, Google's AI teams, Harvey, and a long tail of AI-first startups.

Not only that, Athyna’s AI watches all of them for you. We match their openings to your profile and ping you when a strong fit shows up. Wherever the frontier moves next, you'll hear about it first. Sounds pretty great, right? Anyway, let’s jump into today’s interview.

INTERVIEW 🎙️

Ethan Ding, Co-Founder & CEO at TextQL

Ethan Ding is the Co-Founder & CEO of TextQL, a New York-based AI data platform he started in 2022 with Co-Founder & CTO Mark Hay. TextQL builds AI agents that let enterprises query their data across every existing system, without migrating anything. The AI agent, called ‘Ana’, connects directly to a company's BI tools, warehouses, and documentation, and lets anyone ask plain-language questions and get answers in seconds rather than days. Customers include Amazon, Dropbox, Scale AI, and Blackstone. In April 2026, TextQL raised $17M in strategic investment led by Blackstone’s early-stage investment arm, bringing total disclosed funding to $21.1M. Before TextQL, Ethan held data and research roles at Bessemer Venture Partners and Contrary VC. He writes a newsletter on AI cost curves and enterprise infrastructure that has been cited by Ben Thompson, Reid Hoffman, and TBPN.

Ethan describes his entire career as one long, barely-controlled frustration with the status quo. The first two years of TextQL were, by his own account, a disaster: wrong product, churned customers, models that didn't work, a full rebuild. What kept them going wasn't a plan so much as an inability to accept that the problem wasn't solvable. The company that came out the other side has a blunt thesis: every enterprise has messy data, nobody has fixed it in 20 years, and the agents that can finally navigate that mess without demanding a migration first are going to eat the incumbents. Ethan has opinions about that, and he is not shy about sharing them.

What’s the problem you are trying to solve, and why?

The problem we're trying to solve is that it takes people a long time to get access to their data. They hear: our data is not ready, it's garbage in, garbage out, we haven't cleaned it up or moved it into one system. Every single system in the ecosystem wants you to migrate into their own system (whether it's a BI tool, whether it's a data warehouse). We want to be very clear with our messaging that we are agnostic to all the other systems. Our goal is to make it so that you can query from all those places without having to migrate, without having to do anything, as is.

What was the most difficult when going from zero to one?

For the first two years, the product just didn't work. The language models weren't there, the infrastructure wasn't there. We churned almost all our customers and had to constantly rebuild the product. It was a pretty extensive period of ‘are we going to make it? Is this product going to work? Is this space going to work out at all?’ There were a lot of losses to take along the way.

I don't know if there was a specific day, but I remember one where we sat down in the office and it was just ‘everything is terrible’. We'd just churned a customer and then tore down the entire product from scratch and started whiteboarding. There were six of us. We all grabbed beers and went for a walk on the Brooklyn Bridge. We were just like: we're going to remember this as the worst time. And yeah, it's gone pretty well since then.

What is your main day-to-day job as CEO?

Right now it's a lot of modeling the best behavior for the team. We have a lot of new salespeople and new forward-deployed engineers who don't yet have a strong intuition for how to pitch the product or position against others. This space is relatively immature (we're still growing it) and we're trying to figure out the right messaging.

The team is roughly split in three between sales, forward-deployed engineering, and regular engineering. Everyone on the non-engineering side rolls up to me, while everyone on the engineering side rolls up to my Co-Founder, Mark.

What’s your ideal ICP and how you identify them?

Our ideal ICP is anyone with messy data, which is basically every large enterprise. The messier the data, the bigger the difference we can make. It was actually fairly recent that we landed on this messaging. If you tell someone you can build AI that accurately handles their stuff, they'll ask: how do you deal with things that make accuracy harder? And it's like: why don't we just go one level up? We built AI for people with extremely hard-to-make-sense-of data.

That framing just lands better. It feels like a more believable thing in the structural messaging of what you say. We have customers across six continents—five, actually, Antarctica doesn't really count—but by far the majority of our volume is in the United States.

How are you infusing AI operationally day-to-day?

Almost everyone on the team uses Claude. Every single person uses our internal agent for analytics too. It's kind of a requirement of the job. Our agent handles our CRM updates, scheduling, emailing, mailing list management, and all of our data integration work. All of our dashboards and all of our assets are built from the existing product. We basically eat our own cooking entirely.

How do you get the best out of yourself personally and professionally?

Growing up, I've always been extremely easily frustrated by the status quo; by things around me. It's basically dissatisfaction and rage boiling up inside. In terms of channeling it responsibly.

I'm extremely self-deprecating. I make a lot of jokes about how bad I am at my job and all the mistakes I make. I do my best to create a culture where people can tell me I'm wrong. I try to model the fact that I'm wrong all the time, and on the back of that, that shapes the kind of feedback I get, which I can actually work with.

Extra reading

• TextQL Raises $17M to Help Bring Intelligence to Enterprise Data - April, 2026

• The startup Blackstone just backed to turn any exec’s data question into instant answers - April, 2026

• Building AI for Petabyte-Scale Enterprise Data - October 2025

And that’s it! You can follow Ethan on LinkedIn, his newsletter, or check out TextQL on their website to keep up with what they’re building!

BRAIN FOOD 🧠 

TWEETS OF THE WEEK 🐣 

TOOLS WE RECOMMEND 🛠️

Every week, we highlight tools we like and those we actually use inside our business and give them an honest review. Today, we are highlighting Thesys*—a Generative UI company that helps anyone build AI apps and agents that respond with interactive UI like charts, forms, cards, tables, and more, instead of walls of text.

See the full set of tools we use inside of Athyna & Open Source CEO here.

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